Document Title - Sanjeev Sabhlok's blog
The Glorious Abundance and Creativity of the Robotic Age
Sanjeev Sabhlok
Preliminary Draft 27 Feb 2015
This is very preliminary.
Happy to receive input at sabhlok@
Apple, Amazon, Facebook and Google – combined – have something close to $1 trillion in market capitalization. Together, the four of them employ fewer than 150,000 people.
To maintain that human labor will ever come to want employment, would be to maintain that the human race will cease to encounter obstacles. In that case labor would not only be impossible; it would be superfluous. We should no longer have anything to do, because we should be omnipotent; and we should only have to pronounce our fiat in order to ensure the satisfaction of all our desires and the supply of all our wants. [Bastiat, Economic Sophisms]
Note that
we still haven’t produced machines with common sense, vision, natural language processing, or the ability to create other machines. Our efforts at directly simulating human brains remain primitive. [Source]
Note also that robots will NEVER become alive.
Peter Diamandis has argued that advances in A.I. will be one key to ushering in a new era of “abundance,” with enough food, water, and consumer gadgets for all. Skeptics like Eric Brynjolfsson and I have worried about the consequences of A.I. and robotics for employment. But even if you put aside the sort of worries about what super-advanced A.I. might do to the labor market, there’s another concern, too: that powerful A.I. might threaten us more directly, by battling us for resources. [Source]
Contents
1. Key books on this topic 1
1.1 Books 1
1.2 Articles 1
2. From around 2000 AD: the Early Robotic Age 3
2.1.1 Autonomous economy 5
2.2 Video introduction to the issues 5
2.3 Agricultural age as a major discontinuity from the hunting gathering age 5
2.3.1.1 The Artilect Age 6
2.4 Are there any ‘hard limits’ on advances in robotics/AI? 6
2.4.1 Hardware limits 6
2.4.1.1 Silicon computer have limits 6
2.4.1.1 Molecular computers 6
2.4.1.2 Quantum computers will breakthrough to an unbelievable level 6
2.4.1.3 Nanocomputers 6
2.4.2 Software limits 7
2.4.2.1 Artificial intelligence 7
2.4.2.2 Object recognition 8
2.4.2.3 Machine learning 8
2.4.2.4 Rat Brain simulation 8
2.4.2.5 Human Brain Project 8
2.4.2.6 Quantum computer programming 8
2.5 Three key scenarios 8
2.5.1.1 I.J. Good’s Intelligence explosion concept 9
2.6 Long term structural change in Australia 10
2.7 Industrial machines supplemented muscle. Robots supplement our senses and brains 11
2.8 The ‘coming of age’ of robots 12
2.8.1 What are robots? 12
2.8.2 Maturation of many related technolgies 13
2.8.2.1 Genome mapping 13
2.8.2.2 3-D printing 14
2.8.2.3 Biological computers 14
2.8.2.4 Neural networks 14
2.8.2.5 Recreation of detailed map of the brain 14
2.8.2.6 Fusion 14
2.8.2.7 Nanotechnology/nanorobots 15
2.9 What can robots do? 15
2.9.1 Physical 15
2.9.1.1 2-legged robots can walk in the midst of people and on rough surfaces 15
2.9.1.2 4-legged robots can run faster than humans 15
2.9.1.3 4-legged robots can carry loads and walk faster uphill than humans 15
2.9.1.4 Extreme athleticism in running/flying 16
2.9.1.5 Can jump 30 feet 16
2.9.1.6 Can fight and ‘kill’ other robots 16
2.9.1.7 Can dance /play games 16
2.9.2 Dexterity 16
2.9.2.1 Can bounce balls and catch objects with fingers 16
2.9.2.2 Have extremely fine ‘hand-eye’ coordination 16
2.9.2.3 Can drive trains 16
2.9.2.4 Can drive cars and trucks and fly planes 16
2.9.2.5 Can fly helicopeter upside down 17
2.9.3 Verbal 17
2.9.3.1 Can talk 17
2.9.3.2 Can sing 17
2.9.4 Creative 17
2.9.4.1 Can sketch and make oil paintings (eDavid) 17
2.9.4.2 Can make music (bands) 17
2.9.5 Cognitive computing 17
2.10 Major signs that the robotic age is upon us 18
2.10.1 Significant acceleration in capability 18
2.10.1.1 Already we have a computer equal to human brain in processing power 18
2.10.1.2 Predictions 18
2.10.1.3 Significant acceleration (second half of the chessboard) 18
2.10.1.4 Significant acceleration in AI 19
2.10.2 The commercial case for robots 19
2.10.2.1 Dramatically falling robot prices 19
2.10.2.2 The rise of the multi-purpose robot 19
2.10.2.3 Many other advantages of robots 19
2.10.3 Evidence of commercial deployment 19
2.10.3.1 Size of robotics industry 19
2.10.3.2 Number of WorkCover claims reducing 20
2.10.3.3 Number of robots increasing 20
2.10.3.4 Manufacturing is shifting back to the West 21
2.10.3.5 Suddenness of change 21
2.11 Who’s driving this rapid change? 22
2.12 Key organisations 22
2.12.1 IFR (International Federation of Robotics) 22
2.12.2 DARPA 22
2.12.3 Pentagon 22
2.12.4 Boston Robotics 23
2.12.5 Universal Robots 23
2.12.6 Yamaha 23
2.12.7 iRobot 23
2.12.8 Rethink Robotics 23
2.12.9 Key publicly traded robotic companies 24
2.12.9.1 Healthcare Applications: 24
2.12.9.2 Defense, Security and Space Applications*: 24
2.12.9.3 Industrial and Co-robot Applications**: 24
2.12.9.4 Ancillary businesses to the robotics industry: 25
2.13 Opinions 26
2.13.1 Mostly positive (an overall good, will happen slowly, society will adjust) 26
2.13.1.1 Ray Kurzweil 26
2.13.1.2 William Lazonick 26
2.13.1.3 Hal Varian 26
2.13.1.4 Dr. Michio Kaku 27
2.13.1.5 Frank Levy and Richard Murnane 27
2.13.1.6 Robin Hanson 27
2.13.1.7 W. Brian Arthur 27
2.13.1.8 Mark Thoma 27
2.13.1.9 Eliezer Yudkowsky 27
2.13.1.10 Laurence Katz 27
2.13.1.11 Robert Atkinson 27
2.13.1.12 Nick Bloom 28
2.13.2 Mostly negative (i.e. this is a big issue for society) 28
2.13.2.1 Andrew McCaffee and Erik Brynjolfsson 28
2.13.2.2 Jeffrey Sachs and Lawrence Kotlikoff 29
2.13.2.3 Martin Ford 29
2.13.2.4 Kevin Drum 29
2.13.2.5 Tyler Cowen 29
2.13.2.6 PBS 35
2.13.2.7 Paul Krugman 35
2.13.2.8 Izabella Kaminska 35
2.13.2.9 Alex Hern 35
2.13.3 Confused 36
2.13.3.1 Federico Pistono 36
2.13.3.2 Peter Diamandis 36
3. Examples of robotic innovations (including AI) 37
3.1 Smart assistants 37
3.1.1 Expliner High-Voltage Power Transmission Line Inspection Robot 37
3.1.2 Spare tyre mounting robot 37
3.1.3 Packing assistant 37
3.1.4 Automated vacuum cleaners 37
3.1.5 Toys 38
3.1.6 Hospital assistants 38
3.1.6.1 Medicine Picking and Delivering Robot System 38
3.1.6.2 Surgical assistants 38
3.1.6.3 Heavy lifter 39
3.1.7 Military assistants 39
3.1.8 Police assistants 39
3.1.8.1 Spying robot: 39
3.1.8.2 Robot micorobots/insects 39
3.1.9 Agriculture and fisheries assistants 39
3.1.10 New forms of transport 39
3.1.11 Manager’s assistants 39
3.1.12 Bee pollination assistant 39
3.2 Workers (in manufacturing) 40
3.2.1 Industrial robots 40
3.3 Workers (in retail/service industry) 40
3.3.1 Burger maker 40
3.4 Humanoid robots 40
3.5 Personal assistants 40
3.5.1 Translators 40
3.5.2 Walking assistant 40
3.5.3 Housemaid 40
4. Robots will NEVER become alive 41
4.1 Kurzweil is wrong. Robots will never have a WILL TO LIVE. Hence never will displace man. 41
5. Economic issues and concerns 43
5.1 GDP as an increasingly irrelevant measure of income 43
5.1.1 Digital goods are not traded 43
5.1.2 Consumer surplus is not measured 43
5.2 Glorious abundance doesn’t mean absence of scarcity 43
5.3 Machines and humans: complements or substitutes? 43
5.4 Cost/benefit of robots/IT/technology 43
5.4.1 Capital robots and consumption robots 43
5.4.2 Economics of drones 44
5.5 Say’s law and robotics 44
5.6 Overall increase in prosperity/luxury 44
5.6.1 Productivity and growth 44
5.6.1.1 The May 2013 McKinsey report 44
5.6.2 Increased expectations 55
5.6.3 Really low prices 55
5.6.4 Laws of investment will not change 56
5.6.5 Rising manufacturing productivity 57
5.6.6 Increasing share of services in economic output 57
5.7 Effect on innovation and entrepreneurship 58
5.7.1 Start-ups are cheaper 58
5.8 Effect on labour share 59
5.8.1 Workers’ bargaining power significantly reducing 59
5.8.2 But labour share was much lower in the past 59
5.8.3 Industries where significant loss in labour share is occurring 60
5.8.4 Most importantly, labour share is irrelevant 61
5.9 Effect on jobs 61
5.9.1 View of The Economist 65
5.9.2 Job polarisation 66
5.9.3 Derived demand for resources and labour 68
5.9.4 Many new jobs created by technology 68
5.9.4.1 Kinds of new jobs created 69
5.9.4.2 Number of new jobs created 69
5.9.4.3 Industrial robotics has created 350,000 new jobs 69
5.9.5 But job creation slower than job loss 70
5.9.6 Part time jobs 71
5.9.7 More low-paying jobs will be created 71
5.9.8 Kinds of jobs that are in the process of going 72
5.9.9 Jobs which have gone 73
5.9.9.1 Library 74
5.9.9.2 Stevedores 74
5.9.9.3 Mining truck drivers 74
5.9.9.4 Iphone workers 74
5.9.9.5 Warehousing workers 75
5.9.9.6 Banks 75
5.9.9.7 McDonald’s cashiers 75
5.9.9.8 Telephone directory assistance 75
5.9.9.9 Datacentre IT staff 75
5.9.10 Jobs which are next in line 75
5.9.10.1 Overall analysis 75
5.9.10.2 Administration/bureaucrats 76
5.9.10.3 Call centres and helpdesk 76
5.9.10.4 Lawyers 76
5.9.10.5 Retail 76
5.9.10.6 Butchers (abattoirs) 77
5.9.10.7 Doctors 77
5.9.10.8 Receptionists 78
5.9.10.9 Call centres 78
5.9.10.10 Pharmacies 78
5.9.10.11 Fruit harvesters 78
5.9.10.12 Dusting crops with pesticides 78
5.9.10.13 Cleaners 78
5.9.10.14 Package delivery 78
5.9.10.15 Security guards 79
5.9.10.16 Assembly/packaging workers 79
5.9.10.17 Farmers 79
5.9.10.18 Dairy farmers (robotic dairy) 79
5.9.10.19 Pilots 79
5.9.10.20 Financial services and financial market traders 79
5.9.10.21 Construction industry 79
5.9.10.22 Drummers/ musicians 79
5.9.10.23 Age carers (Social Assistive Robots) 80
5.9.10.24 Housemaids 80
5.9.10.25 Ship repairers (underwater) 80
5.9.10.26 Waste disposal 80
5.9.10.27 Truck drivers 80
5.9.10.28 Taxi drivers 80
5.9.10.29 Astronauts 80
5.9.11 Jobs which are mostly safe 80
5.9.11.1 IT related 81
5.9.11.2 Plumbers 81
5.9.11.3 Electricians 81
5.9.11.4 Construction industry workers 81
5.9.11.5 Hairdressers 81
5.9.11.6 Gardeners 81
5.9.11.7 Old age carers and nurses 81
5.9.11.8 Key government agencies (police, justice, defence) 81
5.9.11.9 Comedians 81
5.10 The flourishing of creativity 81
5.10.1.1 Creative artists, writers and entertainers 81
5.10.1.2 Exercise and fitness trainers 81
5.10.1.3 Interior designers 81
5.10.1.4 Yoga teachers 81
5.10.1.5 Spiritual gurus 81
5.10.1.6 Psychologists and social workers 81
5.11 The challenge for unskilled youth 81
5.12 Effect on wages 82
5.12.1 Fact: Relative share of wages in GDP decline 82
5.12.2 Hypothesis: Not technology but globalisation 83
5.12.3 Hypothesis: Permanently reduced wages 83
5.12.4 Hypothesis: wages may not fall 83
5.13 Effect on employment 83
5.13.1 The less educated have less of a chance of finding jobs now 83
5.13.2 Lower labour participation 84
5.13.3 Employment may not fall in the long run 84
5.13.3.1 There could be short run pain 85
5.13.3.2 Hours worked by everyone may fall 85
5.14 Increased inequality 85
5.14.1 Median income barely growing 86
5.14.1.1 USA 86
5.14.1.2 Australia 87
5.14.2 Divide between rich and poor rapidly growing 87
5.14.3 Share of corporate profits rising 88
5.15 Effect on asset values 88
5.16 Rout of the middle class 88
5.17 Education is the FOUNDATION of robotics/IT revolution 88
5.18 Reduced traffic congestion 89
5.19 Changing government services 89
6. Social (and political/legal) consequences 91
6.1 Will liberate women 91
6.2 Ethics of robotics 91
6.2.1 Isaac Asimov's "Three Laws of Robotics" 91
6.2.2 Will robots take over the world? 91
6.2.3 Humans shouldn’t be doing such jobs anyway 92
6.3 Regulatory impact/ regulation of robots 92
6.3.1 Privacy issues 92
6.3.2 The dissolution of the nation state 92
6.4 Need for appropriate market mechanisms, business models and regulatory policy 93
6.5 The problems of the unemployed 93
6.5.1 Meaninglessness 93
6.5.2 Mass leisure 93
6.5.3 Negative effects of expectorations 93
7. Effect on nations 94
7.1 Developed nations 94
7.1.1 Effect of robotics on USA 94
7.1.2 Effect of robotics on Australia 95
7.2 Developing nations 95
7.2.1 Effect of robotics on China 95
7.2.2 Effect of robotics on India 95
7.2.2.1 India has missed the boat 95
7.2.2.2 India has virtually no chance of being a manufacturing nation now 95
7.2.2.3 India is going to continue to lose top IT talent to the West 95
7.2.2.4 Robotics research in India 96
8. Economics of extreme longevity (even some form of immortality) 97
8.1 Pensions 97
8.2 Further reading on the biology/economics of immortality 98
9. Should we be concerned? Should the government do anything? 99
9.1 A new equilibrium will soon emerge 99
9.2 Some good policies 99
9.2.1 Greater competition and regulatory reform 99
9.2.2 Attract innovators/talent from across the world 99
9.2.2.1 The exodus of talent from Silicon Valley 99
9.2.2.2 Need for talent-friendly policies 100
9.2.3 If you do need to spend on innovation, spend on robotics/AI/nanotechnology 100
9.2.4 Retraining 100
9.3 Bad policies 100
9.3.1 Progressive taxation 100
9.3.2 Redistribution 100
9.3.2.1 Citizen’s income 100
10. References 101
10.1 Key blogs on robotics 101
10.2 Economics of a robotic economy 101
10.3 Science of robotics 101
10.4 Ethics of robotics 104
Key books on this topic
1 Books
Brynjolfsson, E. and McAfee, A. (2011). Race against the machine: How the digital revolution is accelerating innovation, driving productivity, and irreversibly transforming employment and the economy. Digital Frontier Press Lexington, MA.
2 Articles
Carl Benedikt Frey and Michael A. Osborne, The Future of Employment: How Susceptible are Jobs to Computerisation?
Acemoglu, D. (2002). Technical change, inequality, and the labor market. Journal ofEconomic Literature, vol. 40, no. 1, pp. 7–72.
Acemoglu, D. (2003). Labor- and capital-augmenting technical change. Journal of the European Economic Association, vol. 1, no. 1, pp. 1–37.
Acemoglu, D. and Autor, D. (2011). Skills, tasks and technologies: Implications for employment and earnings. Handbook of labor economics, vol. 4, pp. 1043–1171.
Ackerman, E. and Guizzo, E. (2011). 5 technologies that will shape the web. Spectrum, IEEE, vol. 48, no. 6, pp. 40–45.
Atkinson, A.B. (2008). The changing distribution of earnings in OECD countries. Oxford University Press.
Autor, D. and Dorn, D. (2013). The growth of low skill service jobs and the polarization of the US labor market. American Economic Review, vol. forthcoming.
Autor, D., Katz, L.F. and Krueger, A.B. (1998). Computing inequality: have computers changed the labor market? The Quarterly Journal of Economics, vol. 113, no. 4, pp. 1169–1213.
Autor, D., Levy, F. and Murnane, R.J. (2003). The skill content of recent technological change: An empirical exploration. The Quarterly Journal of Economics, vol. 118, no. 4, pp. 1279–1333.
Beaudry, P., Green, D.A. and Sand, B.M. (2013). The great reversal in the demand for skill and cognitive tasks. Tech. Rep., NBER Working Paper No. 18901, National Bureau of Economic Research.
Bresnahan, T.F., Brynjolfsson, E. and Hitt, L.M. (2002). Information technology, workplace organization, and the demand for skilled labor: Firm-level evidence. The Quarterly Journal of Economics, vol. 117, no. 1, pp. 339–376.
Charles, K.K., Hurst, E. and Notowidigdo, M.J. (2013). Manufacturing decline, housing booms, and non-employment. Tech. Rep., NBER Working Paper No. 18949, National Bureau of Economic Research.
Cohn, J. (2013). The robot will see you now. The Atlantic, February 20.
Goldin, C. and Katz, L.F. (2009). The race between education and technology. Harvard University Press.
Goos, M. and Manning, A. (2007). Lousy and lovely jobs: The rising polarization of work in Britain. The Review of Economics and Statistics, vol. 89, no. 1, pp. 118–133.
Goos, M., Manning, A. and Salomons, A. (2009). Job polarization in europe. The American Economic Review, vol. 99, no. 2, pp. 58–63.
Gray, R. (2013). Taking technology to task: The skill content of technological change in early twentieth century united states. Explorations in Economic History.
Guizzo, E. (2008 July). Three engineers, hundreds of robots, one warehouse. IEEE Spectrum. three-engineers-hundreds-of-robots-one-warehouse.
Hanson, R. (2001). Economic growth given machine intelligence. Technical Report, University of California, Berkeley.
Levy, F. and Murnane, R.J. (2004). The new division of labor: How computers are creating the next job market. Princeton University Press.
Markoff, J. (2011). Armies of expensive lawyers replaced by cheaper software.
Markoff, J. (2012 August). Skilled work, without the worker. The New York Times.
Mims, C. (2010 June). AI that picks stocks better than the pros. MIT Technology Review.
Nordhaus, W.D. (2007). Two centuries of productivity growth in computing. The Journal ofEconomic History, vol. 67, no. 1, p. 128.
IFR (2012a). 68 robots perform farmer’s work. Tech. Rep., Case study of Fanuc Robotics Europe S.A., International Federation of Robotics, September 2012.
MGI (2011). An economy that works: Job creation and America’s future. Tech. Rep., McKinsey Global Institute.
MGI (2013). Disruptive technologies: Advances that will transform life, business, and the global economy. Tech. Rep., McKinsey Global Institute.
Woolf, B.P. (2010). Building intelligent interactive tutors: Student-centered strategies for revolutionizing e-learning. Morgan Kaufmann.
From around 2000 AD: the Early Robotic Age
Robert Solow, who won the Nobel Prize in 1987 for his macroeconomic research on economic growth, including on the role of technology, says that “advances in technology always throw people out of work,” but that “the economic history so far is that aggregate employment—and employment at rising wages—has not suffered.” [Source]
"Man is the lowest-cost, 150-pound, nonlinear, all-purpose computer system which can be mass-produced by unskilled labor" NASA (1965).
The writing is on the wall. The world is changing very rapidly and we need to start thinking about it, partiucalarly from the economic policy perspective.
It was not just a transformation of technology from hunting-gathering to agriculture that led to civilisation. The transformation had to be supported by a few key factors:
a) a crop sufficiently sturdy to be stored for years (e.g. wheat/rice);
b) domestic animals that provided both protein and animal horsepower; and
c) sufficient surplus in food production to allow enough creative humans to think of innovative ways to do things (such as smelt metal).
The agricultural revolution provided a CREATIVE DIVIDEND through the surplus so produced [see: Jared Diamond’s Guns, Germs and Steel].
With the industrial age we now need only 2 per cent of humankind to tend to agriculture. The remaining 98 per cent do other creative things.
With the robotic age, we will need less than 0.1 per cent of humankind to produce food. All others, 99.9 per cent, will be able to engage in creative work.
That is why the Robot Age will be the age of Glorious Creativity. It will also be the age where stupid nations like India, determined to produce roads by hand, determined not to let go their small-village agricultural heritage, will become VASTLY POORER compared to those (like China) who adopt the Robotic Revolution.
* * *
Julian Simon always said that the Human Brain is the Ultimate Resource. And he was right.
I've spent some time over the past week in analysis of the issues involved in the Robotic Age and although I haven't articulated my conclusions in any detailed form yet, and I'm still reading and thinking, I'm now VERY confident that there is NOTHING TO BE CONCERNED ABOUT (about the Robotic Age) for those nations which follow high quality governance and economic policies. (This, of course, rules out a good future for nations like India with socialist policies).
Strong adjustments are at work in the world today. The KEY shift is towards two main industries: IT and creative.
In the rush to blame robots and IT for loss of jobs, people are forgetting that the rich are beginning to pay significant amounts of money for 'soft' expertise which improves their QUALITY of life. This includes personal fitness coaches, personal life coaches, yoga teachers, and spiritual advisers.The arts are also flourishing. More museums, more production of art. More music, more sports.
I believe that FOR THOSE COUNTRIES which follow good governance and competitive policies, there lies an era of SUPER-RICHES ahead.
There will likely be some further increase in inequality but let's not forget that inequality is NEVER an issue. The key issue is human flourishing. And that seems guaranteed – for those nations which keep their economies fit, lean and agile.
A flourishing creative class will take the 'mid-tier' jobs earlier taken by the non-creative boring clerks and managers. Dilbert is dead.
Within each clerk is a singer/ writer/ poet or artist. It is time to wake up your creative inner being. Or you can choose to be a nerd. Both nerds and creative people will earn well.
Those who are neither nerds nor creative will be come SERVANTS of the rich. Nothing wrong with that. By servants I mean the service industry – waiters/ nurses/ aged care workers/ gardeners/hairdressers, etc.
Does the government have to do anything?
I firmly oppose the ideas of socialists like Paul Krugman who are trying to increase socialist policies and further destroy USA in the guise of solving the 'unemployment' problem arising from the Robotic Age. Such people should, instead, ask the young to re-skill themselves – and spend more effort in the creative fields.
Remember, low end jobs are still lucrative in terms of purchasing power, as quality of products increases and prices fall [Peter Schiff]
This book is a warning to anyone who wants government bureaucrats and politicians to meddle with the new economy. ANY UNNECESSARY MEDDLING will lead to seriously harmful consequences.
Let the market work out which kinds of jobs it wants and reward. This is known as creative destruction (or what I call in BFN (online notes), creative replacement.
Peter Schiff’s view:
a) This is short and crisp summary of key issues related with robotics. Robotics is NOT fundamentally different to any other technological change of the past. What it will do is prompt a radical shift towards more useful/creative work. There will NEVER be a time when creative (paid) work comes to an end. If nothing else, people will pay to watch good computer game players - as they do in S.Korea.
b) Also here:
In my view the greatest problem to the new economy will be redistributive policies of the government which prevent readjustment of people to creative or service-oriented jobs.
|So let’s begin our analysis of these assertions by starting out with a classic Robinson Caruso example. Mr. Caruso is alone |
|on his island and he must produce everything necessary for his survival and comfort by himself. Mr. Caruso must fish for |
|food, build a house, procure water for drinking and cooking, farm a field for crops, weave his own clothing, etc.. etc.. |
|What would happen if one day a plane flew over his island and parachuted him a fishing robot? The robot could fish for him, |
|procuring fish 24 hours a day 7 days a week. Does anyone think Mr. Caruso would be upset by this? Wouldn’t the robot free |
|him to focus on all the other tasks that are necessary for his survival? |
|What if we now gave Mr. Caruso an entire army of robots capable of fishing, weaving, building, etc.. etc.. Would this leave |
|Mr. Caruso without anything to do? Of course not. Mr. Caruso could now focus on even further improvements to his condition, |
|beyond what the robots are already providing him with. He might work on creating an air conditioning system, or art for the |
|walls of his home, or solving some other problem that the robots have not yet been programmed to solve. Not until every |
|single problem facing humanity as a whole has been solved would Mr. Caruso be left without something productive to do. |
|Because robots are not capable of coming up with novel solutions to human problems, and because human problems are virtually |
|limitless, humans will always have something productive they could be doing. Robots will never be able to replace the |
|creativity of the human mind, which requires a consciousness not present in any machine. [Source] |
1 Autonomous economy
“W. Brian Arthur, a visiting researcher at the Xerox Palo Alto Research Center’s intelligence systems lab and a former economics professor at Stanford University, calls it the “autonomous economy.” [Source]
2 Video introduction to the issues
Raffaello D'Andrea: The astounding athletic power of quadcopters.
Robert Hanson and Martin Ford
Erik Brynjolfsson
Andrew McAffee
I tend to side broadly with Hanson and Peter Schiff.
3 Agricultural age as a major discontinuity from the hunting gathering age
This innovation allowed mankind to significantly increase in population and knowledge. But this was nothing compared with the discontinuity which came with the industrial age in around 1750 AD.
From about 2000 AD, another significant discontinuity has occurred with robotics and AI, allowing further significant increases in productivity. A schematic diagram is provided below to illustrate the concept.
[pic]
1 The Artilect Age
There is a view that the next stage after robotics is artilects in which robots become millions of times more intelligent than humans, leading to the “Artilect War” (“artificial intellect”). This view, by Hugo de Garis, is extremely controversial.
His idea is that just like we slap mosquitoes, the artilects might ‘slap’ us if we become a pest.
I disagree fundamentally with this concept. Artilects can’t be ‘risky’ to mankind since they do not have a MOTIVATION (emotional) to become better off. They do not have a ‘soul’, either. They will therefore always remain as our dutiful servants. The key to success is adaptability, and it very unlikely that AI/artilects will have sufficient adaptability.
The richness and diversity of human motivation entirely distinguishes us from robots/artilets. If any harm is caused, it will be through a human being who misuses the artilects for personal gain.
4 Are there any ‘hard limits’ on advances in robotics/AI?
1 Hardware limits
1 Silicon computer have limits
By 2020 intelligence will be everywhere (ubiquitous computing), embedded in everything.
Robotics is based on the SILICON chip. It is limited by Moore’s law and the laws of thermodynamics. “Moore’s Law states that the number of transistors on a chip doubles every 18 months. This trend has been valid for over 40 years and is likely to continue until around 2020, by which time we will be able to place one bit of information on a single atom. These atom-bits will be able to switch their state (a 0 or a 1) in femtoseconds, which are quadrillionths (1015) times of a second. There are a trillion, trillion (1024) atoms in a handheld object, such as an apple, so potentially, the information processing capacity of such an object would be about 1040 bits per second. Compare this number with the estimated equivalent of the human brain, which is about 1016 bits per second, or a trillion, trillion times smaller.” [Source].
There is a possibility that silicon computers will start facing constraints in the next few years.
2 Molecular computers
The next stage is molecular computers.
3 Quantum computers will breakthrough to an unbelievable level
This involves manipulating bits at the atomic level. However, given quantum physics, even a single particle of sand can be a million trillion times more powerfully than the human brain. [Hugo de Garis, , at the 4-5 minutes mark].
Quantum Computers Animated:
“Stanford University announced that scientists there had managed to encode the letters “S” and “U” within the interference patterns of quantum electron waves. In other words, they were able to encode digital information within particles smaller than atoms.” [Source]
4 Nanocomputers
Nanotechnology is molecular scale engineering. It is the continuing advance of silicon and quantum computing that will lead to nano-computers, that are so small they operate at the molecular level.
“Henri Markram’s work in Switzerland, every neural connection is known in a single cortical column of a rat brain’s cortex. (A rat has about a thousand such columns, each consisting of about 10,000 highly interconnected neurons, and the human brain contains about a million.)” [Source]
2 Software limits
1 Artificial intelligence
Yes, there seems to be no possibility for the creation of a computer as smart and creative as a human (and with consciousness).
While computers will definitely become ten billion times smarter than us within 30-50 years, it remains a moot question when they'll start building smarter computers on their own.
I suspect they'll always need human 'guidance' till we finally understand the underlying qualities of the human brain/ consciousness. But this stage should not be ruled. If it does occur, then humans will be quickly over-shadowed by machines. But I don’t wish to go there – for this is a book about robotic economics not about science fiction.
|Computational power does not necessarily equate to computational intelligence. A computer might be able to calculate 1+2 in a |
|nano second but that doesn't necessarily means it understands what 1+2 means or why it is doing it. Anyone who has actually |
|worked with any form of AI will tell you that most intelligence we design right now works through brute force (mostly). |
|Creativity is a bit more complex, it is taking seemingly unrelated concepts two create new concepts, this is more complicated.|
|We are trying to get around this by modelling the human brain in virtual space. |
|A lot of manufacturing jobs could be taken over, but service jobs will be maintained as humans for the foreseeable future. |
|[Comment: Source] |
It would appear that robotics will need to break the creativity barrier before humans become really useless as workers.
To watch: Artificial intelligence singularity (by Kurzweil)
The Singularity Is Near
Michio Kaku on The Singularity
SINGULARITY [2013] Rise of the Machines with Ray Kurzweil and Stephen Hawking
Paul Root Wolpe disagrees (video). Society is too complex. Things are always much more complex than what we think they are. First the genomes, then the proteins, now epigenetics, and so on. We still aren’t getting the benefits of the genome project since things like DNA/the brain are far more complex than we thought they were. This can be called the ‘complexity fallout’. Singularity significantly simplifies the complexity of biology.
|Diamandis predicts that artificial intelligence (AI) similar to iPhone’s Siri will be responsible for taking jobs from humans |
|in the near future. |
|“AI can today do most of the things that humans can do, they can think better than humans, they can translate and understand |
|85 languages and they can read and write so it is predicted that they will take 50 per cent of human’s jobs in 10 years,” said|
|Diamandis. [Source] |
2 Object recognition
This is the stage when computers can recognise generic objects (e.g. a cup). Taken further, this inclues facial recognition.
3 Machine learning
In this computers learn on their own
4 Rat Brain simulation
“Today, thanks to Henri Markram’s work in Switzerland, every neural connection is known in a single cortical column of a rat brain’s cortex. (A rat has about a thousand such columns, each consisting of about 10,000 highly interconnected neurons, and the human brain contains about a million.)
This detailed connectivity knowledge has been put into supercomputers, so that computer-savvy neuroscientists can perform experiments in a computer, that is, conduct “e-neuroscience.” So a supercomputer will be able to perform the same functions as a rat’s cortical column, but a million times faster–at electronic speeds compared to the rat’s chemical speeds. Following Moore’s Law, the whole rat brain will be thus simulated within a decade, and the human brain a decade or two later.” [Source]
5 Human Brain Project
“The Human Brain Project (HBP) is a research project which aims to simulate the human brain with supercomputers to better understand how it functions. The end hopes of the HBP include being able to mimic the human brain using computers and being able to better diagnose different brain problems.” [Source]
6 Quantum computer programming
Programming quantum computers are particularly hard to program:
5 Three key scenarios
|Singularity discussions seem to be splitting up into three major schools of thought: Accelerating Change, the Event Horizon, |
|and the Intelligence Explosion. |
|Accelerating Change: |
|Core claim: Our intuitions about change are linear; we expect roughly as much change as has occurred in the past over our own |
|lifetimes. But technological change feeds on itself, and therefore accelerates. Change today is faster than it was 500 years |
|ago, which in turn is faster than it was 5000 years ago. Our recent past is not a reliable guide to how much change we should |
|expect in the future. |
|Strong claim: Technological change follows smooth curves, typically exponential. Therefore we can predict with fair precision |
|when new technologies will arrive, and when they will cross key thresholds, like the creation of Artificial Intelligence. |
|Advocates: Ray Kurzweil, Alvin Toffler(?), John Smart |
|Event Horizon: |
|Core claim: For the last hundred thousand years, humans have been the smartest intelligences on the planet. All our social and|
|technological progress was produced by human brains. Shortly, technology will advance to the point of improving on human |
|intelligence (brain-computer interfaces, Artificial Intelligence). This will create a future that is weirder by far than most |
|science fiction, a difference-in-kind that goes beyond amazing shiny gadgets. |
|Strong claim: To know what a superhuman intelligence would do, you would have to be at least that smart yourself. To know |
|where Deep Blue would play in a chess game, you must play at Deep Blue’s level. Thus the future after the creation of |
|smarter-than-human intelligence is absolutely unpredictable. |
|Advocates: Vernor Vinge |
|Intelligence Explosion: |
|Core claim: Intelligence has always been the source of technology. If technology can significantly improve on human |
|intelligence – create minds smarter than the smartest existing humans – then this closes the loop and creates a positive |
|feedback cycle. What would humans with brain-computer interfaces do with their augmented intelligence? One good bet is that |
|they’d design the next generation of brain-computer interfaces. Intelligence enhancement is a classic tipping point; the |
|smarter you get, the more intelligence you can apply to making yourself even smarter. |
|Strong claim: This positive feedback cycle goes FOOM, like a chain of nuclear fissions gone critical – each intelligence |
|improvement triggering an average of>1.000 further improvements of similar magnitude – though not necessarily on a smooth |
|exponential pathway. Technological progress drops into the characteristic timescale of transistors (or super-transistors) |
|rather than human neurons. The ascent rapidly surges upward and creates superintelligence(minds orders of magnitude more |
|powerful than human) before it hits physical limits. |
|Advocates: I. J. Good, Eliezer Yudkowsky |
1 I.J. Good’s Intelligence explosion concept
This is also know as 'hard takeoff' or 'AI-go-FOOM'.
|I. J. Good’s thesis of the “intelligence explosion” states that a sufficiently advanced machine intelligence could build a |
|smarter version of itself, which could in turn build an even smarter version, and that this process could continue to the |
|point of vastly exceeding human intelligence. [Source: ] |
“I. J. Good was the one who suggested the notion of an “intelligence explosion” due to the positive feedback of a smart mind making itself even smarter. Numerous other AI researchers believe something similar” [Source]
This is opposed by a view (“General Intelligence Theorem” à la Greg Egan) which says that nothing qualitatively smarter than a human can exist.” [Source].
6 Long term structural change in Australia
[pic]
Source
The long term effects of the industrial revolution on Australia. I believe (this idea has to be tested) that in the Robotic Age employment in manufacturing will collapse to around 2 per cent, in agriculture to around 0.2 per cent, and mining to 0.2 per cent. Services is where employment will need to come from.
The mining sector in Australia is a classic example of how output is increasing with fewer employees. This trend is now significantly speeding up.
[pic]
Which services are growing, which are falling in Australia (long term trends):
[pic]
Source
So, what will happen in the Robotic Age? I believe (this is to be tested and further considered) that Personal Services will likely skyrocket (personal trainers, house keepers, gardeners, personal life coaches, yoga teachers, etc.); Construction and distribution and utilities services will shrink dramatically as robots take over much of the work, Social services will shrink as education/health becomes robotised.
7 Industrial machines supplemented muscle. Robots supplement our senses and brains
New terms are being coined to reflect our speculations about the new age that is dawning upon us as we speak.
• “lights out” indicates that robotic factories can work without lights;
• “digital divide” refers to the gap between those who have digital mastery and those who don’t;
• “end of work” represents a view that there will be no more work left after robots ‘take over’ all the work in this world.
Whether we like it or not, we are now in a new epoch. Adam Smith would find many similarities to his age but there are key differences he would take some time to understand.
Computers/robots are now not just getting cheaper, they are getting more capable. That capability is the key to the robotic age. Productivity is increasing dramatically even as jobs are falling rapidly.
Much of this is a continuation of the same trend that started in 1750. But there is something new about this.
The key is that machines now sense the environment and respond to it dynamically. They are not static any longer.
8 The ‘coming of age’ of robots
While most humanoid robots are not very useful yet, many other robots are commercially viable. Computation has become cheaper (Moore’s law). Camera prices have fallen dramatically (initially $50,000) – due to consumer revolution. Computer vision has increased. Software has improved. The usability threshold has been crossed. Real robots have real users.
Early forms of robots have been with us since around 1960, but perhaps 2000 roughly marks the onset of the Early Robotic Age.
Please spend 15 minutes on this talk by Andrew McAfee, co-author of Race Against the Machine. I am optimistic along with him about the future but there are very significant issues that need to be articulated and understood, and many policy concepts clarified.
1 What are robots?
A machine was brawn and muscle. It multiplied the power of our muscles. It could not, however, “see” or otherwise identify objects. Robots can “see” and distinguish between objects in a non-mechanical way. They rely on some form of digital ‘perception’ or intelligence.
• The sorting machine in a post office is therefore a (primitive) robot.
• The ATM machine is similarly a robot.
• The automatic check-in machine (for ticket/luggage) at the airport is a robot.
• The self-checkout at the supermarket is a robot.
• A smelter at a steel plant is not a robot.
|The reporter, Steve Kroft, discussed a new definition of robots and robotics in sharp disagreement from the definitions posed |
|by the International Federation of Robots: |
|Steve Kroft said, "The broad universal definition is a machine that can perform the job of a human. The machine can be mobile |
|or stationary, hardware or software." |
|This is different than the robotic industry's most recent tentative definition of service robots which, in short, says the |
|following: |
|A robot is an actuated mechanism programmable in two or more axes with a degree of autonomy, moving within its environment, to|
|perform intended tasks. Autonomy in this context means the ability to perform intended tasks based on current state and |
|sensing, without human intervention. |
|A robot has to have at least two degrees of freedom plus autonomy. |
|ROBOT |
|A fully autonous car (2 degrees of freedom (DoF); steering and transmission) would qualify for a mobile robot as would 3D |
|printers. |
|NOT ROBOT |
|But a washing machine (1 axis; 1 DoF), airline or other kiosk, or adaptive cruise control (all which could be considered as 1 |
|DoF) would not fall under the category of robots. [Source] |
2 Maturation of many related technolgies
Although the Robotic Age primarily refers to robots, it is shorthand for the IT-based revolution that is now coming of age in a large number of related disciplines. A LARGE number of technologies are now SIMULTANEOUSLY MATURING. This is a very exciting time in human history.
[pic]
1 Genome mapping
For those not yet convinced that MASSIVE TECHNOLOGICAL CHANGE is underway (and yes, robotics is now going to have REAL effects on the economy), this is an example of the speed of progress. Human genome costs have fallen from $100 million per genome to less than $7K per genome. (). In just 11 years.
[pic]
2 3-D printing
3-D printing is a key part of the robotics age, since it allows production of entire goods without any direct human intervention.
3 Biological computers
These are now able to store data and also perform calculations:
Storage: “the research team stored five files — totaling about 750 kilobytes of data — as DNA: all 154 of Shakespeare’s sonnets (a text file), Watson and Crick’s classic 1953 paper describing the structure of DNA (a PDF), a color photograph (a JPEG) and a 26-second excerpt from Martin Luther King’s 1963 “I Have a Dream” speech (an MP3). [Source]
4 Neural networks
5 Recreation of detailed map of the brain
First the human genome was created. Now the full map and reproduction of the brain is underway.
6 Fusion
Proven prototypes of fusion (i.e. endless energy) are now not more than 20 years away.
The technology is now 99 per cent there. Final tweaks and a prototype are left. Expect fusion in 10 years max.
[pic]
7 Nanotechnology/nanorobots
Nanorobots are ALREADY there - but need a little bit more shrinkage. (Like we used bullocks to carry our stuff, we now use bacteria to propel these robots).
This is a most fascinating video:
9 What can robots do?
Robots can now do most things that humans can, even if not always very well. But some things they can do many times better than humans can.
Examples are outlined below. Do see some of the linked videos.
1 Physical
1 2-legged robots can walk in the midst of people and on rough surfaces
ASIMO 2011:
Also, Atlas the Pentagon robot.
2 4-legged robots can run faster than humans
This robot (Cheetah) runs at 29 miles per hour.
3 4-legged robots can carry loads and walk faster uphill than humans
Robotic donkey (DARPA - AlphaDog Legged Squad Support System (LS3))
Donkey that throws objects:
[BigDog handles heavy objects. The goal is to use the strength of the legs and torso to help power motions of the arm. This sort of dynamic, whole-body approach to manipulation is used routinely by human athletes and will enhance the performance of advanced robots. Boston Dynamics is developing the control and actuation techniques needed for dynamic manipulation. The cinderblock weighs about 35 lbs and the best throw is a bit more than 17 ft. The research is funded by the Army Research Laboratory's RCTA program.]
4 Extreme athleticism in running/flying
Seeing is believing.
Raffaello D'Andrea: The astounding athletic power of quadcopters.
5 Can jump 30 feet
6 Can fight and ‘kill’ other robots
7 Can dance /play games
Robots now dance, and play soccer and ping pong. China is advancing rapidly in robotics.
E.g. table tennis:
Dancing robots:
Fencing:
2 Dexterity
1 Can bounce balls and catch objects with fingers
2 Have extremely fine ‘hand-eye’ coordination
Universal robots are now able to perform extremely fine ‘hand-eye’ coordination tasks with very little training.
3 Can drive trains
Robotics and IT have replaced thousands of train drivers across the world. A full list of driverless trains:
4 Can drive cars and trucks and fly planes
Google has an unmanned/driverless car/s and F35 is the last manned fighter jet.
Hal Varian says: “Rich people have chauffeurs, but I think that in 10 years we will all have chauffeurs – robotic chauffeurs – because the technology has advanced to the point where it is absolutely real-world stuff.” [Source]
"The cab came floating down out of the sky at the intersection and maneuvered itself to rest at the curb next to them with a finicky precision. There was, of course, nobody in it; like everything else in the world requiring an I.Q. of less than 150, it was computer-controlled." [James Blish’s A Life for the Stars (1962)].[Source] Well, this time is now arriving VERY FAST. What's to be done with those who can't design things?
5 Can fly helicopeter upside down
(that was 2011).
3 Verbal
1 Can talk
A talking robot was launched into space in August 2013. Watch the short movie. Also see the BBC report:
2 Can sing
Singing robot:
4 Creative
1 Can sketch and make oil paintings (eDavid)
[pic]
2 Can make music (bands)
Singing robot:
Robot music band:
5 Cognitive computing
“researchers there are already testing new generations of Watson in medicine, where the technology could help physicians diagnose diseases like cancer, evaluate patients, and prescribe treatments.
“IBM likes to call it cognitive computing. Essentially, Watson uses artificial-¬intelligence techniques, advanced natural-language processing and analytics, and massive amounts of data drawn from sources specific to a given application (in the case of health care, that means medical journals, textbooks, and information collected from the physicians or hospitals using the system). Thanks to these innovative techniques and huge amounts of computing power, it can quickly come up with “advice”—for example, the most recent and relevant information to guide a doctor’s diagnosis and treatment decisions.” [Source]
10 Major signs that the robotic age is upon us
1 Significant acceleration in capability
1 Already we have a computer equal to human brain in processing power
In 2012, the first computer that crossed the human brain's processing capacity (16 petaflops) was built.
2 Predictions
I agree broadly with Kurzweil’s hardware predictions:
• by 2019 even a $1,000 computer will match the processing power of the human brain.[1]
• within 20 years the fastest computer will be thousands of times "smarter" than humans
• by 2055 a $1,000 computer will match the processing power of ALL human brains on Earth.
On the software side, AI is almost endless in its progress, according to Kurzweil.
Bill Gates doesn’t agree with Kurzweil:
My tentative view is that at some point computers will design most future improvements as they become capable of self-learning.
Kurzweil then combines these advances with those of biotechnology and nanotechnology to suggest immortality:
3 Significant acceleration (second half of the chessboard)
The second half of the chessboard is an excellent analogy for the situation currently being experienced in the world of robotics. Robotics has now become palpable. We are aware of it. But this is not even the beginning.
Expect dramatic change every two years.
[pic]
4 Significant acceleration in AI
The key to the Robotic Age is the significant ramping up of artificial intelligence (software).
2 The commercial case for robots
Robots are not just more powerful, they are really cheap.
1 Dramatically falling robot prices
As a result in reduction in key technologies (e.g. cameras/ software to analyse data), new materials, robot prices have dropped massively over the past decade.
2 The rise of the multi-purpose robot
This is a robot that doesn’t need programming and can be locally trained, like one trains a worker.
A summary:
[pic]
3 Many other advantages of robots
“a machine that never goes on strike, never demands a wage hike, doesn't ask for a bigger dormitory and is not too picky about the food in the canteen.” [Source]
|TimS: "My company designs and builds custom automated manufacturing equipment, with many platforms utilizing various forms of |
|'robots.' All this automation does accomplish many things, with the greatest gains being repeatable and reproducible process |
|capability, higher quality, lower scrap rates, and thus lower costs. In the overall scheme, in factories with high labor |
|costs, automation is the name of the game for high volume production. In factories with low labor costs, semi-automatic or |
|totally manual labor is the economic solution. Product cost is tied to overhead, materials, labor and equipment costs. The |
|bottom line trend is the manufacturing factory is becoming more and more automated and higher-tech. If people can manoeuvre |
|smart phones and the like, then I think the brain power is out there for the high-tech factory worker. Mankind is evolving. |
|The last 100 years shows the exponential rate of our technological growth." [Source] |
3 Evidence of commercial deployment
1 Size of robotics industry
About $25 billion turnover in 2011 [Source]
2 Number of WorkCover claims reducing
Dangerous industries are among the first to take up robotics. This is having an effect on physical workplace injuries which are now rapidly reducing.
3 Number of robots increasing
[pic]
[Source]
[pic]
The IFR has predicted that more than 1.5 million industrial robots will be in operation worldwide in 2015. [Source]
See the diagram below.
[pic]
Source:
This diagram is, of course, too simplistic, by comparing apples and oranges. This doesn’t tell us which type of robot is replacing humans. And given some robots are effectively more efficient at specific tasks than humans, it doesn’t tell us whether the replacement robot is equivalent to more than one human. In the end we will need data on “human equivalents” if we are to compare the two.
4 Manufacturing is shifting back to the West
Costs of manufacturing in Japan/China/Vietnam are increasing rapidly. There are significant issues with manufacturing in non-Western nations. [The following from Rodney Brooks
Chairman and CTO, Rethink Robotics here]
• Responsive, short supply chains
• Innovation close to manufacturing
• Protection of intellectual property
• Productivity beats cheap labour
• Avoid higher transportation costs
5 Suddenness of change
“machines could go from performing 25% of jobs to 75% within four years”. [Race Against Machine].
|Imagine a chart resembling a topographic cross section, with the tasks that are “most human” forming a human advantage curve |
|on the higher ground. Here you find chores best done by humans, like gourmet cooking or elite hairdressing. Then there is a |
|“shore” consisting of tasks that humans and machines are equally able to perform and, beyond them an “ocean” of tasks best |
|done by machines. When machines get cheaper or smarter or both, the water level rises, as it were, and the shore moves inland.|
|This sea change has two effects. First, machines will substitute for humans by taking over newly “flooded” tasks. Second, |
|doing machine tasks better complements human tasks, raising the value of doing them well. |
|Imagine that the ocean of machine tasks reached a wide plateau. This would happen if, for instance, machines were almost |
|capable enough to take on a vast array of human jobs. In this situation, a small additional rise in sea level would flood that|
|plateau and push the shoreline so far inland that a huge number of important tasks formerly in the human realm were now |
|achievable with machines. [Source: ] |
11 Who’s driving this rapid change?
|While the European Union, Japan, Korea, and the rest of the world have made significant R&D investments in robotics |
|technology, the U.S. investment, outside unmanned systems for defense purposes, remains practically non-existent. [Source: |
|] |
Why? Apparently Japan has a fear of ageing and also don’t want to allow immigration. Therefore they want to build robots.
Note that industrial robots are made only in Japan, Korea and Europe (not USA) [Source]
China is a huge user of robots, but also has clear plans to move in this area:
|"China’s 12th 5-Year Plan targeted robotics as a growth industry necessary for China’s development. It expects a compound |
|growth rate of 25%, said Wang Weiming, deputy director of the Ministry of Industry and Information Technology. The ministry |
|has set up incentives and 5 geographical areas for Chinese companies to develop (and improve the quality of) their robot |
|products and capabilities. The ambitious plan includes a goal of 30% to be produced with homegrown technologies, Wang said. |
|... In addition to Shanghai, Beijing, Guangzhou and Chengdu, authorities in Liaoning province are constructing a robot |
|industrial complex so that by 2017 they expect $8 billion for robots and other automation equipment." [Source] |
12 Key organisations
1 IFR (International Federation of Robotics)
Download report here.
2 DARPA
3 Pentagon
Atlas
4 Boston Robotics
5 Universal Robots
What humans take 4 days takes this robot just 4 hours.
6 Yamaha
7 iRobot
8 Rethink Robotics
Baxter – a universal robot that can be trained. Requires NO programming. Base price $22,000.
[pic]
Baxter is now at work in Greece. For a mere $22,000 you get a relentless worker. In 5 years’ time, I'd expect Baxter to cost $10,000 or less. "At a Johnson & Johnson factory in Greece, a UR5 is used on a production line where it performs repetitive pick and place tasks as a link between two parts of a production line. The robot takes bottles of cream from one production line, and places them onto the packaging line. Flexibility is the key requirement because there are several different types of creams coming down the line, each positioned differently. he Greek integrator/distributor, InnoPro Technologies, which sold and installed the robot, said that J&J engineers were 100% satisfied and have even given the robot a name." [Source]
Baxter could (in 10-15 years) turn into a home-robot that puts dishes into the dishwasher and back on the shelf, polishes shoes, cleans toilets, and perhaps cooks simple dishes.
9 Key publicly traded robotic companies
Source:
1 Healthcare Applications:
• Intuitive Surgical (ISRG:US) and its da Vinci Robotic Surgical System are being installed at major hospital operating centers worldwide. Intuitive Surgical has more than 870 U.S. and foreign patents as well as more than 990 pending.
• Mako Surgical (MAKO:US) has an interactive robotic arm orthopedic system for knee implants.
• Accuray (ARAY:US) and its CyberKnife Robotic Radiosurgery System is an up-and-coming robotic radiation treatment system.
• Swisslog (SLOG:SW) makes warehouse automation devices as well as hospital logistics and drug management solutions using mobile robots.
• Mazor Robotics (MZOR:IL), an Israeli company, provides state-of-the-art robotic surgical guidance systems.
2 Defense, Security and Space Applications*:
• AeroVironment (AVAV:US) is a provider of unmanned aircraft, systems and services and 85% of their revenue comes from UAS (unmanned aerial systems) sales. They regularly get DoD orders for their Raven and Wasp small unmanned aircraft systems and just got three orders totaling $28.4 million for production of their Puma drone.
• iRobot (IRBT:US), a 100% pure play robotics company, just had a 33% drop in their stock price because of reduced government contracts. They have recently restructured to add healthcare to their lineup of products, consumer products are doing fine, and the company is fishing for additional consumer robotic products.
• QinetiQ (QQ/:LN) is iRobot's direct competitor in the defense robotics marketplace despite their being a British company and not a pure play stock.
* Many of the major providers in Defense, Security and Space do have robotics subsidiaries but are conglomerates where only a very small portion of their revenue is derived from robotics, hence they are not listed here. Examples of this type of company include: Northrup Grumman, Rockwell Automation, General Dynamics, Boeing, Teledyne, Textron and Canadian MacDonald Dettwiler.
3 Industrial and Co-robot Applications**:
• Adept Technology (ADEP:US) is one of the very few industrial robot manufacturers based in the U.S. Most of it's revenue from robotics comes from manufacturing, food processing, automotive and warehousing applications. With their recent acquisition of Mobile Robotics, and after strengthening and modularizing their mobile acquisition,the company began to enter the service robotics sector.
• Two privately held companies, Universal Robotics, a Danish company and c-Link Systems, from the US, along with two publicly-traded companies KUKA (KU2:GR) and ABB (ABBN:VX), have released lightweight, economical, safe, robotic arms for light industrial and SME work.
• KUKA (KU2:GR) has been getting a lot of press for their increasing involvement in China, too. All these companies (KUKA, ABB, FANUC, Adept, Yaskawa Electric (Motoman)) hope to do well in China as China automates its automotive and other industries. But KUKA and the other non-Chinese companies may have problems further down the road when China's in-country technology machine takes over.
• ABB (ABBN:VX) has for many years been active in China and, until Foxconn announced that they would be manufacturing their own robots, ABB was rumored to be the leading contender to get the job. ABB stock comes with the caveat that robotics represents only 21% of their corporate revenue.
• Yaskawa Electric (Motoman) (6506:JP) is similar to ABB in that the company is well respected as a robot manufacturer yet robotics represents only 30% of revenues. They recently announced building plans for a robot factory in China.
• FANUC (6954:JP) recently completed construction of an additional factory in Japan to handle sales to China.
4 Ancillary businesses to the robotics industry:
• Trimble (NASDAQ:TRMB) provides advanced positioning product solutions and component parts as does Hemisphere GPS (TSE:HEM Toronto Stock Exchange) in Canada, particularly for the ag industry. Trimble's recent acquisition of Gatewing, a Belgium provider of a 4-1/2 pound unmanned aircraft and software specialized for surveying and mapping, provides a complementary subsidiary for Trimble. "We’re looking at the acquisition of Gatewing as the start of a center of excellence that will broaden into a product line, rather than a single product.”
• FARO Technologies (NASDAQ:FARO) provides 3D measurement and inspection arms and scanners.
• Cognex (NASDAQ:CGNX) is a provider of machine vision products primarily used in robotic applications.
• Allied Motion Technologies (AMOT:US) makes the servos that are incorporated in the da Vinci surgical and other robotic systems.
13 Opinions
1 Mostly positive (an overall good, will happen slowly, society will adjust)
1 Ray Kurzweil
|Source: |
|Ray Kurzweil believes strongly in the long-run ability of the economy to overcome threats of technological unemployment, |
|because it's done such a good job overcoming these threats in the past. His rebuttal to critics who believe that robots are |
|destined to take all our jobs echoes the comments Michael Chorost made about enlarging the scope of our imaginations: |
|This [technological unemployment] controversy goes back to the advent of automation in the textile industry in England at the |
|beginning of the nineteenth century which marked the beginning of the industrial revolution. Weavers saw that one person with |
|the new machines could replace dozens of weavers. New types of machines were introduced quickly and the weavers predicted that|
|employment would soon be enjoyed only by the elite. They could see clearly the jobs going away but not the new types of |
|employment that could not be described because they had not been invented yet. They formed a society to combat this called the|
|Luddites. The reality turned out very different from their fears. New industries were formed and new jobs created that never |
|existed before. The common man and woman could now have more than one shirt or blouse. The reality of jobs lost could be seen |
|very clearly whereas the advent of new jobs that had not yet been invented were harder to understand. |
|If I were a prescient futurist giving a speech in 1900, I would say that a third of you now work on farms and another third in|
|factories, but in a hundred years -- that is, by the year 2000 -- that will go down to 3% and 3%. That is indeed what |
|happened; today it is 2% and 2%. Everyone in 1900 would exclaim, "My god, we'll all be out of work!" If I then said not to |
|worry, you'll get jobs as website designers, database editors, or chip engineers, no one would know what I was talking about. |
|In the U.S. today, 65% of workers are knowledge workers of some kind and almost none of these jobs existed fifty years ago. |
|So again today we can envision types of work that will go away through continued automation and it is difficult to envision |
|the jobs that have not yet been invented. |
2 William Lazonick
Lazonick is director of the University of Massachusetts Center for Industrial Competitiveness. See article: Robots Don't Destroy Jobs; Rapacious Corporate Executives Do.
3 Hal Varian
"Robotics is where computers were 15 years ago. All the big manufacturing plants have robots, but they’re really expensive and have to be cared for by specialists. But they are getting cheaper and cheaper.’’" Their rate of improvement will boggle the mind. That's a firm prediction.
4 Dr. Michio Kaku
Are We Ready For the Coming 'Age of Abundance?
Video:
5 Frank Levy and Richard Murnane
Third Way report, “Dancing with Robots”.
The New Division of Labor: How Computers Are Creating the Next Job Market
Frank Levy & Richard J. Murnane
6 Robin Hanson
Hanson, Robin. Economic Growth Given Machine Intelligence.
Hanson, Robin. Economics of The Singularity
Singularity economics
7 W. Brian Arthur
The opportunities offered by the wealth-generating capacity of machines, bits and bytes, algorisms, and artificial intelligence will fundamentally shift our societal concerns from “how best to generate growth” to “how best to distribute wealth.” “The productive part of the economy will be in great shape, but the distribution of it will be the main problem,” says W. Brian Arthur, visiting scholar at the Palo Alto Research Center’s Intelligent Systems Laboratory. “The big problem from 2010 on is distributing all the wealth, getting it into human hands.” [Source]
8 Mark Thoma
“There will be jobs we can’t imagine right now,” says Mark Thoma, an economist at the University of Oregon. [Source]
9 Eliezer Yudkowsky
Intelligence Explosion Microeconomics
The Robots, AI, and Unemployment Anti-FAQ
10 Laurence Katz
“Lawrence Katz, a Harvard economist, says that no historical pattern shows these shifts leading to a net decrease in jobs over an extended period. The question, he says, is whether economic history will serve as a useful guide. Will the job disruptions caused by technology be temporary as the workforce adapts, or will we see a science-fiction scenario in which automated processes and robots with superhuman skills take over a broad swath of human tasks? Though Katz expects the historical pattern to hold, it is “genuinely a question,” he says. “If technology disrupts enough, who knows what will happen?” [Source]
11 Robert Atkinson
Time for a Manufacturing Debate Based on Facts, Not Opinion
12 Nick Bloom
|Nick Bloom, an economics professor at Stanford, has seen a big change of heart about such technological unemployment in his |
|discipline recently. The received wisdom used to be that although new technologies put some workers out of jobs, the extra |
|wealth they generated increased consumption and thus created jobs elsewhere. Now many economists are taking the short- to |
|medium-term risk to jobs far more seriously, and some think the potential scale of change may be huge. Mr Thrun draws a |
|parallel with employment in agriculture, which accounted for almost all jobs in the pre-modern era but has since shrunk to |
|just 2% of the workforce. The advent of robots will have a similar effect, he predicts, but over a much shorter period. Even |
|so, he is sure that human ingenuity will generate new jobs, just as it created vast new industries to counteract the decline |
|in agricultural employment. [Source] |
2 Mostly negative (i.e. this is a big issue for society)
“The cab came floating down out of the sky at the intersection and maneuvered itself to rest at the curb next to them with a finicky precision. There was, of course, nobody in it; like everything else in the world requiring an I.Q. of less than 150, it was computer controlled. The worldwide dominance of such machines, Chris’s father had often said, had been one of the chief contributors to the present and apparently permanent depression: the coming of semi-intelligent machines into business and technology had created a second Industrial Revolution, in which only the most highly creative human beings, and those most gifted at administration, found themselves with any skills to sell which were worth the world’s money to buy. Chris studied the cab with the liveliest interest, for though he had often seen them before from a distance, he had of course never ridden in one. But there was very little to see. The cab was an eggshaped bubble of light metals and plastics, painted with large red-and-white checkers, with a row of windows running all around it. Inside, there were two seats for four people, a speaker grille, and that was all; no controls, and no instruments. There was not even any visible, place for the passenger to deposit his fare.” [James Blish, 1962, A Life for the Stars, Cities In Flight, Volume Two]
1 Andrew McCaffee and Erik Brynjolfsson
This talk by Andrew (already cited earlier) is worth listening:
Erik’s talk here:
|Erik Brynjolfsson and Andrew McAfee, both at MIT, also have high hopes for the long-term effect of robots and similar |
|technologies. But in a recent book, “The Second Machine Age”, they argue that technological dislocation may create great |
|problems for moderately skilled workers in the coming decades. They reckon that innovation has speeded up a lot in the past |
|few years and will continue at this pace, for three reasons: the exponential growth in computing power; the progressive |
|digitisation of things that people work with, from maps to legal texts to spreadsheets; and the opportunities for innovators |
|to combine an ever-growing stock of things, ideas and processes into ever more new products and services. |
| |
|Between them, these trends might continue to “hollow out” labour markets in developed countries and, soon enough, developing |
|ones, as more and more jobs requiring medium levels of skill are automated away. This helps explain, the authors argue, why |
|the benefits of economic growth increasingly accrue to a small group of highly paid people, citing in evidence the lack of |
|growth in America’s median wage and the decline in workforce participation. [Source] |
2 Jeffrey Sachs and Lawrence Kotlikoff
|A paper by Jeffrey Sachs and Lawrence Kotlikoff highlights the worrying possibility that this shift could be |
|self-perpetuating: if automation absorbs jobs previously reserved for young people, who have not yet had time to build up |
|skills, it will stop them from acquiring those skills, and its destructive effects will reverberate down the years. [Source] |
3 Martin Ford
Silicon Valley entrepreneur and computer engineer. He believes that “as technology advances, a larger and larger fraction of the population will essentially become unemployable” [Source]
Book: The Lights in the Tunnel: Automation, Accelerating Technology and the Economy of the Future
Second book: Rise of the Robots: Technology and the Threat of a Jobless Future
Blog:
On Huffingpost
• “The Truth About Unemployment — And Why It May Get Worse“, 19 January 2010
• “A Jobless Recovery… And A Jobless Future?“, 2 February 2010
• “The Coming Structural Unemployment Crisis“, 24 May 2010
• “Unemployment: The Economists Just Don’t Get It“, , 4 August 2010
Could Artificial Intelligence Create an Unemployment Crisis?
4 Kevin Drum
Drum, Kevin. Welcome, Robot Overlords. Please Don't Fire Us? Smart machines probably won't kill us all—but they'll definitely take our jobs, and sooner than you think.
5 Tyler Cowen
Views of Tyler cowmen
|Zero Marginal Product: |
|That's Tyler Cowen's term for a segment of the current long-term unemployed. |
|Their productivity may not be literally zero, but it is lower than the cost of training, employing, and insuring them. That is|
|why labor is hurting but capital is doing fine; dumping these employees is tough for the workers themselves -- and arguably |
|bad for society at large – but it simply doesn't damage profits much. It's a cold, hard reality, and one that we will have to |
|deal with, one way or another. [Source] |
|If robots concentrate wealth in the hands of IP owners, wages for many workers might fall or remain stagnant. That is a |
|problem. |
|Similarly, if robots concentrate wealth in the hands of IP owners, it may be hard to drum up the tax revenue to support a |
|higher dependency ratio. The wealthy may produce a blocking political coalition or capital simply may be harder to tax for |
|mobility, accountancy, and Laffer curve-like reasons. There is then a problem with the dependency ratio. [Source] |
Also:
|10 Percent Unemployment Forever? |
|BY TYLER COWEN, JAYME LEMKE | JANUARY 5, 2011 |
|The U.S. economy finally appears to be picking up steam and headed toward recovery: several economic indicators -- including |
|manufacturing and services output, and sales of cars and consumer goods -- have shown noticeable improvement over the last few|
|months. Scan virtually any financial news website, and you'll see it's now a consensus that a sustained economic recovery has |
|not only arrived -- it's picking up speed. |
|But there's good reason to believe that the labor market won't be keeping pace. Rather than an aberration, high unemployment |
|may be an enduring feature of the United States' economy. |
|We are, sadly, in a very deep pit when it comes to the labor market. The recent private-sector estimate from ADP Employer |
|Services announced the creation of 297,000 new jobs for December, but this is the first instance of a real dent in the jobless|
|rate since the beginning of the recession. The November report from the U.S. Bureau of Labor Statistics pegged the |
|unemployment rate at 9.8 percent, which translates to over 15.1 million unemployed. Over 40 percent of currently unemployed |
|workers have been out of a job for over six months, the highest percentage of long-term unemployment since World War II. The |
|numbers look even worse if we consider the underemployed, which includes potential workers who have given up looking for a job|
|or the 9 percent of the labor force that is made up of part-time workers who would prefer to be working full-time. At least |
|2.5 million people gave up looking for work in the last year alone. |
|Even if the December rate of job creation continues, it will be 2014 before unemployment is down to 5 percent. But last |
|month's good news may not last. At a more conservative estimate of 150,000 jobs added per month, it could be 2024 before |
|employment is back to 2007 levels. Keep in mind that there are 100,000-plus estimated new entrants into the workforce each |
|month. In November, a sum total of 92,000 new jobs were created -- but that didn't lower the unemployment rate. |
|So what happened? Why have American labor markets ended up in such a dire situation? |
|The simple Keynesian explanation for the initial unemployment is that aggregate demand -- the country's combined spending and |
|investment -- has been too low. But it's unlikely that spending is the only problem, as unemployment is too high and too |
|persistent relative to similar episodes of disinflation in recent history. If weak demand was the main problem, profits should|
|be collapsing too, but they are not. Investment and corporate profits have been fine for some time now, and they are broadly |
|within the range of pre-recession estimates. |
|There's a second problem with the Keynesian story, which relies heavily on the notion that real, inflation-adjusted wages are |
|sitting at too high a level. If unemployment causes someone real suffering, why wouldn't he or she be willing to take a lower |
|salary to get a job and ease the pain? But rather than falling, private-industry wages are currently on the rise -- up nearly |
|60 cents per hour since the end of the recession. There are plenty of good theories why it is hard to cut the wages of |
|employed workers -- long-term contracts pose legal challenges, and fragile worker morale threatens to collapse under the |
|stress of wage cuts. But it's harder to explain why unemployed workers can't find new jobs for less pay, especially if output |
|is recovering, profits are high, and corporations are sitting on a lot of cash. |
|Many conservatives in the United States have placed the blame for high unemployment on the shoulders of President Barack |
|Obama, arguing that his administration's liberal agenda has complicated the recovery. But the statistics suggest otherwise. |
|Again, corporate profits and consumer spending are fine. Indeed, it's the sector in which the government has most directly |
|intervened -- health care -- that has maintained the most robust job growth over the past two years, adding 20,000 new jobs in|
|November alone. And don't go blaming job losses on illegal immigrants taking jobs from documented workers: Latino immigrants |
|have left the country in large numbers since the start of the financial crisis. |
|As time passes, it is harder to avoid the notion that a lot of those old jobs simply weren't adding much to the economy. |
|Except for the height of the housing boom -- October 2007 through June 2008 -- real GDP is now higher than it has been in the |
|entirety of U.S. history. The fact that the United States has pre-crisis levels of output with fewer workers raises doubts as |
|to whether those additional workers were producing very much in the first place. If a business owner fires 10 people and a |
|year later output is almost back to normal, it's pretty hard to make the argument that they were doing much in the first |
|place. |
|The story runs as follows. Before the financial crash, there were lots of not-so-useful workers holding not-so-useful jobs. |
|Employers didn't so much bother to figure out who they were. Demand was high and revenue was booming, so rooting out the less |
|productive workers would have involved a lot of time and trouble -- plus it would have involved some morale costs with the |
|more productive workers, who don't like being measured and spied on. So firms simply let the problem lie. |
|Then came the 2008 recession, and it was no longer possible to keep so many people on payroll. A lot of businesses were then |
|forced to face the music: Bosses had to make tough calls about who could be let go and who was worth saving. (Note that |
|unemployment is low for workers with a college degree, only 5 percent compared with 16 percent for less educated workers with |
|no high school degree. This is consistent with the reality that less-productive individuals, who tend to have less education, |
|have been laid off.) |
|In essence, we have seen the rise of a large class of "zero marginal product workers," to coin a term. Their productivity may |
|not be literally zero, but it is lower than the cost of training, employing, and insuring them. That is why labor is hurting |
|but capital is doing fine; dumping these employees is tough for the workers themselves -- and arguably bad for society at |
|large -- but it simply doesn't damage profits much. It's a cold, hard reality, and one that we will have to deal with, one way|
|or another. |
| |
|So how should we interpret the recent trickle of good news? Well, one positive note is that less-productive, laid-off workers |
|are undertaking the needed adjustments. For instance, according to a survey by the Pew Research Center, nearly 70 percent of |
|unemployed workers have already made dramatic changes in their career or job-field choice, or are considering doing so. There |
|also have been migrations out of expensive urban areas and into smaller and less expensive ones, such as Austin, Salt Lake |
|City, and northern Virginia, with relatively high-performing industries and more fluid labor markets. |
|In other words, the U.S. economy is going through some major structural shifts. It's not a question of getting back to where |
|we were, but rather that the economy must solve a new problem of re-employing a lot of people who were not, in reality, |
|producing very much in the first place. That's a steeper challenge than we had realized early in the stages of this recession |
|-- and so far policymakers have failed at meeting it. |
|Analysts still disagree on how rapidly the U.S. economy will recover. But they're missing the point. The era of low |
|unemployment may be in our rearview mirror for a long time to come. [Source] |
|End of the average is nigh as inequality divides society |
|Young people are advised to avoid excessive specialisation and to 'do what you enjoy, learn general skills, learn how to learn|
|-and learn how to retrain yourself'. Source: Getty Images |
|DO you want your child to have a job in 2033? If so, according to a book that is gripping policymakers in Washington, they had|
|better start deferring to computers. Society is about to be divided into big earners and big losers and those who rage against|
|the machine are destined for the scrap heap. |
|Tyler Cowen, an economics professor at George Mason University in Virginia, delivers the bad news cheerfully. Inequality is on|
|the rise, he argues, and the middle class will soon be seen as a quaint feature of a bygone era. |
|Over the next two decades, he predicts, society will become a "hypermeritocracy" in which 15 per cent will be richly rewarded |
|for their adeptness in harnessing technology and the remaining 85 per cent will be consigned to a fragile existence in which |
|wages freeze or fall and few get a second chance at success. |
|His book, Average is Over, concludes that we are about to enter "the age of genius machines, and it will be the people who |
|work with them that will rise". |
|For the rest, life will be decidedly tough and although the fracturing of society is "not inevitable in a metaphysical sense",|
|he says, he has little optimism that governments will do the things necessary to make the situation better. |
|An engaging and eclectic thinker, Cowen, 51, was chess champion of New Jersey at 15, has written a guide to ethnic dining and |
|is a prolific blogger. The Los Angeles Times has described him as "a man who can talk about Haitian voodoo flags, Iranian |
|cinema, Hong Kong cuisine, abstract expressionism, Zairean music and Mexican folk art seemingly with equal facility". |
|Last year, he was invited to Downing Street to deliver a seminar on industrial policy and warned against Britain embracing the|
|politics of envy. |
|Cowen emphasises the importance of humility in accepting that computers usually know best and has reflected this in his own |
|life. He met his wife 10 years ago via , a medium that forced them "out of our usual intuitions and to our mutual |
|benefit". |
|He is enthused by the advances in chess brought by computers and accepts that he might not have succeeded as a young player |
|using software because "I'm not sure how humble I was back then". |
|The key, he says, is to realise that, as in "freestyle chess", in which players can consult computer programs, "the human and |
|computer together are stronger than just the computer, and certainly stronger than just the human". |
|Being the best at chess -or anything in life -is no longer good enough. "The humans who are best at freestyle chess are not |
|the grandmasters but people who are smart and know something about chess but also know when to defer to the computer and when |
|your wisdom actually counts for something." |
|Computer algorithms, he argues, are becoming better at knowing what we want than we do -and successful people will just go |
|with this. |
|Reading Amazon or Yelp reviews leads to better choices -as does walking away from a business deal because a software program |
|tells you it's too risky, even if your gut is telling you to hang in there. |
|The downside is that employers will also use computers with "oppressive precision" to measure output, weed out slackers and |
|spot those who have not always been steady and conscientious. Making a fresh start will become next to impossible. |
|How do we help our children to succeed in this brave, somewhat scary new world -to be part of the 15 per cent? |
|Cowen says the future is too unpredictable to produce lists of jobs to gravitate towards or to avoid. But he does advise |
|avoiding excessive specialisation: "Do what you enjoy, learn general skills, learn how to learn -and learn how to retrain |
|yourself." |
|WHO ARE THE WINNERS? |
|WOMEN: Cowen argues that there will be a premium on service jobs that "make people feel better" and on reliability. "A lot of |
|these new jobs will be service sector jobs, so some of that will be looking after old people, some of that will be looking |
|after young people, nannies, some of it greeting customers who show up." |
|Looking after the rich will also be lucrative. |
|He adds: "For service sector jobs, a lot of women have advantages over men. How many people want to hire a male nanny? Rightly|
|or wrongly, a lot of people find women more reliable." |
|MARKETERS: Not those who did a business course on marketing, but those who know how to market themselves. "In any society with|
|higher inequality, marketing matters much more," Cowen says. |
|The wealthy have increasing demands on their time and are bombarded with information from all sides. |
|So how do they decide who to employ? "People who have the ability to somehow be persuasive or catch notice or be rhetorically |
|effective or have a good trademark or personal brand -the returns there are skyrocketing." |
|COACHES: There are now computer programs that can mark essays. "I find it quite remarkable," Cowen says. "They seem to do it |
|pretty well." But this does not mean teachers will be out of a job. The ones who can be inspirational life coaches will do |
|especially well. "For a good coach, a good tutor or a good role model, the returns will be very high." In Hong Kong and South |
|Korea, some tutors make millions of dollars a year. "Those tutors are not the smartest people, they're the best motivators ...|
|the theatrical side of it is becoming more important." |
|GENERALISTS: Cowen says those who are computer whizzes will obviously do well. But most of us are not like that. |
|"If you do the humanities in a really smart way, you can do really well. That's counter-intuitive but ... managing people, |
|persuading, will be job skills with very high returns." Mark Zuckerberg, the Facebook co-founder, studied psychology at |
|Harvard (though he did not graduate). |
|A combination of technical knowledge and the ability to solve real-world problems will be at a premium. Those who can |
|prioritise and sort information effectively will be sought out by those in the 15 per cent who do not have the time to do it |
|themselves. "People will want to go to generalists who will be filters in different ways," Cowen predicts. |
|Smartphones already do everything for us, bar making the tea. Siri does not always know the right answer and your GPS is far |
|from infallible, but these tools are improving all the time. Humans who believe they know best are wrong and will be punished |
|in the workplace for their arrogance. |
|Cowen says those who listen to computers will win the glittering prizes, even if they find their pride a little battered at |
|first. The possibilities for computers telling us things about ourselves that we don't know are endless. |
|In Average is Over, Cowen writes: "During a date, a woman might consult a pocket device in the ladies room that tells her how |
|much she really likes the guy. The machine could register her pulse, breathing, tone of voice, the level of detail in her |
|narrative, or whichever biological features prove to have predictive power." |
|THE CONSCIENTIOUS: Those who put in the work stand to inherit the earth. Cowen believes that within the next five years the |
|world's best education, or something close to it, will be available online at no cost. Just because something is there and is |
|free, however, does not mean everyone will take advantage of it. Only the self-motivated and conscientious will take |
|advantage. Already, conscientious students from India are beating American slackers. |
|The ability to monitor performance and track record, and for employers to have easy access to those records, means the steady |
|worker who turns up on time, never has a gap between jobs and does not take sick days will be prized. |
|IMMIGRANTS: Despite the big divide between the 15 per cent and the 85 per cent, Cowen foresees a high degree of social |
|mobility. "People are rising from the middle, and indeed the bottom, all the time, often immigrants ... it's completely wrong |
|to think the current elite will capture all of those gains." |
|As highly motivated and conscientious workers, immigrants are always likely to do well. "Immigrants are one group where when |
|they see a bigger divide, they try harder to make that leap," Cowen says. Immigrants took a risk and perhaps gave up a |
|comfortable and safe lifestyle back home to strive for more. |
|LOSERS |
|TRUCK drivers will soon be out of a job as driverless vehicles are perfected. Journalists who write basic match reports or |
|summaries of the stockmarket may soon find that computers can do as good a job and make fewer mistakes. Filing clerks are |
|already no more. But the biggest losers Cowen identifies are young men. |
|"They might be smart, energetic, maybe even very creative, but they're often not that disciplined, no that conscientious, and|
|these new institutions will be measuring their value every step along the way." |
|Cowen says psychology and experience tell us that "women are on average more conscientious than men ... more likely to follow |
|instructions and orders with exactness and without resentment". |
|While some men are extremely dedicated to work, there is a big downside to male employees. Men, in greater numbers, he writes,|
|"will be more irresponsible, more likely to show up drunk, more likely to end up in prison, and more likely to become |
|irreparably unemployed". |
|He warns that "if you're a young male hothead who just can't follow orders, and you have your own ideas about how everything |
|should be done", then you should forget about ever making it into that 15per cent. |
6 PBS
Jobs are not just leaving China or USA, they are leaving the PLANET. No more jobs to produce things like shoes. ONLY designers of products are needed, given universal robots and 3d printers.
7 Paul Krugman
1. “Rise of the Robots“, 8 December 2012
2. “Technology or Monopoly Power?“, 9 December 2012
3. “Robots and Robber Barons“, 9 December 2012
4. “Human Versus Physical Capital“, 11 December 2012
5. “Policy Implications of Capital-Biased Technology: Opening Remarks“, 28 December 2012
Krugman and Kaminska argue that there's a strong chance that redistribution will get significantly more important in the near future. That's because, they fear, all our jobs will be taken by robots. [Source]
|Krugman writes: |
|I’ve noted before that the nature of rising inequality in America changed around 2000. Until then, it was all about worker |
|versus worker; the distribution of income between labor and capital — between wages and profits, if you like — had been stable|
|for decades. Since then, however, labor’s share of the pie has fallen sharply. As it turns out, this is not a uniquely |
|American phenomenon. A new report from the International Labor Organization points out that the same thing has been happening |
|in many other countries, which is what you’d expect to see if global technological trends were turning against workers. |
|[Source] |
8 Izabella Kaminska
Krugman and Kaminska argue that there's a strong chance that redistribution will get significantly more important in the near future. That's because, they fear, all our jobs will be taken by robots. . [Source]
|And Kaminska adds: |
|The new inequality we are seeing has little to do with how well educated you are. It’s hard to penetrate beyond the barrier on|
|education alone. The new inequality is about capital owners and non-capital owners. |
|And increasingly, it’s about technology capital owners. Those who own the robots and the tech are becoming the new landlord |
|rentier types. [Source] |
9 Alex Hern
|Two weeks ago, I wrote about the idea of a citizen's income: the state replacing the vast majority of the benefit system with |
|one cash payment made to everyone, regardless of employment or income. |
|The advantages of such a change are legion. At a stroke, the thorny issues of incentives are done away with, since work always|
|pays; the deadweight loss associated with means testing disappears (albeit replaced with the deadweight loss of giving money |
|to people who don't need it); those most likely to fall through the cracks of a regimented welfare state find the barrier to |
|re-entry done away with; and it allows for a recognition of the value of certain types of non-market labour, like caring or |
|raising children. |
|The New York Times' Paul Krugman and the Financial Times' Izabella Kaminska now wade into the fray, proposing another |
|advantage of the policy: its redistributive effect. [Source] |
3 Confused
1 Federico Pistono
Rarely has anyone been more confused that this young man. He is a totally confused socialist. He has no clue about how economies work and therefore doesn't understand that robotics will take away jobs but also allow more creative jobs to become more economically viable. Sadly, these geeks who are going to become super-wealthy and therefore influential in world-policy, don't understand economics.
2 Peter Diamandis
A great thinker, visionary and master of technology, and extremely positive about the future. However, he is totally confused about economics and imagines a socialist future (see this extract here: ).
|Responding to Mr. Reich, he said it’s quite possible that people won’t need jobs the way they do now. As the price of |
|technology falls, so will the cost of living, he said—enabling the world to meet the basic needs of all people within 30 |
|years. He said that he is a libertarian and a capitalist at heart, but that the world seems to be headed toward socialism. |
|[Source] |
|“We're heading from a world of "Have" and "Have-nots" to a world of "Haves" and "Super-haves". I think the final result of |
|technology is a sort of "Technology-socialism" where tech is handling our basic needs... now i'm personally a |
|libertarian-capitalist by nature.” |
|The end result of technology is "technological socialism" where our basic needs are being met by Tech. I do think we will be |
|re-inventing the economy (or what ever that means) and will end up where energy and information are the two most precious |
|resources. |
|[Source] |
His view is that once devices become so good, then there won’t even be any professionals. He doesn’t understand the conception of LIMITLESS human needs. Therefore, there will still be many fields in which jobs will continue to be created.
Just because only 2 per cent of us now work in agriculture doesn’t mean jobs have disappeared. We just do different things, and many more of them.
And under no circumstance can prosperity continue when even the remotest whiff of socialism comes into the system.
Examples of robotic innovations (including AI)
Robots are widely used today, in hospitals, manufacturing, police, armed forces, aged care facilities – and virtually everywhere else. We are mostly unaware of their presence, so successfully has this transition to robotics been.
A summary on almost all robots can be found here:
1 Smart assistants
1 Expliner High-Voltage Power Transmission Line Inspection Robot
A phenomenal solution for bushfire prevention in Victoria. Alternative inspection (physical/helicopter) required by the Regs is both inadequate and expensive.
2 Spare tyre mounting robot
The spare tire mounting robot has been in action since January, 2010 at an assembling line of Takaoka plant of the company (Figure 1) and by September 2010 successfully mounted 100,000 spare tires automatically in cars within 4550 s without any troubles. Thanks to newly developed load compensation mechanisms and control algorithm, the robot allows to be driven by small servomotors of 80 W to handle heavy objects so that the system can work together with human workers without any special safety measures like safety fences, working area separation, etc. conforming to the global safety regulations. [Source: Race against the Machine]
3 Packing assistant
[pic]
4 Automated vacuum cleaners
iRobot etc.
5 Toys
• robotic hamsters (Zhu Zhu)
• robotic penguins
• indoor-flying iPhone controlled quad copter by Parrot.
6 Hospital assistants
Medical robotics (included in the services sector) are poised for many years of rapid growth propelled by:
• Growing patient demand for non-invasive surgery,
• The current effort to reduce hospital costs by increasing productivity through a variety of robotic activities (non-invasive surgery, pill dispensing, materials transfer, lab assistance, etc.),
• Hospitals, which have held back capital purchases (such as Intuitive Surgical's million dollar da Vinci devices) for the past two years, are beginning to reinvest in these types of equipment. [Source]
1 Medicine Picking and Delivering Robot System
Medicine Picking and Delivering Robot System hospital robot (Robot for accurate delivery of the right medicines to patients - used in 50 hospitals already)
2 Surgical assistants
Over the last decade significant progress has been made in medical robotics. Today several thousand prostate operations are performed using minimally invasive robots, and the number of cardiac procedures is also increasing significantly
Three-armed robot known as da Vinci®, which has helped to usher in the next generation of minimally invasive surgery
[pic]
The practice of robotic surgery is currently largely dominated by the da Vinci system of Intuitive Surgical (Sunnyvale, CA, USA) but other commercial players have now entered the market with surgical robotic products or are appearing in the horizon with medium and long term propositions. [Source]
3 Heavy lifter
7 Military assistants
Robots in unstructured environments (e.g. iRobot bomb disposal robots)
8 Police assistants
1 Spying robot:
[pic]
2 Robot micorobots/insects
9 Agriculture and fisheries assistants
In Japan drones dust crops and track schools of tuna [Source]
10 New forms of transport
[totally new forms of travel. A car takes the same space on the road as (potentially) 14 walkers. By crunching the space needed for the motor and eliminating the need for 4 wheels, future transport could take far less space - leading to a dramatic reduction in traffic congestion:
Major solution to traffic congestion:
11 Manager’s assistants
Telepresence robots:
12 Bee pollination assistant
Robobee - pollinator/surveillance
2 Workers (in manufacturing)
1 Industrial robots
There are a massive number of industrial robots that operate in manufacturing plants, and have almost entirely replaced humans.
The world's fastest robot (in Australian).
3 Workers (in retail/service industry)
1 Burger maker
This robot can make 340 burgers per hour
4 Humanoid robots
HUMANOID ROBOTS - STILL NOT A THREAT TO JOBS
Humanoid robots will take time - 25 more years - to displace jobs. But in the meanwhile industrial robots will displace hundreds of millions of jobs
5 Personal assistants
1 Translators
GeoFluent offering from Lionbridge has brought instantaneous machine translation to customer service interactions. [Race against the machine]
“"We hope that in a few years we'll be able to break down the language barriers between people," the senior vice-president of Microsoft Research told the audience. There was a tense two-second pause before the translator's voice came through.
Rashid continued: "Personally, I believe this is going to lead to a better world." Pause, repeat in Chinese.” []
A LOT of people offered to translate BFN into different Indian languages over the past 4.5 years, but not one was successful in completing the task. Most humans don't have time/capacity/determination to deliver on their commitments. Once this translating system is available (actually, it already is), BFN can be supplied in various Indian languages instantly - thus multiplying its spread 50 times.
2 Walking assistant
(HOW TO WALK)
3 Housemaid
Robots will NEVER become alive
I thought it is important to emphasise that robots will never become alive.
1 Kurzweil is wrong. Robots will never have a WILL TO LIVE. Hence never will displace man.
|Source: my blog post. |
|Today we have outstanding voice recognition programs. They do not recognise the MEANING of the words, however. Even being |
|fluent in syntax will never make it understand semantics. |
|We have outstanding facial recognition programs. They do not recognise the PERSON in the picture, only the superficial |
|reconstruction of the facial features. A bunch of pixels is NOT a person. |
|We have a program that can drive a car. That program, however, does not know even WHAT it is that it is doing, leave alone |
|know what it is avoiding hitting on the road. |
|We have a program that can beat the world Jeopardy champion. The program doesn't know WHAT it is doing, or even what is |
|jeopardy. |
|I came across the great debate between Ray Kurzweil and John Searle (this). |
|I think Searle wins hands down, but I'm not sure Searle has grasped (or articulated) the key point about consciousness. His |
|full talk on consciousness – see the original youtube video condensed below – ignores the sub-conscious mind – when we are |
|asleep. |
|But that's wrong. The real driver of the conscious mind is not "biological" (that's too general), it is a a natural property |
|of LIFE. |
|Kurzweil is right that we will use computers and computing in the future to radically improve and augment ourselves, even to |
|'dump' our memories (possibly – although I doubt it), even to live forever – assuming our bodies are regularly updated. |
|But at NO time will computers become ALIVE. They will remain our servants (sometimes even dangerous servants – e.g. if |
|programmed to autonomously shoot people down). |
|Consciousness is a unique quality of BIOLOGY. Even the smallest creature – a bacteria – has some form of consciousness. The |
|form of consciousness changes as the biological grunt power available to a creature, improves. Our consciousness is different |
|to that of a dog's or bacteria's but it is very clear that dogs are conscious. And cockroaches. And ants. And mites. |
|Consciousness is driven by the key property of life – a MOTIVATION or will to live. |
|That will, being a purely available to LIVING creatures (animals, to be precise), is designed to surmount obstacles to life. |
|It has a MOTIVATION in everything it does. It also has many subsidiary motivations (e.g. will to reproduce – normally |
|unconscious). |
|Biology is based on hardware but the hardware has FOUGHT ITS WAY THROUGH, to survive. Every second of the hardware's life is a|
|battle against entropy. There are millions of processes at work each moment in a living creature that sustain it from moment |
|to moment. And SOME of these lead to a conscious mind, where such a mind might add additional evolutionary value. |
|Indeed, 90 per cent of our will to live is UNCONSCIOUS. We don't know why our body lives, or wants to continue to live. Our |
|heart beats without our conscious permission. |
|The reason why hardware and software CANNOT replicate consciousness is because consciousness – and meaning – is the essence |
|of life. Meaning makes "sense" only in relation to LIFE. And in relation only to a living creature's capacity to survive in an|
|environment evolution has prepared it to survive in. |
|No matter how smart computers become, they will NEVER become ALIVE. For that to happen, we'll need a separate process – to |
|create life in the laboratory first. Since they will not have the will to live, nor a desire to be self-sustaining, or to |
|reproduce, they will NEVER compete with humans. |
|Having said that, we WILL achieve most of the things that Kurzweil talks about in the next 25 years. The age of abundance is |
|nearing, but we need not fear robots. |
|Our greatest enemy will remain the same as it has always been: MAN, including killer robots designed by man. |
Economic issues and concerns
1 GDP as an increasingly irrelevant measure of income
1 Digital goods are not traded
See my post:
2 Consumer surplus is not measured
See my post:
2 Glorious abundance doesn’t mean absence of scarcity
If there is abundance of everything then much of economics becomes irrelevant. There is a fundamental law of economics, though, that there is no Nivrana or total satiation.
People are not going to stop wanting things. Once they have material goods they’ll want other (mental/spiritual) goods. Something will always be scarce, including prized places of residence.
Further, total of production will never drop to zero (although marginal costs may well drop to zero in some cases).
Therefore, all that the idea of ‘glorious abundance’ refers to is that mankind would have have managed to produce most goods required for its sustenance at very low costs.
3 Machines and humans: complements or substitutes?
Robin Hanson asks: are machines and humans complements or substitutes?
IT is a general purpose technology. Robots can do routine things,. Human will need to do creative things.
A human-computer symbiosis scenario can be imagined where the human is designed into the process.
“Asked about the claim that such advanced industrial robots could eliminate jobs, Brooks [producer of the Baxter robot] answers simply that he doesn’t see it that way. Robots, he says, can be to factory workers as electric drills are to construction workers: “It makes them more productive and efficient, but it doesn’t take jobs.”” [Source]
4 Cost/benefit of robots/IT/technology
Robots are not free. Therefore the general economic principle will always apply, that no business will deploy robots unless the benefits of doing so exceed the costs.
Two key factors are making robots more likely to be deployed: (a) rising labour costs and (b) falling robot costs.
1 Capital robots and consumption robots
Different treatments will apply to long lived robots vs. shortlived ones (e.g. floor cleaning robots).
2 Economics of drones
The economics of cheap drone delivery.
5 Say’s law and robotics
The essential fear among technologists (and confused econmists) is that robotics will lead to greater supply than demand.
The reality is that in a free market the supply creates demand – since businesses only invest to the extent they anticiapate a demand. The fact that something is produced is indication that there is demand. A proper understanding of the Says’ law is crucial to understanding the future of the robotic economy.
6 Overall increase in prosperity/luxury
1 Productivity and growth
[pic]
Source:
“The economics of digital information, in short, are the economics not of scarcity but of abundance”. [Source: Race Against Machines]
1 The May 2013 McKinsey report
Source:
|5. Advanced robotics |
|During the past few decades, industrial robots have taken on a variety of manufacturing tasks, usually those that are |
|difficult, dangerous, or impractical for humans—welding, spray-painting, or handling heavy materials, for example. Robotics is|
|now seeing major advances that could make it practical to substitute machines for human labor in increasing numbers of |
|manufacturing applications, in many service applications, and, importantly, in extremely valuable uses such as robotic surgery|
|and human augmentation. Advances in artificial intelligence, machine vision, sensors, motors, and hydraulics—even in materials|
|that mimic a sense of touch—are making this possible. Robots are not only becoming capable of taking on more delicate and |
|intricate tasks, such as picking and packing or manipulating small electronics parts, but they are also more adaptable and |
|capable of operating in chaotic conditions and working alongside humans. At the same time, the cost of robots is declining. |
|Advanced robotics promises a world with limited need for physical labor in which robot workers and robotic human augmentation |
|could lead to massive increases in productivity and even extend human lives (see Box 7, “Vision: Machines end physical toil |
|and improve lives”). Many goods and services could become cheaper and more abundant due to these advances. The physically |
|handicapped and the elderly could lead healthier and less-restricted lives using robotic prosthetics and “exoskeletons” that |
|strap on like braces and assist in locomotion. We estimate that the application of advanced robotics across health care, |
|manufacturing, and services could generate a potential economic impact of $1.7 trillion to $4.5 trillion per year by 2025, |
|including more than $800 billion to $2.6 trillion in value from health-care uses. This impact would result from saving and |
|extending lives and transforming the way in which many products are built and many services are delivered. |
|Advanced robotics also holds a great deal of promise for businesses and economies. Early adopters could gain important |
|quality, cost, and speed advantages over competitors, while some companies could find that advanced robotics lowers the |
|barriers for new competitors. Businesses in developing economies could be among the biggest buyers of robotics given the |
|current rate of automation; however, these economies could be negatively impacted by falling demand for low-wage manual labor,|
|upon which they rely for economic development. The ability of robots to take on a far wider range of jobs economically could |
|encourage global companies to move some production back to advanced economies. In advanced economies, some workers might find |
|new job opportunities in developing, maintaining, or working with robots. At the same time, many jobs in advanced economies |
|involving manual labor might be automated away, placing even more importance on educating and retraining workers for |
|higher-skill jobs. |
|Box 7. Vision: Machines end physical toil and improve lives |
|Imagine a world in which advanced robots expertly and inexpensively perform and augment most physical tasks. Imagine you are a|
|manager in a manufacturing plant in 2035. At your plant, injuries are virtually unheard-of. In fact, there are few people on |
|the floor: a small group of highly skilled |
|specialists oversee thousands of robots, interacting naturally with the robot workforce to produce goods with unprecedented |
|speed and precision, |
|24 hours a day, 365 days a year. |
|When a new product or design improvement is introduced, factory workers train robots to follow new routines, using simple |
|touch-screen interfaces, demonstration, and even verbal commands. Most of your day is spent optimizing processes and flows and|
|even assisting with product designs based on what you see on the factory floor and the data that your robots generate. |
|During lunch, you swing by a local fast-food restaurant. You watch as your meal is prepared and cooked exactly the way you |
|like it by a robot. Back at your desk, you see service robots making deliveries and cleaning the floors and windows. Outside, |
|robots pick up trash and replace broken street lights. |
|In a world of advanced robotics, surgeons are assisted by miniature robotic surgery systems, greatly reducing both the time |
|necessary for procedures and their invasiveness. Recovery is more rapid as well. People suffering from paralysis due to spinal|
|injuries are able to walk again with the help of robotic exoskeletons directly connected to the nervous system. |
|DEFINITION |
|Traditional robots excel at tasks that require superhuman speed, strength, stamina, or precision in a controlled environment |
|(robot welding or semiconductor fabrication, for example). They are bolted in place behind railings to prevent injuries to |
|humans. They do exactly what they are programmed to do—and nothing more. But now, a new generation of more sophisticated |
|robots is becoming commercially available. These advanced robots have greater mobility, dexterity, flexibility, and |
|adaptability, as well as the ability to learn from and interact with humans, greatly expanding their range of potential |
|applications. They have high-definition machine vision and advanced image recognition software that allows them to position |
|objects precisely for delicate operations and to discern a part in a pile. They are powered by sophisticated motors and |
|actuators, allowing them to move faster and more precisely, and some are made from lighter, softer materials. The US Defense |
|Advanced Research Projects Agency (DARPA) is even working on robots that can fully automate the sewing of garments, using a |
|process that tracks the movement of individual threads and precisely moves fabric to perform exact stitching .64 |
|64 Katie Drummond, “Clothes will sew themselves in DARPA’s sweat-free sweatshops,” Wired, June 8, 2012. |
|Advances in artificial intelligence, combined with improved sensors, are making it possible for robots to make complex |
|judgments and learn how to execute tasks on their own, enabling them to manage well in uncertain or fluid situations. By 2025 |
|advanced robots could be capable of producing goods with higher quality and reliability by catching and correcting their own |
|mistakes and those of other robots or humans. These robots can sense and quickly react to obstacles, other robots, or human |
|coworkers, giving them greater “awareness” and making it possible for them to work more safely side-by-side with humans. Many |
|advanced robots can also communicate with one another and work together on shared tasks. Some advanced robots are designed to |
|be simple, small, and inexpensive, while having the ability to be networked together and work in teams. These distributed, or |
|“swarm,” robots could eventually be used for dangerous tasks such as search and rescue operations. |
|Finally, advances in interfaces, sensors (including sophisticated tactile sensors), and actuators, combined with improved |
|materials and ergonomic designs, are furthering robotic surgery and dramatically improving the quality and usefulness of human|
|prosthetic devices. Ultraprecise surgical robots are making new forms of minimally invasive surgery possible that can reduce |
|postsurgical complications, enable faster recovery, and possibly reduce surgical death rates. Robotic prosthetics and |
|exoskeletons are able to take precise directions and make increasingly accurate and delicate movements. New interfaces have |
|been |
|developed that can operate robotic limbs using small electrical signals produced when muscles contract or using signals from |
|nerve endings or even brain waves. The capabilities of these prosthetics may soon come to rival or exceed those of actual |
|human limbs. These advances could eventually include prosthetic hands with independently moving fingers and prosthetic body |
|parts that mimic the sense of touch using a neural interface.65 |
|These technological advances, combined with declining costs, are making entirely new uses for robots possible. For example, El|
|Dulze, a Spanish food processor, now uses highly agile robots to gently pick up heads of lettuce from a conveyor belt, measure|
|their density (rejecting heads that don’t meet company standards), and replace them on the belt, where other robots position |
|the heads for a machine that removes their roots. The company says the robots are better than humans at assessing lettuce |
|quality (the reject rate has fallen from 20 percent to 5 percent), and hygiene at the facility has also improved.66 |
|POTENTIAL FOR ACCELERATION |
|Adoption rates for advanced robots will be determined by many factors, including labor market conditions. For example, in |
|China, where wages and living standards are rising, workers are pressing for better working conditions, including relief |
|from long hours of precise piecework that can lead to repetitive stress injuries. As education levels rise, fewer workers are |
|willing to take such jobs. As a result, Foxconn, a contract manufacturer that employs 1.2 million workers, is investing in |
|robots to assemble products such as the Apple iPhone.67 According to the International Federation of Robotics (a major |
|robotics industry group), China is expected to become the world’s largest consumer of industrial robots by 2014. |
|65 Megan Scudellari, “Missing touch,” The Scientist, September 1, 2012. |
|66 68 robots perform farmer’s work, case study of Fanuc Robotics Europe S.A., International Federation of Robotics, September |
|2012. |
|67 John Markoff, “Skilled work, without the worker,” The New York Times, August 18, 2012. |
|Global manufacturing labor costs today are $6 trillion annually, so additional automation represents a huge opportunity. |
|Demographics will also play a role in determining demand for advanced robotics. Robotic surgical systems and prosthetics could|
|help meet the large and growing need (particularly in advanced, aging economies) to provide quality health care. And many |
|manufacturers still rely on legions of low-skill workers (often in developing countries) to do work that involves precise |
|operations on irregular objects, such as bending tiny wires to assemble mobile phones or deboning chicken breasts; over the |
|coming decade, many of these tasks could be automated. |
|New applications for advanced robotics, particularly in services, are also emerging. Robots are now poised to take on dirty, |
|dangerous, and labor-intensive service work, such as inspecting and cleaning underground pipes, cleaning office buildings, or |
|collecting trash. Domestic service robots are another expanding market. Though robotic vacuum cleaners have been around for |
|years, sales of these and similar household robots are now growing rapidly, by about 15 to 20 percent annually. Adoption could|
|accelerate even further by 2025 as these machines become more capable and consumers consider the trade-offs between buying |
|robots, sacrificing leisure time, or hiring professional cleaners or gardeners to perform these tasks. |
|Advanced robots are also of great interest to military planners, who see opportunities to both automate combat (similar to |
|remotely piloted drone aircraft) and support human troops. DARPA is investing in a range of advanced robotics programs, from a|
|full robotics “challenge” (similar to the DARPA Grand Challenge that pioneered self-driving cars) to four-legged robots for |
|carrying supplies, robotic exoskeletons and suits to strengthen and protect troops, and advanced prosthetic limbs to help |
|injured soldiers. This type of military investment could greatly speed further advancement. |
|Robot prices are dropping, placing them within reach of more users. Industrial robots with features such as machine vision and|
|high-precision dexterity typically cost $100,000 to $150,000. By 2025, it is possible that very advanced robots with a high |
|level of machine intelligence and other capabilities could be available for $50,000 to $75,000 or less. In recent decades, |
|robot prices have fallen about 10 percent annually (adjusted for quality improvements) and may decline at a similar or faster |
|rate through 2025.68 Accelerated price declines could be made possible by scale efficiencies in robot production (due in large|
|part to rising demand by Chinese and other Asian manufacturers), the decreasing cost of advanced sensors (partly driven by |
|demand for inexpensive sensors in smartphones and tablets), and by the rapidly increasing performance of computers and |
|software. Some entrepreneurs are focusing on developing inexpensive general purpose robots that can be easily trained to do |
|simple tasks (see Box 8, “Your new coworker, Baxter”). |
|The rate at which robots could proliferate is a subject of intense debate. According to the International Federation of |
|Robotics, industrial robot sales reached a record 166,000 units in 2011, a 40 percent jump over 2010; sales in China grew by |
|more than 50 percent in 2011. Since 1995 global sales have grown by 6.7 percent per year on average. It is possible that there|
|could be even faster |
|68 World robotics 2012, International Federation of Robotics, August 30, 2012. |
|growth ahead if Baxter and other low-priced, general-purpose models can drive rapid adoption in simple manufacturing and |
|service work. At the same time, installations of advanced industrial robots could accelerate beyond historic rates if robotics|
|technology continues to accelerate. Adoption scenarios will depend both on improvements in capability and price and |
|receptivity to automation; in addition, significant organizational and societal barriers may stand in the way. |
|Box 8. Your new coworker, Baxter |
|To make robots useful in low-end manufacturing, they not only have to be priced attractively, but they also need to fit into |
|the workplace. They can’t take up too much space, they have to work well and safely with humans, and they have to be easy to |
|program. These were some of the goals for “Baxter,” a $22,000 general-purpose robot developed by startup company Rethink |
|Robotics. Another goal was to put a friendly face on robots—literally. Baxter features an LCD display screen mounted on a |
|“neck” above its |
|body. The screen shows a pair of eyes that take on different expressions depending on the situation. The eyes follow what the |
|robot’s two arms are doing, as a human worker would. |
|While Baxter’s functionality is somewhat limited—it is best at performing simple operations such as picking up objects, moving|
|them, and putting them down—it makes up for these limitations with superior adaptability and modularity created by the ability|
|to install different standard attachments on its arms. When the robot is first installed or needs a new routine, it “learns” |
|without the need for programming. A human simply guides the robot |
|arms through the motions that will be needed for the task, which Baxter memorizes. It even nods its “head” to indicate that it|
|has understood its new instructions. |
|POTENTIAL ECONOMIC IMPACT |
|We estimate that by 2025 advanced robotics could have a worldwide economic impact of $1.7 trillion to $4.5 trillion annually |
|across the applications we have sized (Exhibit 7). Much of this impact—$800 billion to $2.6 trillion—could come from improving|
|and extending people’s lives. An additional $700 billion to $1.4 trillion could arise from automating manufacturing and |
|commercial service tasks. We estimate that the use of advanced robots for industrial and service tasks could take on work in |
|2025 that could be equivalent to the output of 40 million to |
|75 million full-time equivalents (FTEs). This could potentially have annual economic impact of $600 billion to $1.2 trillion |
|in developed countries and $100 billion to $200 billion in developing economies. Finally, $200 billion to $500 billion in |
|impact could arise from the use of time-saving household service robots. |
|Exhibit 7 |
|Sized applications of advanced robotics could have direct economic impact of $1.7 trillion to $4.5 trillion per year in 2025 |
|[pic] |
|1 Using QALY (quality-adjusted life years) estimates. |
|NOTE: Estimates of potential economic impact are for some applications only and are not comprehensive estimates of total |
|potential impact. Estimates include consumer surplus and cannot be related to potential company revenue, market size, or GDP |
|impact. We do not size possible surplus shifts among companies and industries, or between companies and consumers. These |
|estimates are not risk- or probability-adjusted. Numbers may not sum due to rounding. |
|SOURCE: McKinsey Global Institute analysis |
|Health care |
|We estimated the potential economic impact of robotic surgery and robotic prosthetics to be as much as $800 billion to $2.6 |
|trillion annually by 2025, based on saving lives and improving quality of life. For estimating the potential economic impact |
|of robotics for human augmentation, we considered potential uses of robotic prosthetics and exoskeletons.69 By 2025 there |
|could be more than 50 million people with impaired mobility in the developed world, including amputees and elderly people, for|
|whom robotic devices could restore mobility, improve quality of life, and increase lifespan. It is possible that 5 to 10 |
|percent of these people could have access to robotic augmentation by 2025 given the current penetration of alternatives such |
|as traditional prosthetics and motorized wheelchairs. Studies indicate that impaired mobility contributes significantly |
|to reduced life expectancy due to increased health risks such as injury and osteoporosis .70 |
|If it were possible to extend life by one to two years for each disabled person and provide a 20 to 30 percent improvement in |
|quality of life over eight years using |
|69 Robotic mechanisms that can be worn by physically handicapped people to help move limbs (or even entire bodies). |
|70 For more on the effects of disabilities on life expectancy, see R. Thomas and M. Barnes, “Life expectancy for people with |
|disabilities,” NeuroRehabilitation, May 2007. |
|robotic assistance (assuming substantial restoration of normal function) the result could be a potential impact of $240,000 to|
|$390,000 per person, using a quality-adjusted life year (QALY) approach. If these results can be achieved, robotics for human |
|augmentation could lead to a potential economic impact of $600 billion to $2 trillion per year by 2025, much of which could be|
|consumer surplus accruing to the users of these robotic devices. |
|As the technology for robotic surgery improves, it could have the potential to prevent deaths and significantly reduce both |
|in-patient care time and missed work days. Robotic surgical “platforms” are already being used for minimally invasive |
|procedures such as laparoscopic surgery. It is possible that with advances in robotic technology, by 2025 robotic surgery |
|could be widely used for these and other procedures. Approximately 200 million major surgeries could be performed every year |
|in countries with developed health-care systems in 2025.71 Currently, about 3 percent of all major surgeries result in death, |
|but it is possible that by 2025, advanced robotic surgical systems could help reduce these deaths substantially, perhaps by as|
|much as 20 percent, by reducing common complications such as bleeding or internal bruising. |
|This improvement in outcomes could be enabled by more flexible surgical robots with a greater range of motion that could |
|perform more types of operations, or from new features such as AI-assisted autocorrect systems that could warn surgeons when |
|they are about to cut the wrong tissue or apply too much pressure. Declining costs in robotic surgery systems could allow more|
|hospitals and surgeons to use the technology, potentially increasing the performance of many surgeons. We estimate that if 5 |
|to 15 percent of all major surgeries in countries with developed health-care systems could be performed with the assistance of|
|robots by 2025, it could result in 60,000 to 180,000 lives saved each year. Robot-assisted surgery could also cut in-patient |
|stays and sick days associated with surgery by 50 percent. If these results can be achieved, we estimate that robotic surgery |
|could have an economic impact of $200 billion to $600 billion per year by 2025.72 |
|Industrial robots |
|For industrial robots, we analyzed data regarding job tasks, occupations, and distribution across countries .73 We then |
|considered which tasks could be fully or partially automated economically by advanced robots by 2025, assuming a high level of|
|robot performance and continued reductions in cost. In developed countries, across occupations such as manufacturing, packing,|
|construction, maintenance, and agriculture, we estimate that 15 to 25 percent of industrial worker tasks could be automated |
|cost-effectively (based on estimated 2025 wage rates) by 2025. We estimate that in developing countries, on average, 5 to 15 |
|percent of manufacturing worker tasks could be automated across relevant occupations by 2025. |
|71 Based on analysis by Thomas G. Weiser et al., “An estimation of the global volume of surgery: A modeling strategy based on |
|available data,” Lancet, volume 372, number 9633, July 12, 2008. |
|72 We use a quality-adjusted life year (QALY) of $100,000 and assume that surgical patients avoiding death are restored to a |
|normal life expectancy. |
|73 Analysis of job occupations and tasks is based on data from a variety of sources, including labor and wage data from the |
|Economist Intelligence Unit, International Labour Organisation, IHS Global Insight, Eurostat, and various national labor |
|bureaus. |
|We calculated the potential cost savings using the estimated annual cost of advanced robots compared with the annual |
|employment cost of an equivalent number of workers. This yields a potential economic impact of $600 billion to $1.2 trillion |
|per year by 2025. This would imply a substantial increase in the number of industrial robots installed globally by 2025, by |
|about 15 million to 25 million robots, requiring investments totaling about $900 billion to $1.2 trillion. Realizing all of |
|this potential impact would therefore imply 25 to 30 percent average annual growth in robot sales, significantly higher than |
|the average growth rate over the past two decades, but lower than the growth rate in 2010 and 2011. |
|Service robots |
|Service robots fall into two categories: those used in commercial settings and personal robots. For personal and household |
|service robots, we focused on the potential to automate cleaning and domestic tasks such as vacuuming, mopping, lawn mowing, |
|and gutter cleaning. The use of advanced robots for these types of tasks has significant potential given the current |
|trajectory of technology improvement, the relatively low cost of the robots required, and the already increasing rate of |
|adoption. Sales of household robots used largely for |
|the above-mentioned tasks are already growing by about 20 percent annually. To estimate the potential impact of household |
|robots, we considered the amount of time spent on relevant cleaning and domestic tasks, focusing on the developed world, where|
|significant adoption is most likely. Based on US and European labor studies, we estimate that 90 billion to 115 billion hours |
|per year are spent performing relevant household tasks in the developed world.74 If 25 to 50 percent of people in the |
|developed world were to adopt the use of these robots by 2025, $200 billion to $500 billion worth of time savings could be |
|realized. We believe this level of adoption is possible given the rapid advances in low-cost robotics technology, the |
|relatively limited sophistication of the robots required for these applications, and the demonstrated willingness of many |
|consumers to pay for household time-saving devices. |
|For commercial service robots, we analyzed data on job tasks, occupations, and distribution across countries .75 We then |
|considered which tasks could be fully or partially automated economically by advanced robots by 2025, assuming a high level of|
|robot performance and continued reductions in cost. We estimate that in developed economies, across occupations such as food |
|preparation, health care, commercial cleaning, and elder care, as much as 7 to 12 percent of commercial service worker tasks |
|could be automated cost-effectively by 2025. For example, nurses spend up to 20 percent of their shift time wheeling equipment|
|and carts from one location to another or waiting for a cart to arrive. So-called courier robots (self-guided, motorized |
|carts) can take on these tasks. We estimate that |
|in developing countries, 4 to 8 percent of commercial service worker tasks could be automated across relevant occupations by |
|2025. To achieve this, we estimate that 2.5 million to eight million advanced robots would be necessary, requiring an |
|estimated investment of $200 billion to $400 billion globally by 2025. |
|74 Estimates based on data from Rachel Krantz-Kent, “Measuring time spent in unpaid household work: Results from the American |
|time use survey,” Monthly Labor Review, volume 132, number 7, July 2009. |
|75 Analysis of job occupations and tasks based on data from a variety of sources, including labor and wage data from the |
|Economist Intelligence Unit, International Labour Organisation, IHS Global Insight, Eurostat, and various national labor |
|bureaus. |
|BARRIERS AND ENABLERS |
|There are several important barriers that could limit adoption of advanced robotics by 2025. First, although costs are |
|declining, most industrial and many commercial service robots remain expensive, costing tens or hundreds of thousands of |
|dollars per robot. Surgical robots often cost more than $1 million (although these costs could come down and few of these |
|might be needed compared with industrial and service robots). Large-scale adoption of industrial and service robots could |
|require investments of perhaps $1.1 trillion to $1.6 trillion by 2025. Before making these investments, companies would likely|
|require strong evidence of positive returns on investment, and establishing a clear track record of performance could take |
|years. And once robots are purchased and installed, |
|it can still take time to redesign processes and flows to fully take advantage of their capabilities. |
|Surgical robots have already seen significant growth in adoption, but additional trials and data will be required to fully |
|demonstrate their benefits, particularly given concerns about health-care costs in the United States and other advanced |
|economies. There are also questions about whether robotically assisted surgery has demonstrated significantly better |
|performance than nonrobotic minimally invasive surgery techniques, which are less costly. While the capabilities and |
|performance of the technology could improve significantly by 2025, adoption may be constrained until definitive proof of |
|results is available. |
|The talent required to operate and maintain advanced robots is an important enabler that will be required to fully capture |
|their potential. Some advanced robots could be designed to be very user-friendly and able to work naturally side-by-side with |
|humans, but advanced robots may still require a high level of expertise to maintain their hardware and software. |
|Finally, the potential effect of advanced robots on employment could generate social and political resistance, particularly if|
|robots are perceived as destroying more jobs than they create. Although the productivity improvements that advanced robots |
|would create would drive growth in the economy, the workers who would be displaced might not be easily re-employed. Policies |
|discouraging adoption of advanced robots—for example, by protecting manual worker jobs or levying taxes on robots—could limit |
|their potential economic impact. Policy makers will face difficult questions regarding legal liability, such as determining |
|who is at fault when service or household robots contribute to accidents or injuries. |
|IMPLICATIONS |
|Over the coming decade, advanced robotics could deliver tremendous value for robot creators, health-care providers, |
|manufacturers, service providers, entrepreneurs, consumers, and societies. For many businesses, advanced robotics promises |
|significantly reduced labor costs, greater flexibility, and reduced time to deliver products to the marketplace. Business |
|leaders should look for opportunities to leverage growing technology capabilities to help automate difficult, labor-intensive,|
|and dangerous tasks in ways that are simple, user-friendly, and cost-effective, whether for treating patients or automating |
|manual work. |
|For hospitals and health-care providers, advanced robotics could ultimately offer substantial improvements in patient care and|
|outcomes. As a result, providers |
|of robotic systems and supporting tools or services could see large growth opportunities over the coming decade. Makers of |
|robotic surgical systems could see strong demand for increasingly advanced systems but also feel pressure to minimize costs |
|and clearly demonstrate improved outcomes for patients. Makers of robotic prosthetics and exoskeletons could experience |
|similarly high demand and may want to look for ways to reach disabled and elderly people around the world, even in |
|less-developed regions. |
|Manufacturing and service companies with large workforces could benefit from reduced costs, reduced injuries, and lower |
|overhead, as well as reducing payrolls in human resources, labor relations, and factory supervisory roles. Factories might no |
|longer need to be located near sources of low-cost labor, allowing them to be located closer to final assembly and consumers, |
|simplifying supply chains and reducing warehousing and transportation costs. |
|However, business leaders will face challenges in capturing the full productivity and quality improvements that could be |
|afforded by advanced robots. Advanced robotics requires substantial capital investments, and businesses will need clear |
|evidence of positive return on investment. Reconfiguring manufacturing processes, service delivery channels, and supply chains|
|is difficult and time-consuming. Training employees to work effectively alongside robots is also no small task. To maximize |
|value capture and stay ahead of the curve, businesses should continually experiment with advanced robotics and additional |
|automation, identify promising technologies, rethink business processes, and develop in-house talent. They should also |
|consider how their supply chains could be redesigned to leverage automation, and how additional speed to market, flexibility, |
|and quality could help differentiate their offerings from those of competitors. |
|For some entrepreneurs, decreasing robot cost and increasing capabilities could make entirely new business models possible or |
|decrease barriers to entry in the manufacturing and service industries. Robotically enabled production facilities, fast-food |
|restaurants, self-service laundries, and medical clinics might offer superior efficiency and quality and could scale quickly. |
|Established manufacturers may need to accelerate automation to meet the competition while investing in innovative product |
|development or superior service quality to better differentiate their offerings. |
|For societies and policy makers, the prospect of increasingly capable robots brings potential benefits: growing national |
|productivity, higher-quality goods, safer surgeries, and better quality of life for the elderly and disabled. But it also |
|poses new challenges in employment, education, and skill training. In some cases, access to advanced robotics could cause |
|companies to repatriate manufacturing operations from low-wage offshore locations. And the spread of robotics could create new|
|high-skill employment opportunities. But the larger effect could be to redefine or eliminate jobs. By 2025, tens of millions |
|of jobs in both developing and advanced economies could be affected. Many of these employees could require economic assistance|
|and retraining. Part of the solution will be to place even more emphasis on educating workers in high-skill, high-value fields|
|such as math, science, and engineering. |
2 Increased expectations
The better the health robots, the more the demand for even more of them.
The expansion of the percolation of luxuries will continue unabated.
3 Really low prices
Effect of competition and really low prices:
But there is a point at which it is uneconomic to supply:
The robotic economy will be deflationary. Please get the confused Keynesians out of the way.
Some time ago I wrote about the irrational fear among Keynesians of deflation.
The key argument against deflation is two-fold:
a) It prevents consumers from buying things today in anticipation of lower future prices.
b) It prevents investors from investing in new projects since they are likely better off by simply putting their money in the
bank.
I disagree on both counts.
When PCs first came into the market (in the 1980s) we (the consumers) always knew that if we waited long enough, prices would be lower and quality higher. But that never prevented a good number of us from bying computers immediately, since the benefits of that specific purchase exceeded costs.
Similarly, despite knowing that prices of PCs are going to fall dramatically over time, producers have never hesitated in ramping up production. The cost-benefit of the investment decision already TAKES INTO ACCOUNT future lower prices. It is the overall ROI that matters, not future prices per se.
Consumers and investors make decisions on the basis of MARGINAL analysis. They do not care about the specific value of ANY single parameter (like price). They care ONLY that net benefits (or consumer surplus) > net costs (price).
Businesses can make HUGE PILES OF MONEY even in the face of falling prices.
Keynesian ideas are fundamentally flawed; not based on ANY credible economic analysis.
Keynesian policies are preventing USA/Japan from growing rapidly
If prices were allowed to fall in USA/Japan, consumers would open up their purse strings and start buying. That would prompt efficient producers to start producing (for whom the scale of the demand is a crucial signal) and rapidly bring the global economy out of its extended slump.
But such ideas are anathema to the typical Keynesian thinks consumers will only consume, and businesses invest, under inflationary conditions.
Who ever gave them this stupid idea?
Why are these people trying to second-guess optimal free market decisions? Who ever allowed them to graduate as economists?
I can only say this: that if Keynesian ideas are not entirely rejected by the world, then the onset of the Robotic Age – and the glorious abundance that will accompany is - will be greatly delayed.
The Robotic Age will be accompanied by continuous PRICE DEFLATION for MOST goods and services.
The Robotic Age cannot tolerate Keynesian policies of artificial (monetary/fiscal) inflation.
It doesn't matter in the Robotic Age how little consumers are willing to spend. It will STILL be profitable to produce goods.
Lower prices, better quality (and high – but possibly decreasing median wages) are not a bad thing. They are the sign of ABUNDANCE.
Let the market find out its own prices.
Move out of the way, Ben Bernanke and Paul Krugman. You are seriously harming the world.
Addendum
For those who protest that Keynesianism is largely related to fiscal policy, let me agree that there are strong traces of monetarism in the low interest rate/quantitative easing strategies of the Fed. These policies, however, are Keynesian in approach since they aim to stimulate the economy. I disagree with any approach to 'fine-tune' the economy through the central banking system.
4 Laws of investment will not change
Key point: Even large technology companies can easily go bankrupt (e.g. Amazon works at less than 1 per cent margin). Competition can drive down prices very steeply. Multiple players in each technology will keep driving costs down. And although owners of the technology will prosper it doesn’t seem likely that they will get exceptionally richer.
|Suppose General Motors owns an industrial robot. As you say, it requires energy, maintenance, etc. All that is NOT |
|consumption. It is an input used in producing cars. Consumption occurs when someone BUYS A CAR. If no one is buying cars, GM |
|will shut the robot down. Imagine an extreme case of a fully automated economy. No one has a job or an income. No one can buy |
|anything. All the machines would end up getting shut down, and warehouses would be full of consumer products that no one could|
|buy. [Source] |
But this argument is false
|it is much better to simply model consumption as being something that an agent does when they take in low-entropy resources |
|and spits out high-entropy waste. Then it becomes *abundantly* clear that humans, machines and corporations all act as |
|consumers. You do not need to be a person with a bank account to consume. |
|The robot fuel and parts count. They create a demand for a good or service that did not exist before. Add up all the purchases|
|being made instead (ignoring who is making them) – to understand where the demand for goods in the economy is *actually* |
|coming from – and then you will see that corporations and machines can account for purchases just as well as humans can – |
|without the “sci-fi” of robots with incomes and bank accounts. [Source] |
Key issue is that companies will produce ONLY if it is economically viable. That includes assessing future prices and demand. Technology companies KNOW today that future prices will fall. They STILL choose to produce. Therefore, lower prices or lower ability to pay is NOT an issue of any concern.
5 Rising manufacturing productivity
[pic]
6 Increasing share of services in economic output
Consistent with the increasing share of services in employment, the share of services in output has also been increasing.
[pic]
Source
7 Effect on innovation and entrepreneurship
We’ll continue to see an exponential increase in innovation.
1 Start-ups are cheaper
|“A tiny company with a dozen people has access to infrastructure that only the largest multinational could afford 15 years |
|ago,” Varian says. “You can put in Voice over IP, you have Google Docs, Wiki, email, social networks, chat. These tools would |
|have been ridiculously expensive 15 years ago and now they are free, ubiquitous. So you can co-ordinate productive activity |
|globally at a very low cost.’’ [ |
|A 2011 research report for the Kauffman Foundation by E. J. Reddy and Robert Litany found that even though the total number of|
|new businesses founded annually in the United States has remained largely steady, the total number of people employed by them |
|at start-up has been declining in recent years. This could be because modern business technology lets a company start leaner |
|and stay leaner as it grows. [race against machine] |
| |
|Shortly after the Luddites began smashing the machinery that they thought threatened their jobs, the economist David Ricardo, |
|who initially thought that advances in technology would benefit all, developed an abstract model that showed the possibility |
|of technological unemployment. The basic idea was that at some point, the equilibrium wages for workers might fall below the |
|level needed for subsistence. A rational human would see no point in taking a job at a wage that low, so the worker would go |
|unemployed and the work would be done by a machine instead. [ [Race against the machine] |
8 Effect on labour share
Labour share has much to do with bargaining power. Bargaining power is related both to marginal productivity and relative scarcitiy of a resource.
There are some suggestions that technology might be reducing labour share (i.e. their bargaining power).
E.g Loukas Karabarbounis and Brent Neiman in The Global Decline of the Labor Share, June 2013, suggest that “the decrease in the relative price of investment goods, often attributed to advances in information technology and the computer age, induced frms to shift away from labor and toward capital.”
[pic]
Source
1 Workers’ bargaining power significantly reducing
No doubt there are continuing effects of Obama's terrible policies but also the rapid improvement in technology that mean the same output now needs less workers. "Workers feel like they have absolutely no bargaining power," said Robert Mellman, an economist at J.P. Morgan Chase & Co. [Source].
2 But labour share was much lower in the past
That IT (and ultimately robotics) has a role to play in this is not self-evident.
[pic]
Source
3 Industries where significant loss in labour share is occurring
Bargaining capacity of labour is reducing most in mining, transport, manufacturing and utilities.
[pic]
Source
4 Most importantly, labour share is irrelevant
Just like inequality is irrelevant, so also labour share is irrelevant. These are SOCIALIST CONCERNS and we should not waste time worrying about them.
It doesn’t matter what share of the “pie” is split between capital and labour. What matters (in the broad, philosophical sense) is that (a) people are free (b) there is justice and good governance, (c) as a result the pie is increasing and (d) no one is worse off. Let labour and capital bargain in freedom. The main thing is there should be incentives for, and freedom, to produce and create wealth through new technology and innovation.
Robotics and IT is entirely positive, the moment people remove their socialist blinkers.
9 Effect on jobs
In my view, things that will retain value even the robotic age include: land, time, meaning, beauty, health, the company of others, children.
[pic]
It is expected that the forthcoming improvemens in robotics will be accompanied by the largest job-shedding episode in human history. Job creation will also occur, but will not keep pace with job-shedding. Much of this net loss of jobs will likely be permanent.
By the 2020s it can be reasonably expected that robotics would have matured and replaced millions of semi-skilled workers across the world, particularly from the developing world. Industry would have moved back to the developed world. The competitive advantage in robotics will likely see the baton of world economic leadership pass on to Japan and S.E. Asia (along with USA and Germany), which are currently leaders in robotics.
“Farms employed 90% of the population; automation reduced it to 5%. The children of farmers worked in industry. When automation destroyed those jobs, their children became service workers: technicians, managers, etc. Each step up increased our productivity, hence our income and wealth. Can this continue?” [Source]
Jobs are not just leaving China or USA, they are leaving the PLANET. No more jobs to produce things like shoes. ONLY designers of products are needed, given universal robots and 3d printers. [see: ]
However, there is reason to be more cautious about such claims:
|jdoe: "Some time ago (I think in the '60s), experts predicted that with continuing technological advances and increased |
|productivity, the work week would shorten to 20 something hours. Instead, the opposite happened. Americans work longer hours |
|than ever. Two parents must now work just to make ends meet, whereas one parent used to suffice. Americans, at least the |
|middle class, certainly have seen any real tangible benefits of automation. Quite the opposite. Not to sound pessimistic, but |
|I'm not so sure the future will be much different." [Source] |
[pic]
|When robots take our jobs, humans will be the new 1%. Here's how to fight back |
|Michael Belfiore, The Guardian, 22 March 2014 |
|Will you be replaced by a machine? There's nearly a 50-50 chance, according to a recent study by Oxford University researchers|
|who found that 47% of the labor market in the US alone is at risk of being mechanized out of existence. Approximately 702 jobs|
|thus far held by humans are now threatened by non-humans, as we were reminded by a widely shared report on the study this |
|week. |
|It’s not hard to see why. Advances in robotics and artificial intelligence are bringing robots into more and more workplaces. |
|For example: |
|Autonomous vehicles now in development by just about every major automaker threaten the jobs of truckers and cabbies. |
|The Baxter robot from Rethink Robotics is designed to work side-by-side with human factory supervisors, learning new tasks on |
|the go – something only human workers could do previously. |
|Robotic surgeons such as those made by Intuitive Surgical and the open-sourceRaven project currently require human surgeons in|
|the loop, but inroads have already been made into giving these machines autonomy as well. |
|Unmanned aerial vehicles – as in, drones – are getting set for integration into the US national airspace next year, |
|potentially replacing the jobs of many human pilots. |
|My profession isn't immune to robotic outsourcing either. The Quill robotic journalist digests facts from raw data, and spits |
|out fully formed sports and business stories. |
|Oh, and Mark Zuckerberg and Elon Musk are now backing "a computer that thinks like a person except it doesn't need to eat or |
|sleep". So there's that. |
|There’s even a robotic burger flipper in the works. The website of Momentum Machinesboasts that its slicing, grinding, frying |
|robot can do "everything employees can do except better", and that it will "democratize access to high-quality food, making it|
|available to the masses". |
|All of which begs the question: will there be anyone left who can afford those better burgers, or will everyone be out of |
|work? And what the hell are we supposed to do about the inevitable rise of the machines? |
|The march of the worker drones does seem inevitable, and not just into specialized job functions. The Pentagon's mad-science |
|research arm, Darpa, is currently hosting theDarpa Robotics Challenge for the creation of humanoid robots capable of working |
|in disaster areas that are too dangerous for humans. These all-purpose machines are designed to let themselves into buildings |
|and pick up and use whatever tools are at hand there – indeed, to do the things we cannot. |
|At the Darpa trials in Miami a few months ago, I watched one of the 16 struggling 'bots stare for 10 minutes at a door handle,|
|apparently uncertain what to do with it. The machine looked capable enough: two arms, two legs, about six feet tall, a head |
|studded with sensors. But it was definitely lacking in the brains department. Still, the program manager at Darpa in charge of|
|the operation imagines future versions serving as in-home aides for the elderly or disabled. The robots are in the primitive, |
|baby-step stages right now, but things can move quickly when it comes to Darpa robotics programs. |
|Autonomous vehicles, for example, went from being unable to complete a course through open desert in the Darpa Grand |
|Challenge, to deftly navigating simulated city streets – complete with human-driven traffic – in three short years. Three US |
|states and the District of Columbia have already passed legislation regulating robotic cars on public roads. |
|Sooner or later, it seems, robots will have staged a takeover not only of our workplaces, and streets, but also of our homes. |
|What then? |
|As early as the 1960s, Arthur C Clarke, professional visionary and inventor of the communications satellite, predicted the end|
|of menial labor (mental as well as manual), due to mechanization (and, more disturbingly, bio-engineered apes). In his essay |
|The World of 2001, originally published in Vogue and reprinted in his book The View from Serendip, Clarke wrote: "the main |
|result of all these developments will be to eliminate 99 percent of human activity … if we look at humanity as it is |
|constituted today." |
|Our salvation, in Clarke's view, will lie in our looking toward loftier pursuits than all those kinds of jobs that machines |
|will take over: |
|In the day-after-tomorrow society there will be no place for anyone as ignorant as the average mid-twentieth-century college |
|graduate. If it seems an impossible goal to bring the whole population of the planet up to superuniversity levels, remember |
|that a few centuries ago it would have seemed equally unthinkable that everybody would be able to read. Today we have to set |
|our sights much higher, and it is not unrealistic to do so. |
|Of course this depends on our valuing, as a society, individual knowledge, creating thinking, curiosity and all the other |
|things that elevate us above the level of machines. It depends on our fostering the kind of society that not only frees people|
|from menial labor, but also enables them to reach their full human potential – not just go begging for want of a lousy job. |
|How many ways can a cook contribute to society other than flipping burgers? What can a sportswriter do beyond coming up with |
|endless variations on "beat," topped", "outshot" and "defeated"? It's about time to find out. |
1 View of The Economist
“The productivity gains from future automation will be real, even if they mostly accrue to the owners of the machines. Some will be spent on goods and services—golf instructors, household help and so on—and most of the rest invested in firms that are seeking to expand and presumably hire more labour. Though inequality could soar in such a world, unemployment would not necessarily spike.”
[pic]
2 Job polarisation
|Is Job Polarization Holding Back the Labor Market? |
|Stefania Albanesi, Victoria Gregory, Christina Patterson, and Ayşegül Şahin |
|As the chart below shows, the share of routine jobs has been steadily decreasing for the cognitive and manual categories since|
|the 1980s, and the decline accelerated during the 1981-82 and 2007-09 recessions. Most of the rise in the employment share of |
|nonroutine jobs reflects the increase in cognitive nonroutine occupations. |
| |
|[pic] |
|Soon, all that will be left for human beings will be the non-routine, creative work. How many of our occupations will our |
|software overlords steal away from us? Many more than today, according to Carl Benedict Frey and Michael A. Osborne, two |
|researchers at Oxford who looked at 702 current occupations. |
|"Soon, all that will be left for human beings will be the non-routine, creative work." |
|The researchers found that approximately half of current occupations (47 percent) are at risk of going the way of the |
|telephone operator within just a decade or two. These two researchers relied on the same matrix of work as the Federal Reserve|
|team, and examined how quickly robotic dexterity and A.I. cognition would hollow out jobs that seem to be the preserve of |
|humans today: |
|Our findings could be interpreted as two waves of computerisation, separated by a "technological plateau". In the first wave, |
|we find that most workers in transportation and logistics occupations, together with the bulk of office and administrative |
|support workers, and labour in production occupations, are likely to be substituted by computer capital. |
|Note that the "transportation and logistics" sector includes many occupations that will be slammed by autonomous vehicles, |
|like truckers (the number one occupation for men in the U.S. currently), taxi drivers and warehouse workers. Administrative |
|support is the number one job for women in the US, so our robot overlords are equal opportunity, at least. |
|Frey and Osborne suggest that the second future wave of displacement will come at some later date, when A.I. gains the secrets|
|of creativity and social intelligence. That may take a longer time, but at some future date, lawyers, engineers, brain |
|surgeons and even actors might be displaced by 'bots. In fact, one venture capital firm, Deep Knowledge Ventures, has |
|already appointed an algorithm to its board of directors. |
|"Lawyers, engineers, brain surgeons and even actors might be displaced by 'bots." |
|So, we are confronted with the critical question of 2025, as I stated in the recent Pew Internet report, AI, Robotics, and the|
|Future of Jobs: |
|What are people for in a world that does not need their labor, and where only a minority are needed to guide the 'bot-based |
|economy? |
|[Source] |
3 Derived demand for resources and labour
“Machines … guzzle oil and require spare parts just like any other creature. Machines *do* consume goods and materials – creating consumer demand and stimulating the economy.” [Source]
|Robert Atkinson |
|Brynjolfsson and McAfee mistakenly consider only first order effects of automation where a machine replaces a worker. However,|
|there are also second order effects that must be considered when evaluating the true impact of technology on jobs. Consider an|
|organization that implements automation leading to cost reductions. Those dollars flow back into to the economy either through|
|lower prices, higher wages for remaining workers, or higher profits, which in turn stimulates demand that leads to employment |
|increases in other sectors. And for anyone who says that people wouldn’t be able to find things to spend their money on, just |
|go to a shopping mall and give the average shopper $25,000. They will clearly find lots of things to spend it on. |
|It should also be pointed out that virtually all economic studies analysing the relationship between productivity and jobs |
|found either no impacts or positive impacts on total jobs in the moderate term. As the OECD has stated: |
|Historically, the income-generating effects of new technologies have proved more powerful than the labor-displacing effects: |
|technological progress has been accompanied not only by higher output and productivity, but also by higher overall employment.|
|But wait, isn’t it different this time? Just look at all the new cool technologies ready to take away our jobs: driverless |
|cars, artificial intelligence, and of course, robots |
|But this time is actually not different. New innovations being introduced will largely boost productivity in information-based|
|functions or routinized functions, but not jobs that involve interacting with people (e.g., nursing homes, police and fire) or|
|doing non-routine physical tasks (e.g., construction or janitorial services). In addition, new technological growth will |
|create new industries and business models that will promote economic and job growth across the board. |
|The reality is that, far from being doomed by an excess of technology, we are actually at risk of being held back from too |
|little innovation. [Robert Atkinson |
4 Many new jobs created by technology
In order to make those robots work, companies need people for programming, maintenance and repair. [Source]
“We are gifted with the vision of our times and cursed with the temptation to extrapolate that vision into the future. How could our farmer know that in 2013 humans would be paid to make movies, pick up garbage, write online, build robots, clean bathrooms, engineer rockets, lead guided tours, drive trucks, play in garage bands, brew artisanal beer, or write code?” [Source]
Automation entails huge upfront investments. Companies that invest in automation have to build organizations to ensure steady supplies of high-quality materials, improve and maintain machinery, and capture sufficiently large market shares to achieve economies of scale. These investments in the development and utilization of automated facilities create lots of high-value-added jobs, especially for companies that, because of their investments, can grow large by producing higher quality, lower cost products than the competition. [Source]
1 Kinds of new jobs created
computer designers, builders, maintenance people, application designers, improvers. Note that these are almost all high tech.
A GUARANTEED JOB AWAITS: "The shortage of people who know how to build, program, maintain, and repair robots has gotten so severe that, in some parts of the country, qualified candidates can practically write their own ticket." [Source]
Technology , when unleashed in a competitive market, has always unleashed new jobs, industries, and professions. Examples of new jobs include those created by technology companies e.g. google, etc.
"job creation in the future will “center on three kinds of work: solving unstructured problems [example: performing delicate surgery], working with new information [example: analyzing marketing data] and carrying out non-routine manual tasks [example: moving furniture].”" [Source] And of course, more computer/robot infrastructure related jobs.
2 Number of new jobs created
“They count 3.5 million workers directly involved “in creating computer infrastructure” — software developers, systems analysts and data experts.” [Source]
There is apparently a “job-creation ratio of 3.6 jobs for every robot deployed” [Source]
3 Industrial robotics has created 350,000 new jobs
|Do industrial robots really have a positive impact on employment? Of course they do and there are over 50 years of data |
|proving that to be the case. |
|There are at least 350,000 people directly employed by and in the industrial robotics industry. There are ancillary providers |
|of components, software and other services for robots and installations but these jobs are hard to quantify. |
|[Source] |
[pic]
[Source]
5 But job creation slower than job loss
|We are being afflicted with a new disease of which some readers may not yet have heard the name, but of which they will hear a|
|great deal in the years to come - namely, technological unemployment. This means unemployment due to our discovery of means of|
|economising the use of labour outrunning the pace at which we can find new uses for labour. |
|- John Maynard Keynes, 1930 |
However, there is considerable evidence that jobs aren’t keeping pace.
[pic]
Source:
It can be argued that much of this is due to bad US policy:
|In the last three decades the government has pursued policies that have the effect of redistributing income upward so that the|
|gains from growth are not broadly shared. These policies include a high dollar policy that makes U.S. manufacturing goods less|
|competitive domestically and internationally, a policy of selective protectionism that largely protects the most highly |
|educated professionals (e.g. doctors and lawyers) from foreign competition, and a policy of shifting tens of billions of |
|dollars each year to Wall Street banks through "too big to fail" insurance provided at zero cost by the government. |
|If this new generation of robots ends up making large segments of the population worse off, it will be the result of |
|deliberate policies. It is not the fault of the robots. [Source] |
The giant leap in unemployment numbers dates from a very specific event, not from a long-run process that has been displacing workers over time. In 2007, the unemployment rate was 4.6. By 2009, it was 9.6, and remains very high. What happened wasn’t a sudden rush of robots onto the scene, but a financial catastrophe that nearly tanked the global economy. [Source]
6 Part time jobs
This is, in the short term, an empirical question. What's the pace of the loss of human jobs vs. the creation of new ones. That labour force participation is decreasing (beyond the baby boomer retirement levels) and educated youth aren't finding jobs suggests businesses are desperately automating in order to survive in this ultra-competitive marketplace. At a minimum I envisage a very significant increase in the share of part-time employment in the short run.
7 More low-paying jobs will be created
As technology rewards the very highly educated and replaces the middle class, there is an inevitable trend towards more lower-paid jobs in the services sector - that are currently too difficult to be replaced by robots.
This implies an inevitable increase in inequality. Even the poorest will have all amenities and I-phones, but they'll earn proportionately less than before.
|The US Bureau of Labor Statistics estimates that among the most rapidly growing occupational categories over the next ten |
|years will be “healthcare support occupations” (nursing aides, orderlies, and attendants) and “food preparation and serving |
|workers” – that is, overwhelmingly low-wage jobs |
|[pic] |
|In short, ICT creates an economy that is both “hi-tech” and “hi-touch” – a world of robots and apps, but also of fashion, |
|design, land, and face-to-face services. This economy is the result of our remarkable ability to solve the problem of |
|production and automate away the need for continual labor. [Source] |
8 Kinds of jobs that are in the process of going
|“Invisible” robots, such as Aethon’s Tugs, look like more pernicious job eaters, ready to take over much of the work that |
|hospital porters do today. Mr Thrun offers Kiva’s warehouse robots as an example of a similar labour-replacing system. And |
|software will take over a lot of the tasks carried out by humans sitting in front of screens. In a recent study of the |
|susceptibility of jobs to computerisation carried out by Carl Benedikt Frey and Michael Osborne at Oxford University, many of |
|the job categories at greatest risk involved hardly any manual labour at all. |
|Given the doornail dumbness of machines, how can they take over so many moderately skilled jobs? One of the answers is that if|
|you have enough doornails and enough data, there are ways of simulating smartness that are proving good enough to solve an |
|ever greater range of problems, and that problems restricted to the world of data are much more tractable than those that |
|require manipulating things in the real world. |
|Andrew Ng of Stanford is a pioneer and advocate of this sort of “machine learning”, a product of the trends towards ever |
|cheaper computing power and ever more widespread digitisation that Mr Brynjolfsson and Mr McAfee describe. Working with |
|Google, Mr Ng came up with a system that, using 16,000 processors to look at a significant fraction of a video on YouTube, |
|came to “recognise” cats with no prior knowledge that there was such a thing. Google uses related approaches to tackle a |
|number of more practical problems, such as machine translation and voice recognition. It would be surprising if it did not |
|apply the same sort of thinking to its new acquisitions in robotics, whether they are used in manufacturing, in services or |
|for that matter in agriculture or construction. |
|Managing changing tasks in a changing world means that many workplaces will still need humans, but as workplaces become more |
|efficient the number of people employed will shrink in the long run. William Nordhaus, a Yale economist, has shown that even |
|though the world has become much better lit in an ever-widening variety of ways over the past few centuries, the number of |
|people who provide the ever better lighting has declined. There is, in the end, only so much light that people can consume. |
|Many other human needs, too, can probably be satisfied with less labour in the future, though that will take time. [Source] |
“Peter Diamandis said robots will also be responsible for the loss of 50 percent of the jobs in the service sector in 10 years as they will compete with imported labor sources as the cost of labor will drop to just the cost of power.” [Source]
9 Jobs which have gone
technology is someday likely to advance to the point where the majority of the routine jobs held by average workers will be automated. That is a lot of jobs—probably most jobs. Two thirds of our population does not have a college degree, and even many college graduates have jobs that can be broken down into relatively routine tasks that will be susceptible to software automation algorithms and expert systems. This is something that I think could potentially happen in the next couple of decades. [Source]
[pic][Source]
1 Library
Self-check out
Reference librarians: Want to be productive? Forget the library. Use google scholar/electronic databases "In a recent study, Google found students who used its search function answered questions three times quicker than those who used the library."
North Carolina State University this month introduced a high-tech library where robots — "bookBots" — retrieve books when students request them, instead of humans. The library's 1.5 million books are no longer displayed on shelves; they're kept in 18,000 metal bins that require one-ninth the space. [Source]
2 Stevedores
Stevedores replaced. This, again, is just the beginning. Only 2013 now.
[pic]
3 Mining truck drivers
[pic]
4 Iphone workers
1 million robots installed:
5 Warehousing workers
See:
Amazon has purchased Kiva systems.
“A warehouse equipped with Kiva robots can handle up to four times as many orders as a similar unautomated warehouse, where workers might spend as much as 70 percent of their time walking about to retrieve goods. (Coincidentally or not, Amazon bought Kiva soon after a press report revealed that workers at one of the retailer’s giant warehouses often walked more than 10 miles a day.). While the robots are the company’s poster boys, its lesser-known innovations lie in the complex algorithms that guide the robots’ movements and determine where in the warehouse products are stored. These algorithms help make the system adaptable. It can learn, for example, that a certain product is seldom ordered, so it should be stored in a remote area.
” [Source]
6 Banks
ATM machines replaced the tellers.
7 McDonald’s cashiers
7000 cashiers replaced:
8 Telephone directory assistance
Automated, and/or through the internet.
9 Datacentre IT staff
IT trends of eliminating IT datacenters and consolidating on the cloud.
10 Jobs which are next in line
Note that computers haven’t really become “intelligent”.
1 Overall analysis
Middle tier jobs (bank teller, airport check-in clerk, travel agent, call centre (through Voice technology)) have been the fastest to go. "Gardener, hairdresser, or home health aide" have been relatively safe jobs, so far. Of course, these jobs pay virtually nothing.
|It can be easier to automate the work of a bookkeeper, bank teller, or semi-skilled factory worker than a gardener, |
|hairdresser, or home health aide. In particular, over the past 25 years, physical activities that require a degree of physical|
|coordination and sensory perception have proven more resistant to automation than basic information processing, a phenomenon |
|known as Moravec’s Paradox’. For instance, many types of clerical work have been automated, and millions of people interact |
|with robot bank tellers and airport ticket agents each day. More recently, call center work - which was widely offshored to |
|India, the Philippines, or other low-wage nations in the 1990s - has increasingly been replaced by automated voice response |
|systems that can recognize an increasingly large domain-specific vocabulary and even complete sentences. [Race Against the |
|Machine] |
|As Singer points out, the order in which jobs are automated respective to one another may be quite surprising (Singer 2009, |
|pp. 130–132). For instance, he suspects that human hairdressers may stay with us for awhile because of their respective skill |
|set, including the ability to put customers at ease (Singer 2009, p. 131). [Source: Robots and the changing workforce, Jason |
|Borenstein , AI & Soc (2011) 26:87–93 |
2 Administration/bureaucrats
We can expect automation of administration and won’t need too much middle management in the future.
3 Call centres and helpdesk
|"US firm IPsoft has recently established an Australian office to sell automation software that allows robots to replace humans|
|in Level 0 and Level 1 tech support roles such as helpdesk. It already supplies virtual workers for companies such as Pfizer |
|and Autodesk, and claims to have addressed more than 17 billion customer ‘‘incidents’’ without human intervention. The company|
|recently struck a deal with Indian outsourcing giant Infosys to sell more virtual IT engineers to answer queries such as when |
|computer users need to have their passwords changed by their company’s helpdesk." [Source] |
4 Lawyers
Not long ago I had thought that legal outsourcing to India may grow, possibly in the area of legal discovery. But machines now do that MUCH cheaper:
|A March 2011 story by John Markoff in the New York Times highlighted how heavily computers’ pattern recognition abilities are |
|already being exploited by the legal industry where, according to one estimate, moving from human to digital labor during the |
|discovery process could let one lawyer do the work of 500. In January, for example, Blackstone Discovery of Palo Alto, Calif.,|
|helped analyze 1.5 million documents for less than $100,000. ‘From a legal staffing viewpoint, it means that a lot of people |
|who used to be allocated to conduct document review are no longer able to be billed out,’ said Bill Herr, who as a lawyer at a|
|major chemical company used to muster auditoriums of lawyers to read documents for weeks on end. ‘People get bored, people get|
|headaches. Computers don’t.’ [Source: Race Against the Machine] |
5 Retail
Self service checkouts, laser bar code scanners for ringing up sales, robotic DVD stores (Redbox.), streaming music, video, software. ‘Face to face interaction in retail is largely disappearing. RFID for inventory and order management as well as returns processing, automated warehouses, better inventory control management systems have all reduced the headcount needed for a retail operation [see commentators here]
|And an article the same month in the Los Angeles Times by Alena Semuels highlighted that despite the fact that closing a sale |
|often requires complex communication, the retail industry has been automating rapidly. |
|In an industry that employs nearly 1 in 10 Americans and has long been a reliable job generator, companies increasingly are |
|looking to peddle more products with fewer employees. - Virtual assistants are taking the place of customer service |
|representatives. Kiosks and self-service machines are reducing the need for checkout clerks. |
|Vending machines now sell iPods, bathing suits, gold coins, sunglasses and razors; some will even dispense prescription drugs |
|and medical marijuana to consumers willing to submit to a fingerprint scan. And shoppers are finding information on touch |
|screen kiosks, rather than talking to attendants. |
|The [machines] cost a fraction of brick-and-mortar stores. They also reflect changing consumer buying habits. Online shopping |
|has made Americans comfortable with the idea of buying all manner of products without the help of a salesman or clerk. [Race |
|against the machine] |
6 Butchers (abattoirs)
This is a very dangerous job. There is no doubt that abattoirs will soon get robotised.
7 Doctors
(GPs/surgeons)
Diagnostic devices (hand-held – which do a number of tests) will soon be there that can diagnose most of our problems BETTER than doctors can.
at 12 minutes
Watson is already getting better than doctors in SOME cases. Expect it to outsmart doctors in ALL cases in a few years now. Goodbye pathetic GPs! Welcome lifesaving AI and robots.
"I've had a couple of patients where Watson found things that I had missed," says Dr. Neil Mehta, the staff physician who's leading the Cleveland Clinic's end of the Watson project. "It doesn't work every time, but it's getting better." One example is a patient suffering from sleep apnea-like symptoms. Years earlier, this patient had a blood gas test that would have confirmed the diagnosis, but the test results were hidden in a hard-to-find section of the medical record. Without Watson, Mehta says he never would have seen the result.” [Source]
HUMAN DOCTORS MISS 50 PER CENT OF CANCERS. WATSON ONLY MISSES 10 PER CENT.
"It would take at least 160 hours of reading a week just to keep up with new medical knowledge as it's published, let alone consider its relevance or apply it practically. Watson's ability to absorb this information faster than any human should, in theory, fix a flaw in the current healthcare model. Wellpoint's Samuel Nessbaum has claimed that, in tests, Watson's successful diagnosis rate for lung cancer is 90 percent, compared to 50 percent for human doctors." [Source]
Artificial intelligence, however, needs close shepherding since even the smartest computer is still only at the level of a pre-schooler:
“In the new study, researchers decided to test out just how close tohuman intelligence AI has come. They administered the verbal portions of a standard IQ test called the Wechsler Preschool and Primary Scale of Intelligence Test to ConceptNet4.
The machine's score was similar to that of a 4-year-old child. But this was no ordinary child: its intelligence was all over the map. The program scored highly on the vocabulary and similarity portions of the test, but floundered on comprehension sections, which are heavy on the "why" questions.
"If a child had scores that varied this much, it might be a symptom that something was wrong," Sloan said in a statement. [Source]
8 Receptionists
In another 20 years expect most office receptionists to be replaced.
)
9 Call centres
The end of Indian call centres is nigh. "Eliza has replaced India’s Tata Consulting Services." [Source]
Also see this:
If India can't produce ANYTHING that others buy, if India can't sell ANY SERVICE that others want, if India has no RAW MATERIAL that others need, and if India refuses to improve governance/policy systems then the ONLY resource India will have to offer is its most talented brains - which the West will quickly snap up (or which may still be used through Infosys etc.), further impoverishing India.
Watson will displace a very significant proportion of Indian call centres:
"as many as 61 percent of all telephone support calls currently fail because human support-center employees are unable to give people correct or complete information
Watson, I.B.M. says, will be used to help human operators, but the system can also be used in a “self-service” mode, in which customers can interact directly with the program by typing questions in a Web browser or by speaking to a speech recognition program." [Source]
But many may remain since computers haven’t really become “intelligent”.
10 Pharmacies
Pharmacies will feature a single pill-dispensing robot in the back while the pharmacists focus on patient consulting. [Source]
11 Fruit harvesters
Fruit harvester jobs are on the line.
and
Fruit and vegetable picking will continue to be robotized until no humans pick outside of specialty farms. [Source]
12 Dusting crops with pesticides
“In Japan drones dust crops” [Source]
13 Cleaners
the more dexterous chores of cleaning in offices and schools will be taken over by late-night robots, starting with easy-to-do floors and windows and eventually getting to toilets. [Source]
14 Package delivery
By drones. “A Palo Alto, Calif., start-up called Matternet wants to establish a network of drones that will transport small, urgent packages, like those for medicine.” [Source]
15 Security guards
Through satellites, remote cameras and drones, much security work can be centralised.
16 Assembly/packaging workers
Most assembly/packaging workers’ jobs are likely to go pretty soon, in the next 5 years at most:
Speedy bots able to lift 150 pounds all day long will retrieve boxes, sort them, and load them onto trucks. [Source]
17 Farmers
Farmers
[Intelligent machines are already in place]
18 Dairy farmers (robotic dairy)
See:
19 Pilots
"Even the F-35's champions concede that it will probably be the last manned strike fighter aircraft the West will build." Thousands of pilots almost certain to lose their jobs (this would also include passenger planes in the longer run).
20 Financial services and financial market traders
Robotic traders are now actively used. ‘Financial services have become a greater share of GDP for post-reality economies. Much of it is automated, conducted by robots’ (a commentator here).
If you are a great treader, you can convert your insights into a program which can then automatically buy and sell.
[See: ]
“Think high-speed trading on Wall Street. The lightning-quick trades account for most of the volume on the major stock exchanges, yet the action is driven by computers and software communicating with other computers and software, supervised and monitored by at most a relative handful of highly compensated workers. (As a Wharton School report put it, “In the time it takes to read this sentence, tens of thousands of high-speed, computer-automated transactions can occur.”)” [Source]
21 Construction industry
From 11 minutes you see why construction industry will soon be revolutionised with flying robots that build massive skyscrapers.
Full fledged major robots are not being designed to build entire homes – much stronger than normal homes – without any labour.
22 Drummers/ musicians
Robotic bands are now actively playing bands (jointly with humans). The first
Flying robots playing James Bond music. Again, something to be seen to be believed.
23 Age carers (Social Assistive Robots)
Social Assistive Robots are rapidly coming:
See this.
24 Housemaids
Need a housemaid/helper? This is getting close, but another 20 years and they'll be super-functional. End of the endless arguments with the maid who never comes in time.
25 Ship repairers (underwater)
Robots are now being created to do this job.
26 Waste disposal
Automatic sorting/processing is likely to become more common.
27 Truck drivers
The highway legs of long-haul trucking routes will be driven by robots embedded in truck cabs. [Source]
It would be harsh to generalise, but I, for one, would be glad to be rid of truck drivers - who are often extremely rash, and after damaging property, deny liability – putting the common citizen in great risk.
28 Taxi drivers
In fact, it would be good if taxi drivers were replaced with self-driven cars, given the terrible reputation they’ve developed.
29 Astronauts
11 Jobs which are mostly safe
Although a number of other jobs will make use of IT in some way, they will use it largely in an assisting role, with smaller direct displacement.
“Problem is, home health care is an occupation that has one of the highest concentrations of low-paid jobs set to grow by 2020, according to calculations by the Economic Policy Institute. At least 45 percent of all employees working in farming, personal care, building and grounds maintenance, and health-care support earn at or below poverty wages. These jobs often come without retirement and health-care benefits.” [Source]
Jobs that deal with unstructured environments are likely to remain: “people are still far better at dealing with changes in their environment and reacting to unexpected events. “People and robots working together can happen much more quickly than robots simply replacing humans,” he [John Leonard, a professor of engineering at MIT and a member of its Computer Science and Artificial Intelligence Laboratory (CSAIL)] says. “That’s not going to happen in my lifetime at a massive scale. The semiautonomous taxi will still have a driver.” [Source]
1 IT related
I'd strongly recommend that young people start taking Coursera courses in AI or any other technology that interests them.
2 Plumbers
3 Electricians
4 Construction industry workers
5 Hairdressers
6 Gardeners
7 Old age carers and nurses
8 Key government agencies (police, justice, defence)
9 Comedians
If you are a really good artist/comedian/singer, you too will do well.
10 The flourishing of creativity
The Robotic Age will be the age of creativity. With routine jobs out of the way, people will be rewarded for creativity.
The rich will have plenty of time to pay for entertainment by live artists and to go to art galleries and music shows. This will be the main growth industry.
No matter how good computers get at art, there are things that are uniquely human – related to spirituality and consciousness, which cannot be replicated by computers (nor is there any need for them to do so).
In this talk , Michio Kaku explains the kind of creativity that will succeed.
1 Creative artists, writers and entertainers
2 Exercise and fitness trainers
3 Interior designers
4 Yoga teachers
5 Spiritual gurus
6 Psychologists and social workers
11 The challenge for unskilled youth
The solution, in my tentative opinion, is going to be in the services sector in areas where computers/IT/robotics will take longer to penetrate. That will require SOFT SKILLS among the less qualified youth, an ability to relate to others, to care for others. They will have to make themselves useful to others, not just mechanically capable of operating machines (for such jobs will no longer exist).
With the ageing population caring skills will be in great demand. But only good carers will be in demand. Some carers will turn out to be criminals or otherwise disinterested in care and we wouldn't want them inside our homes. If bad incidents occur, people will switch to robots even in this area. Japan has already started using robots for this purpose. Bad carers can, however, get jobs in other fields such as gardening, restaurants, or creative industries.
12 Effect on wages
There will be jobs in the future. Both high paying and low paying ones. It is likely that the ones in the middle will go.
“Problem is, home health care is an occupation that has one of the highest concentrations of low-paid jobs set to grow by 2020, according to calculations by the Economic Policy Institute. At least 45 percent of all employees working in farming, personal care, building and grounds maintenance, and health-care support earn at or below poverty wages. These jobs often come without retirement and health-care benefits. “[Source]
1 Fact: Relative share of wages in GDP decline
"Over the past 40 years, weekly wages for those with a high school degree have fallen and wages for those with a high school degree and some college have stagnated. On the other hand, college-educated workers have seen significant gains, with the biggest gains going to those who have completed graduate training". What chance do most Indians - without world class college education - have in tomorrow's world economy? [Race Against the Machine]
"The link between higher productivity and people’s wages and salaries was severed—the income of the top 1 percent nearly quadrupled from 1979 to 2007, while the typical family’s barely budged." [Obama in a speech on 24 July 2013]
[pic]
Source:
2 Hypothesis: Not technology but globalisation
|The ILO looks at a larger set of explaining variables (including ‘financialisation’) than these authors do and finds: |
|“We have found that globalisation, i.e. increased international trade, has negative effects on the wage share in advanced as |
|well as in developing economies, which is in contradiction to the Stolper-Samuelson Theorem. Overall, the results are similar |
|for advanced and developing economies, with the possible exception of low-income countries. Financialisation has had the |
|largest negative effect on wage shares. Technological progress (including structural change) has had substantial effects on |
|the wage share, but these have been positive since 1980 and can therefore not explain the decline in the wage share. |
|Globalisation and welfare state retrenchment have had moderate negative effects on the wage share.” |
| |
|Source. |
3 Hypothesis: Permanently reduced wages
4 Hypothesis: wages may not fall
wages may not really fall:
13 Effect on employment
1 The less educated have less of a chance of finding jobs now
Source:
[pic]
2 Lower labour participation
Very significant drop off in participation rate in USA since 2000. Although 2/3rd is due to demographic factors, 1/3rd is related to technology: "many unemployed construction and manufacturing workers have struggled to find work in growing fields, such as technology and health care, and it's not clear if or when they will, Lavorgna says."
Note: Australian participation rate is still climbing.
3 Employment may not fall in the long run
Here is a much more positive perspective. [This]
I'm not sure about the Australian experience that has been cited, though.
1) Even in Australia, the median income has stagnated. If nothing else, inequality is significantly increasing.
2) OECD has recently said: "The non-jobseeker population (in Australia) on unemployment benefit is so large that it needs more analysis and attention." []
1 There could be short run pain
|TYLER COWEN |
|Despite the grim forecast, Tyler Cowen argues that western societies won’t collapse under the weight of future industrial |
|change, but will eventually adjust to a new phase of ubiquitous automation—the period Brynjolfsson calls the ‘Second Machine |
|Age’. However, he warns that evolution will take considerable time to play out. |
|‘If you look at the Industrial Revolution that starts in England say around 1780 and for a long time a lot of jobs do go away,|
|wage gains are very slow, there’s a lot of volatility, it’s not really until the 1840s that real wages in England are going up|
|significantly,’ he says. ‘So I think this time around it will actually be a lot like the last time. We will have a transition |
|period of many decades. That will be tough for many people. In the very long run it will be splendid, but along the way it’s |
|not always going to feel splendid. I think that is the historical pattern for a lot of these changes.’ [Source] |
2 Hours worked by everyone may fall
|If technology reduces demand for labor by a quarter, that might translate into everyone working 25 percent less rather than |
|unemployment rising by one-fourth. The late economic historian Robert Fogel predicted that the increase in leisure between |
|1995 and 2040 would exceed the gain Americans saw in the 115 years before 1995. [Source] |
14 Increased inequality
See Chrystia Freeland here. Top 0.1 per cent of USA owns 8 per cent of GDP. A mere 2 people in USA own more wealth than 120 million people at the bottom 40 per cent in USA. Facebook with $100 billion in capitalisation, has less than 10,000 employees.
This is only the beginning. IT and Robotics are radically re-writing income distribution rules across the world. I disagree with Freeland that the only jobs left for others will be to massage the top 1 per cent. The fields of education and health will blossom as they have never done before. Imagine the HUNDREDS OF MILLIONS in India waiting for good education to reach them. This is the time to focus on services.
There has been a steadily increasing treand in inequality over the past century:
|“I percent of the population of the United States pays 28.7 percent of the income tax, suggesting that as societies advance |
|into the Information Age they will experience an even more skewed distribution of incomes and abilities. People are quite |
|accustomed to substantial inequalities of wealth. In 1828, 4 percent of New Yorkers were thought to have owned 62 percent of |
|all the city's wealth. By 1845, the top 4 percent owned about 81 percent of all corporate and noncorporate wealth in New York |
|City. More broadly, the top 10 percent of the population owned about 40 percent of the wealth across the whole United States |
|in 1860. By 1890, records suggest that the richest 12 percent then owned about 86 percent of America's wealth. |
|The Information Age has already changed the distribution of wealth, particularly in the United States, and is one of the |
|reasons for the bitterness of modem American politics, which we explore further in the next chapter. The Information Age |
|requires a quite high standard of literacy and numeracy for economic success. A massive U.S. Education Department survey, |
|"Adult Literacy in America," has shown that as many as 90 million Americans over the age of fifteen are woefully incompetent. |
|Or in the more colorful characterization of American expatriate Bill Bryson, "They are as stupid as pig dribble."' |
|Specifically, 90 million American adults were judged incapable of writing a letter, fathoming a bus schedule, or adding and |
|subtracting, even with the help of a calculator. Those who cannot make sense of an ordinary bus timetable are unlikely to be |
|able to make much of the Information Superhighway. From this third of Americans who have not prepared themselves to join the |
|electronic information world, an angry underclass is being recruited. At the top of society is a small group, perhaps 5 |
|percent, of highly educated information workers or capital owners who are the Information Age equivalent of the landed |
|aristocracy of the feudal age—with the crucial difference that the elite of the Information Age are specialists in production,|
|not specialists in violence. |
|There is no inherent reason to suppose that technology always tends to mask rather than accentuate the differences in human |
|talents and motivation. |
|Source: The Sovereign Individual: Mastering the Transition to the Information Age, by James Dale Davidson, William Rees-Mogg |
Virtually all commentators agree that in the robotic age inequality will increase:
|The income gap between the rich and everyone else has grown as middle-class manufacturing jobs have been replaced with |
|low-wage service jobs and companies have fired and cut their way to record profitability. But this is a compensation and |
|investment problem, not an employment problem: These jobs are needed, which is why they exist. For a variety of reasons, |
|however, the jobs just don’t pay as much as the heavily unionized manufacturing jobs that they replaced. [Source] |
1 Median income barely growing
This last generation was the first one in the West where the average worker did not experience real increase in income. The worker benefited from increased quality and range of products, but not higher income.
1 USA
In contrast to labor productivity, median family income has risen only slowly since the 1970s (Figure 3.2) once the effects of inflation are taken into account. As discussed in Chapter 1, Tyler Cowen and others point to this fact as evidence of economy-wide stagnation.
In some ways, Cowen understates his case. If you zoom in on the past decade and focus on working-age households, real median income has actually fallen from $60,746 to $55,821. This is the first decade to see declining median income since the figures were first compiled. Median net worth also declined this past decade when adjusted for inflation, another first. [Race against the machine]
2 Australia
(this is Australia) [Source: p.33: )
[pic]
2 Divide between rich and poor rapidly growing
The divide between the rich and poor is growing rapidly - potentially exacerbated by technological displacement. This trend will accelerate, forcing significant people to the bottom in the West. And the idea of nations like India catching up (as a whole) is now looking practically impossible. This chart is for Australia. USA trends are similar Source:
“Economist Ed Wolff found that over 100% of all the wealth increase in America between 1983 and 2009 accrued to the top 20% of households. The other four-fifths of the population saw a net decrease in wealth over nearly 30 years. [Race Against the Machine]
"The median worker is losing the race against the machine." [Race Against the Machine]- in the West. And given India's refusal to at least take SOME advantage of modern economics and technology, its fate is now sealed at the very bottom of the world's pyramid.
3 Share of corporate profits rising
“corporate profits as a share of GDP are at 50-year highs. Meanwhile, compensation to labor in all forms, including wages and benefits, is at a 50-year low”[Race Against the Machine]
15 Effect on asset values
16 Rout of the middle class
Here's a more positive paper: "It is found that automation has a significant positive impact on productivity in the short run as well as in the long run. Moreover, automation tends to reduce employment in the short run. In the long run, however, employment increases." I'm sceptical about its long run conclusion - but there is no doubt that REALLY low paying service sector jobs will INCREASE. It is the middle tier ('middle class') that will be wiped out.
“Andrew McAfee says, and many middle-class jobs are right in the bull’s-eye; even relatively high-skill work in education, medicine, and law is affected. “The middle seems to be going away,” he adds. “The top and bottom are clearly getting farther apart.” While technology might be only one factor, says McAfee, it has been an “underappreciated” one, and it is likely to become increasingly significant.” [Source]
|David Autor, an economist at MIT has extensively studied the connections between jobs and technology. At least since the |
|1980s, he says, computers have increasingly taken over such tasks as bookkeeping, clerical work, and repetitive production |
|jobs in manufacturing—all of which typically provided middle-class pay. At the same time, higher-paying jobs requiring |
|creativity and problem-solving skills, often aided by computers, have proliferated. So have low-skill jobs: demand has |
|increased for restaurant workers, janitors, home health aides, and others doing service work that is nearly impossible to |
|automate. The result, says Autor, has been a “polarization” of the workforce and a “hollowing out” of the middle |
|class—something that has been happening in numerous industrialized countries for the last several decades. But “that is very |
|different from saying technology is affecting the total number of jobs,” he adds. “Jobs can change a lot without there being |
|huge changes in employment rates.” [Source] |
17 Education is the FOUNDATION of robotics/IT revolution
Michio Kaku is very concerned about the lack of good education in USA. H1-B visa
(from 45 minutes)
We need more physicsts and engineers.
18 Reduced traffic congestion
|With driverless half cars (gyroscopic), traffic will also fall dramatically as you don't own any car but rent on demand. The |
|car drives up and then goes and does something useful. 95 per cent of the time most of the world's cars are FALLOW. What a |
|brilliant man is this! Peter Diamandis. [see |
|] |
19 Changing government services
|Eight Trends Driving the Transformation of Government Services |
|Automation of Services |
|A variety of government services, from traffic violations to building inspections, could become automated through the use of |
|embedded sensors and intelligent, integrated networks. |
|In addition to increased efficiency, automation will allow governments to provide personalized services at a level of quality |
|previously reserved for private luxury. Machine learning, data mining and predictive software will enable the creation of |
|virtual civil servants, who can perform many aspects of today’s government jobs. |
|This trend will alleviate the vast majority of standardized tasks, leaving civil servants with more time to focus on the needs|
|of individual citizens. |
|Mobile & Wearable Computing |
|In the next decade the number of mobile smart devices will increase exponentially: smart wallets, activity sensors, and |
|wearable devices such as augmented reality glasses or contact lenses will integrate seamlessly with their environment. New |
|forms of wearable computers, such as today’s Google Glass, will allow people to directly experience digital worlds as part of |
|their day-to-day physical activities. Mobile and wearable computing will enable new forms of complex interaction that create |
|exciting opportunities in a range of services. |
|Machine Learning |
|Machine learning will enable computers to go beyond executing simple tasks and into new realms of pattern matching, learning |
|and meaning-detection. These systems will learn to adapt to human behavior and provide services that work intuitively and |
|effectively for their users. Machine learning will also provide decision-support for professionals in various domains, from |
|medicine to organizational strategy. |
|Simulation, Visualization, and Gaming |
|Complex interactive simulations will enable new forms of deliberation, exploration and learning in a range of fields. |
|Citizens, and civil servants, for example, will be able to test outcomes of policy decisions and possible scenarios before |
|they occur, often within a fun and realistic gaming environment. Advanced visualizations will enable us to find insight in the|
|oceans of data that we create. |
|Right Time / Right Place Assistance |
|Powerful analytic tools will become available to citizens and service providers, combining outputs from multiple data services|
|such as the next generation of Google search, IBM’s Watson, or Wolfram’s Alpha. This will result in a predictive layer of |
|services derived from observed habits, data correlation and advanced predictive pattern matching. Although they won’t always |
|understand how or why, tomorrow’s citizens will be delighted by how services appear to meet their every need… often before |
|they are aware they even need them. |
|Technologies of Coordination |
|Digital platforms for the coordination of activities will expand rapidly, creating new opportunities for reimagined service |
|delivery. Crowd sourced services such as Mechanical Turk or oDesk, for example, will enable complex work to be broken down |
|into smaller tasks and completed by a web of experts at any time and in any place. |
|Intelligent Infrastructure |
|A carpet of networked sensors will cover our built environment, enabling new levels of automation and responsiveness. |
|Planners, and officials will be able to ‘read’ this data to fine tune smart systems, ranging from reduced traffic and to more |
|efficient energy use. The implementation of self-driving cars and delivery drones are another powerful example. |
|Personalization |
|Data analytics and smart interfaces will create capacity for highly personalized customer services. This will allow |
|governments to serve individual citizens far more accurately and effective than ever before. [Source] |
Social (and political/legal) consequences
1 Will liberate women
As they can work from home, the role of women in the economy will change.
2 Ethics of robotics
|The wait for a fully-functional robotic nurse is not just because the hardware, software and artificial intelligence need |
|work. Scientists also need to figure out the best methods for safely using them. |
|"Delivering machines is not just a question of buying robots, even if in the future they become cheap. There are many ethical |
|issues," said Espingardeiro. |
|Currently Espingardeiro and others are researching the advantages and disadvantages of robots over human caretakers. They are |
|also looking into the potentially troubling implications of a patient developing an emotional connection to a robot. |
|"This is a very vulnerable group, very frail," said Espingardeiro. "What happens if they get attached to these machines?" |
|[Source] |
1 Isaac Asimov's "Three Laws of Robotics"
A robot may not injure a human being or, through inaction, allow a human being to come to harm.
A robot must obey orders given it by human beings except where such orders would conflict with the First Law.
A robot must protect its own existence as long as such protection does not conflict with the First or Second Law.
2 Will robots take over the world?
James Barrat, in a book, Our Final Invention: Artificial Intelligence and the End of the Human Era, has expressed concern that if AI really becomes super-intelligent, it could take over mankind. [A review here]
I many ways, this discussion is premature, and can be (or should be) parked till at least a modicum of REAL intelligence is achieved by robots.
3 Humans shouldn’t be doing such jobs anyway
|Here's what Kelly has to say about robots stealing our jobs: |
|The fact that a task is routine enough to be measured suggests that it is routine enough to go to the robots. In my opinion, |
|many of the jobs that are being fought over by unions today are jobs that will be outlawed within several generations as |
|inhumane. |
|If a job is so routine that it could be done by robots - usually robots that can't really think but are really good at doing |
|mechanical tasks over and over - will it be seen as "inhumane" by future generations? [Source] |
3 Regulatory impact/ regulation of robots
And the Nevada state legislature directed its Department of Motor Vehicles to come up with regulations covering autonomous vehicles on the state’s roads. [Race against the machine]
Japan is working on robot regulation – to ensure that robots behave appropriately.
This video contains a panel discussion on robot soldiers and killer robots, and highlights the importance of appropriate regulatory frameworks: (killer robots – the future of war)
1 Privacy issues
This will need serious regulatory work in the coming decades.
This is an eye-opening (although long but entirely worthwhile) video.
In casinos there is total surveillance:
And of course in Disneyland, etc.
Basically there is now NO way we can prevent TOTAL SURVEILLANCE by corporations and governments of our existence. It is already happening, and will only increase.
This creates a fundamental threat to human dignity and liberty - two key principles of democracy. There has been a systematic attack on these two principles over the past decade because even the USA doesn't have any legal framework to protect individual ownership of data about them. Privacy laws are totally ineffectual (and indeed, arguably unnecessary).
The ONLY way our privacy can ultimately be protected is if we own ALL data about ourselves. That means if anyone wishes to use individualised data for a commercial use he/she must pay for it - unless it is a government investigation authorised by a court.
I believe appropriate regulation needs to be created to make information about each individual a property right. If the Robotic Economy doesn't evolve such ownership rights, then we are headed for a state much worse than the Orwellian 1984 where not just privacy would have gone, even freedom and dignity would no longer exist as a concept.
In the age of increasing inequality the average citizen could well become a digital slave.
2 The dissolution of the nation state
The borderless world. The need for global harmonisation is likely to become urgent and very pressing. But this will remain quite difficult.
If governments don’t regulate properly, then ENTIRE INDUSTRIES will migrate to other countries. E.g. health/surgery/education.
4 Need for appropriate market mechanisms, business models and regulatory policy
In this video, Michael Schrage refers to the need for innovation in business models and policy.
This indicates the increasing importance of economic theory (e.g. Hal Varian’s innovations) in the future.
There will be a need to make money in a different way.
5 The problems of the unemployed
Notions of simply redistributing the wealth miss the fact that the returns on work aren’t just measured in wages. The workplace is a major institution in society. Work is a social environment, with birthday celebrations and coffee klatches, purpose and (hopefully) meaning. People who work are less lonely on average than people who don’t. People with jobs feel connected to their wider community. Jobs can be and should be mentally stimulating and emotionally engaging. “For most people, work is a community,” says Meir Statman, a finance professor at Santa Clara University. [Source]
1 Meaninglessness
2 Mass leisure
3 Negative effects of expectorations
Effect on nations
1 Developed nations
Developed nations (or even nations like China which are pursuing robotics actively) are likely to be able to grow rapidly through exports.
|And Solow, who is 87, notes that the aspirations of billions of poor people in other parts of the world will create ample room|
|for continued economic growth—and employment—around the globe. “Some of that will be done by those large low-wage populations,|
|but it offers plenty of opportunities for higher-productivity, higher-wage workers in the rich countries to export,” he says. |
|[Source] |
1 Effect of robotics on USA
USA, in particular, has lost many millions of jobs due to offshoring. [“"Over the past decade the US has lost 6 million manufacturing jobs.” - Source]
Countries like USA are likely to see an increase in jobs in the short run due to increased robotics as manufacturing returns to USA (onshoring). Manufacturing accounts for 11% of employment in the U.S. but 24% in Germany and 27% in South Korea. There is significant scope to bring manufacturing back to USA.
Onshoring, however, will occur only when robots become sufficiently cheap and flexible. This is now starting to happen.
“Robotics is a critical factor in rebalancing world manufacturing economies because it reduces the threat from low-cost-of-labor countries.” [Source]
“Apple is moving some manufacturing BACK to the USA from abroad. Termed reshoring work. But instead of 1,000s of factory workers, it is expected TOTAL employment, including the receptionist, to be 200. Why? Automation.” [Source]
My comment
We should be concerned about the reduction in liberties in USA, not so much these market/technology-based trends. Liberty is the mandatory condition, middle class is optional. If liberty is available to everyone (and therefore opportunity) then people won’t really care so much about the inevitably increasing inequality.
If there is enough prosperity through modern technology, then progressive taxation can rebalance distribution (although I disagree with this idea of ‘rebalancing’), if necessary.
The risk comes not from the reducing middle class but from increasing restrictions on technology and capital. And federal debt. If such restrictions (and over-spending by government) are not removed, technology and capital flight will occur, driving away even prosperity from USA. [Source]
2 Effect of robotics on Australia
The future for most small nations like Australia is going to be somewhat similar to India in the robotic age. As major factories locate to USA/Japan/Korea/Germany (given their intellectual advantage in robotics), countries like Australia will become mere consumers. There will set in an ever-widening gap in the GDP of robotised nations and ill-prepared nations like Australia. Stagnant income for the vast majority of Australians will become chronic.
Australia spends hundreds of millions of dollars in the name of "innovation". Not sure how much of that goes towards artificial intelligence. So far nothing worth mentioning in the robotics/AI stable has emerged from Australia (there is the Boeing cockpit design, though). In the end it is going to be only about BRAIN POWER and ability to multiply the human brain a million times through robots/AI. Today Australia depends on Americans and Japanese to build its cars locally, and has no ability to build a TV set/computer/mobile phone/voice recognition system. There is no internal development of innovation. Its future is not looking great.
2 Developing nations
1 Effect of robotics on China
China is consciously focusing on robotics as a strategy to prevent Western onshoring. This is likely to make China a major manufacturing hub even in the future.
2 Effect of robotics on India
1 India has missed the boat
India has missed the boat. The world of robotics and machines is making India redundant to the world economy. Too little FDI, 10th rate education system, zero infrastructure, caste system, and 100th rate governance system. Massive change is underway, much bigger than the China story. I don't know whether India is even aware of what is going on!
2 India has virtually no chance of being a manufacturing nation now
Here's where India needs to move now - towards services. It has virtually no chance in manufacturing (the onset of the Robotic Age coupled with India's terrible socialist policies - which blocked FDI at the right time - almost entirely rule out major manufacturing in India).
Its focus (in terms of employment) should be on increased education, health and services. Agriculture should be allowed to mechanised as soon as practicable. IT industry is India's KEY future industry. Fortunately, in this area India is relatively well placed. India should provide the intellectual input for new software/robots and its entrepreneurs should MASSIVELY exploit the opportunity to fund their ideas through new crowdfunding models.
Note that I'm not "advocating" that India skip manufacturing. I'm merely stating the fact that India is now IRRELEVANT to global manufacturing. China is not. Even in the Robotic Age China will do a lot of manufacturing. India's window was roughly till today (since 1947), but now that window has largely closed. India should still try to ramp up IT/robotics, but it has a very remote chance now of ever catching up either in income or output, with the West.
3 India is going to continue to lose top IT talent to the West
Attracting top technical talent from India (and other developing countries) is a DELIBERATE strategy in the West to create innovation and jobs in the face of rapid loss of jobs in traditional industries/services. Only top talent is wanted.
I don't see how India can possibly retain its talent given miserable policies of Congress/BJP. These primitive "parties" and their leaders are fighting ancient medieval battles when the robotics age is already upon us.
These people have no sense of urgency that the time to act is almost over. Just like FII drained away recently, FDI will come to a halt (except in a few areas such as insurance/retail) as manufacturing shifts back to the West and most outsourcing is made irrelevant by technology.
India faces a bleak future. Sometimes I feel that it is best for all talent to GET OUT of India - so it can at least achieve something in life. Millions of lives are being totally wasted in India.
INDIA IS LUCKY THAT US HAS BECOME A BIT STUPID RE: IMMIGRATION. The moment US gets its act together, virtually ALL talent in India will leave. The West has not choice but to create an OPEN ARMS POLICY for talent.
|"Anand and Shikha Chhatpar, they started a company called Fame Express that was building really cool Facebook apps. They |
|signed up a million users in almost no time, building lots of revenue. Annan and Shikha paid a quarter of a million dollars in|
|taxes while they were here. They had to go back to India to get their visa adjusted to start the process of permanent |
|residency, and the U.S. government wouldn't let them back, despite the fact that they were hiring Americans, they were doing |
|well, they were here legally. Annan had filed eight patents, so the guy was exceptional. No one was disagreeing that he's a |
|worthy candidate. But even the head of the immigration department couldn't fix this. So now they're living in India, paying |
|Indian taxes, employing Indian workers. It's a big loss for America. This is the stupidity of our immigration system" [Source]|
Beware of the day when USA wakes up and implements this policy by Vivek Wadhwa: "If we had a startup visa which allowed any foreigner to start a company here, if after three or four years the company is employing less than five Americans, that person is ineligible for a green card. That would lead to tens of thousands of new startups, possibly hundreds of thousands of startups, which would generate hundreds of thousands, maybe millions of jobs — all for a cost of zero." [Source]
4 Robotics research in India
E-yantra, a group of students at IIT Bombay (Mumbai), tweeted in response to my previous article, and agreed with my diagnosis that Indians can expect to be replaced by robots if they don't rush in to upskill. RIGHT NOW.
Economics of extreme longevity (even some form of immortality)
As part of my readings on robotics, I've become persuaded that regardless of whether machines can become genuinely human-like (that would depend largely on progress in AI, since hardware will definitely permit such capacity), man willplaced break through the atomic levels of biology.
"Aging isn't the irreversible affliction that we thought it was" [Source]
Extreme longevity is 100 per cent certain in the near future, even if immortality is still in question. We can't rule out immortality, though. Its probability is greater than zero. So we should at least start thinking aloud about it.
In the extreme case, immortality will collide with infinite abundance – leading to rather strange outcomes. Some videos first:
And here's a report on Kurzweil's recent talk. And this: Ray Kurzweil’s Case for Immortality.
"I'm right on the cusp," he adds. "I think some of us will make it through" – he means baby boomers, who can hope to experience practical immortality if they hang on for another 15 years.
And a TEDx Vienna talk: . And here's China Daily spreading this idea across China.
All signs are now VERY STRONG that disease will come fully under human control. For instance: human-engineered bacteria are now able to hunts down pathogens.
Economists need to start thinking about this issue.
1 Pensions
A basic question would be, for instance, about old-age pension schemes.
I'm fundamentally opposed to all pension schemes. Instead, I believe a social minimum is the way to go. Regardless of the cause, if you have fallen below a poverty level, the government should top up (not double count) till you are able to (frugally) survive. Why should anyone be responsible for paying you a pension?
All over the West, old-age pension schemes are now in place. As longevity increases dramatically, these schemes will come under massive pressure, and will ultimately need to be abolished – as they should.
2 Further reading on the biology/economics of immortality
I'm going to start reading/reviewing the literature on this issue, time permitting. If you've got any peer reviewed references, please let me know.
A quick search across the internet led to the following links:
A facebook group where people share data on longevity studies.
The Economics of Immortality: Conference hosted by the European Commission, Bruxelles, 8 October 2009
Economics of immortality?
Economics of longevity.
The Economics of Immortality (contains a video talk)
How do Changes in Human Longevity Impact on our Demography?
Would Immortality Become An Overpopulation Nightmare?
Immortality and Society
The Social Burden of Longer Lives
Some Practical Problems of Immortality
Immortality within 30 Years
Immortality is a bad idea (Joichi Ito)
The ethics of ageing, immortality and genetics by Daniela Cutas
The Economic and Social Benefits of "Immortality"
Should we be concerned? Should the government do anything?
There is seemingly a "growing mismatch between rapidly advancing digital technologies and slow-changing humans."
But after considerable analysis and thought I’ve come to the view that this is not a matter of concern. There is a new equilibrium ahead for mankind.
1 A new equilibrium will soon emerge
There is no reason to panic.
|“unemployment in the Kennedy and early Johnson years remained stubbornly high, reaching 7 percent at one point. Automation, |
|seen loitering in the vicinity of the industrial crime, appeared a likely culprit.” To take one example: Life magazine |
|published a picture in 1963 of a new automated machine tool called Milwaukee-Matic that could replace 18 workers. |
|It was feared that this was the new norm. Robert Heilbroner, a well-known economist who wrote a widely read book on economic |
|history (“The Worldly Philosophers: The Lives, Times, and Ideas of the Great Economic Thinkers”) warned: “As machines continue|
|to invade society . . . it is human labor itself — at least, as we now think of ‘labor’ — that is gradually rendered |
|redundant.” |
|So concerned was President Johnson that in 1964 he appointed a National Commission on Technology, Automation and Economic |
|Progress. [Source] |
The economy is already adjusting, as people with greater buying power (IT-driven industries) are starting to pay personal trainers and artists for a better quality of life.
Creative, fitness and spiritual industries are going to be the boom industries of the future.
2 Some good policies
1 Greater competition and regulatory reform
We would need even more competition and regulatory reform, to make it easier for businesses to establish and operate.
2 Attract innovators/talent from across the world
Robotics/IT is driven by top science and maths talent, so it will be crucial to attract the best talent from across the world (possibly through migration).
1 The exodus of talent from Silicon Valley
In a study “Then and Now: America’s New Immigrant Entrepreneurs, Part VII Vivek Wadhwa shows that “the number of immigrant entrepreneurs in the United States has fallen slightly. But according to Vivek Wadhwa, an author of the study, the drop is especially steep in Silicon Valley, long a magnet for the brightest and most ambitious minds from around the world. From 1995 to 2005, immigrants founded 52 percent of the startups in Silicon Valley. The updated research shows that since 2005, that dropped to 44 percent.” [Source]
|In this video, Michio Kaku shows how US has grown off the brainpower of top technical PhDs from Indian and China, etc. |
|America's secret weapon is H1B. |
|And here is Indian Vivek Wadhwa strongly promoting that USA attract India's top talent: |
|"Anand and Shikha Chhatpar, they started a company called Fame Express that was building really cool Facebook apps. They |
|signed up a million users in almost no time, building lots of revenue. Annan and Shikha paid a quarter of a million dollars in|
|taxes while they were here. They had to go back to India to get their visa adjusted to start the process of permanent |
|residency, and the U.S. government wouldn't let them back, despite the fact that they were hiring Americans, they were doing |
|well, they were here legally. Annan had filed eight patents, so the guy was exceptional. No one was disagreeing that he's a |
|worthy candidate. But even the head of the immigration department couldn't fix this. So now they're living in India, paying |
|Indian taxes, employing Indian workers. It's a big loss for America. This is the stupidity of our immigration system" [Source]|
|And here is Bill Gates promoting migration of technically skilled people into USA. |
|The USA has no option but to go full throttle on attracting the world's best talent if it has to succeed in this Robotic Age. |
2 Need for talent-friendly policies
3 If you do need to spend on innovation, spend on robotics/AI/nanotechnology
If funds must be spend on innovation policy (ideally this should be left to the market) then some co-funding of good robotics ventures may be sensible on case by case basis.
4 Retraining
Retraining is generally a bad idea, but in some cases it might work.
|The idea that if we could simply re-train everyone, the problem would be solved is simply not credible. If you doubt that, ask|
|any of the thousands of workers who have completed training programs, but still can't find work. [Source] |
3 Bad policies
1 Progressive taxation
This is a common ‘solution’ to inequality. Excessively progressive taxation can, however, cause capital to flee.
2 Redistribution
1 Citizen’s income
A more disastrous idea than this was never imagined.
References
1 Key blogs on robotics
Everything robotic
2 Economics of a robotic economy
Artificial Intelligence - Economics and Job Market Impact
Drum, Kevin. Welcome, Robot Overlords. Please Don't Fire Us? Smart machines probably won't kill us all—but they'll definitely take our jobs, and sooner than you think.
Hanson, Robin. Economic Growth Given Machine Intelligence.
Hanson, Robin. Economics of The Singularity
Nilsson, N. J. (1985). Artificial intelligence, employment, and income. Human Systems Management, 5, 123–125.
Nilsson, N., Cook, S., Kay, A., Duchin, F., Boden, M., & Chamot, D. (1983). Artificial intelligence: its impacts on human occupations and distribution of income. In Proceedings 8th International Joint Conference on Artificial Intelligence Karlsruhe, West Germany. William Kaufmann.
Loukas Karabarbounis and Brent Neiman, The Global Decline of the Labor Share, June 2013
Should we fear the end of work?
Smith, Karl. Inequality In The Robot Future
What the robotic age means for U.S. manufacturing
Matthew Yglesias, Who Gets Rich When Robots Take Our Jobs
David H. Autor, Frank Levy and Richard J. Murnane: “The Skill Content of Recent Technological Change: An Empirical Exploration,” published in The Quarterly Journal of Economics in November 2003
David F. Noble, Forces of Production: A Social History of Industrial Automation.
Leandro Prados de la Escosura and Joan R. Rosés, WAGES AND LABOR INCOME IN HISTORY: A SURVEY
Jason Borenstein in AI & SOCIETY (2011), Robots and the changing workforce
Journal
AI & SOCIETY
3 Science of robotics
Anderson SL (2008) Asimov’s ‘‘three laws of robotics’’ and machine metaethics. AI & Soc 22:477–493
Bankhead C (2009) SGO: robotic hysterectomy shows advantages over open surgery. MedPage Today. . com/MeetingCoverage/SGO/12784. Accessed 18 Feb 2009
Banks MR, Willoughby LM, Banks WA (2008) Animal-Assisted therapy and loneliness in nursing homes: use of robotic versus living dogs. J Am Med Dir Assoc 9(3):173–177
Berry JN III (2006) Humans do a better job. Libr J 131:10
Clarke R (1993) Asimov’s laws of robotics: implications for information technology—part I. Computer 26(12):53–61
Clarke R (1994) Asimov’s laws of robotics: implications for information technology-part II. Computer 27(1):57–66
Demetriou D (2009) Robot teacher conducts first class in Tokyo school.
Faucounau V, Wu YH, Boulay M, Maestrutti M, Rigaud AS (2009) Caregivers’ requirements for in-home robotic agent for supporting community-living elderly subjects with cognitive impairment. Technol Health Care 17(1):33–40
Hayes B (2009) Automation on the job. Am Sci 97(1):10
Iacono S, Kling R (1998) Computerization movements: the rise of the internet and distant forms of work. In: Yates J, Van Maanen J (eds) Information technology and organizational transformation: history, rhetoric, and practice. Sage Publications, Thousand Oaks, CA, pp 93–136 (part of an anthology from 2001)
Kane T (2006) The Terrifying liberation of labor. Notre Dame J Law Ethics Public Policy 20:815–833
Kleiner K (2008) Bottle-brush robot goes where ‘pigs’ can’t reach. NewScientist.
Kurzweil R (1990) The age of intelligent machines, Chapter Five: mechanical roots.
Kurzweil R (2000) The age of spiritual machines: when computers exceed human intelligence. Penguin Books, USA.
Lin P, Bekey G, Abney K (2008) Autonomous military robotics: risk, ethics, and design. Ethics & Emerging Technologies Group at California State Polytechnic University
Luo M (2009) Job retraining may fall short of high hopes. The New York Times
Lynn LH (2002) Engineers and engineering in the US and Japan: a critical review of the literature and suggestions for a new research agenda. IEEE Trans Eng Manage 49(1):95–106
MacDorman KF, Vasudevan SK, Ho C-C (2009) Does Japan really have robot mania? Comparing attitudes by implicit and explicit measures. AI & Soc 23:485–510
Nagenborg M, Capurro R, Weber J, Pingel C (2008) Ethical regulations on robotics in Europe. AI & Soc 22:349–366
Nomura T (2009) Software agents and robots in mental therapy: psychological and sociological perspectives. AI & Soc 23:471–
Norman DA (2007) The design of future things. Basic Books, New York
Nye DE (2004) Technological prediction: a promethean problem. In: Technological visions: the hopes and fears that shape new technologies. Temple University Press, Philadelphia, pp 159–176
Pilotless police drone takes off (2007) BBC News. . co.uk/go/pr/fr/-/2/hi/uk_news/england/merseyside/6676809.stm. Accessed 28 July 2009
Poll: Adults prefer face time to Facebook (2009) . http:// Science_News/2009/08/03/Poll-Adults-preferface-time-to-Facebook/UPI-12321249322918/. Accessed 4 Aug 2009
Pullin J (2006) Automation saves jobs. Professional Engineering, p 39
Robertson N (2009) How robot drones revolutionized the face of warfare. . warfare.remote.uav/index.html. Accessed 24 July 2009
Robotic Percussionist. . html. Accessed 8 May 2009
Robots seen doing work of 3.5 million in Japan (2008) . 220080408. Accessed 24 Jan 2009
Scassellati B (2007) How social robots will help us to diagnose, treat, and understand autism. In: Thrun S, Brooks R, Durrant-Whyte H (eds) Robotics research. Springer, New York, pp 552–563
Singer PW (2009) Wired for War. Penguin Press, New York
Slade G (2007) Made to break: technology and obsolescence in America. Harvard University Press, Cambridge
Smith D (2009) Does Baseball’s future lie in these cold, robotic hands? . . Accessed 30 July 2009
Sparrow R, Sparrow L (2006) In the hands of machines? The future of aged care. Mind Mach 16:141–161
Spencer R (2004) Assembly robots help U.S. companies stay competitive, retain jobs. Robotics World 22:10, 12–13
Tabuchi H (2009) In Japan, machines for work and play are idle. The New York Times. technology/13robot.html. Accessed 30 July 2009
Tenner E (1996) The Computerized Of.ce: productivity puzzles. In: Katz E, Light A, Thompson W (eds) Controlling Technology: contemporary issues, 2nd edn. Prometheus Books, Amherst, NY, pp 467–485 (part of an anthology from 2003)
The Automation Jobless (1961) Time Magazine
US Air Force (2009) United States Air Force Unmanned Aircraft Systems Flight Plan 2009–2047. 072309kp1.pdf. Accessed 1 Sept 2009
US Department of Defense (2009) Unmanned Systems Integrated Roadmap 2009–2034. UMSIntegratedRoadmap2009.pdf. Accessed 17 July 2009
Wallach W, Allen C (2009) Moral machines: teaching robots right from wrong. Oxford University Press, Inc., New York
Winner L (1980) Do artifacts have politics. In: Teich AH (ed) Technology and the future, 9th edn. Wadsworth, New York, 2003, pp 148–164
Brynjolfsson, Erik and Andrew McAfee, Race Against The Machine: How the Digital Revolution is Accelerating Innovation, Driving Productivity, and Irreversibly Transforming Employment and the Economy.
Borenstein, Jason, Robots and the changing workforce , AI & Soc (2011) 26:87–93
Vedakkapet, Prahlad, The Robotic Age
Kurzweil, Ray (2005). The Singularity Is Near: When Humans Transcend Biology.
Moravec, H. (1998). When will computer hardware match the human brain? Journal of Transhumanism. .
Brynjolfsson, Erik and Adam Saunders. Wired for Innovation:How Information Technology is Reshaping the Economy
A Roadmap for US Robotics From Internet to Robotics (2009)
Gerhardus D., Robot-assisted surgery: the future is here, J Healthc Manag. 2003 Jul-Aug;48(4):242-51.
Edmundas Kazimieras Zavadskas, Automation and robotics in construction: International research and achievements.
Paula Gomes (2011), Surgical robotics: Reviewing the past, analysing the present, imagining the future Robotics and Computer-Integrated Manufacturing, Volume 27, Issue 2, April 2011, Pages 261–266.
4 Ethics of robotics
Arkin RC (2007) Governing lethal behavior: embedding ethics in a hybrid deliberative/reactive robot architecture, GVU Technical Report GIT-GVU-07-11, pp 1–117
Bringsjord S (2008) Ethical robots: the future can heed us. AI & Soc 22:539–550
Decker M (2008) Caregiving robots and ethical reflection: the perspective of interdisciplinary technology assessment. AI & Soc 22:315–330
Harris CE (2008) The Good Engineer: giving virtue its due in engineering ethics. Sci Eng Ethics 14(2):153–164
Michael Nagenborg, Rafael Capurro, Jutta Weber, Christoph Pingel (2008). Ethical regulations on robotics in Europe, AI & SOCIETY (2008)
`
Key issues
Object and facial recognition
Computers do better than humans
AI: Key barrier is human emotions. And we can’t mass produce minds.
Inter-operability
Synthetic biology (converting biological through GM to make them do things they were not designed for)
Deep learning
Sparse coding
Home robots – people are willing to spend more than for a car (if it were useful).
Cyborg (cybernetic organism)
Artificial materials (e.g. metamaterials) including invisibility cloak
Spacex
Following images from:
[pic]
[pic]
COMPUTER SINGER MAKES $120 million. (And yes, she dances in 3D through modern projection technologies.)
Hatsune Miku is a computer program (Yamaha's Vocaloid 2 voice synthesiser). You can make her sing anything you like. She has made $US120 million for CFM from 80,000 sales plus licensing.
Somewhat crazy:
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