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it is about coming robotic age and it is compiled by sanjeev sablok.
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The Glorious Abundance and Creativity of the Robotic Age
Sanjeev SabhlokPreliminary Draft 17 September 2013
This is very preliminary.Happy to receive input at [email protected]
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.
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Contents
1. From around 2000 AD: the Early Robotic Age...................................11.1.1 Autonomous economy..............................................................................3
1.2 Video introduction to the issues............................................................................31.3 Agricultural age as a major discontinuity from the hunting gathering age.............3
1.3.1.1 The Artilect Age..................................................................................................................41.4 Are there any ‘hard limits’ on advances in robotics/AI?.........................................4
1.4.1 Hardware limits.........................................................................................41.4.1.1 Silicon computer have limits...............................................................................................41.4.1.1 Molecular computers.........................................................................................................41.4.1.2 Quantum computers will breakthrough to an unbelievable level.......................................41.4.1.1 Nanocomputers..................................................................................................................4
1.4.2 Software limits..........................................................................................51.4.2.1 AI 51.4.2.1 Object recognition..............................................................................................................51.4.2.2 Machine learning................................................................................................................51.4.2.3 Rat Brain simulation...........................................................................................................51.4.2.4 Human Brain Project...........................................................................................................61.4.2.5 Quantum computer programming.....................................................................................6
1.5 Three key scenarios................................................................................................61.5.1.1 I.J. Good’s Intelligence explosion concept..........................................................................7
1.6 Long term structural change in Australia...............................................................81.7 Industrial machines supplemented muscle. Robots supplement our senses and
brains 91.8 The ‘coming of age’ of robots...............................................................................10
1.8.1 What are robots?....................................................................................101.8.2 Maturation of many related technolgies.................................................11
1.8.2.1 Genome mapping.............................................................................................................111.8.2.2 3-D printing.......................................................................................................................121.8.2.3 Biological computers........................................................................................................121.8.2.4 Neural networks...............................................................................................................121.8.2.5 Recreation of detailed map of the brain...........................................................................121.8.2.1 Fusion 121.8.2.1 Nanotechnology/nanorobots...........................................................................................12
1.9 What can robots do?............................................................................................131.9.1 Physical...................................................................................................13
1.9.1.1 2-legged robots can walk in the midst of people and on rough surfaces..........................131.9.1.2 4-legged robots can run faster than humans....................................................................131.9.1.3 4-legged robots can carry loads and walk faster uphill than humans...............................131.9.1.4 Extreme athleticism in running/flying...............................................................................131.9.1.5 Can jump 30 feet..............................................................................................................131.9.1.1 Can fight and ‘kill’ other robots........................................................................................131.9.1.1 Can dance /play games.....................................................................................................13
1.9.2 Dexterity.................................................................................................131.9.2.1 Can bounce balls and catch objects with fingers..............................................................131.9.2.2 Have extremely fine ‘hand-eye’ coordination...................................................................141.9.2.1 Can drive trains.................................................................................................................141.9.2.2 Can drive cars and trucks and fly planes...........................................................................141.9.2.1 Can fly helicopeter upside down.......................................................................................14
1.9.3 Verbal......................................................................................................141.9.3.1 Can talk 141.9.3.2 Can sing 14
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1.9.4 Creative...................................................................................................141.9.4.1 Can sketch and make oil paintings (eDavid)......................................................................141.9.4.1 Can make music (bands)...................................................................................................15
1.9.1 Cognitive computing...............................................................................151.10 Major signs that the robotic age is upon us.........................................................15
1.10.1 Significant acceleration in capability.......................................................151.10.1.1 Already we have a computer equal to human brain in processing power......151.10.1.1 Predictions.....................................................................................................151.10.1.2 Significant acceleration (second half of the chessboard)...............................161.10.1.3 Significant acceleration in AI..........................................................................16
1.10.2 The commercial case for robots..............................................................161.10.2.1 Dramatically falling robot prices.....................................................................161.10.2.2 The rise of the multi-purpose robot...............................................................161.10.2.3 Many other advantages of robots..................................................................17
1.10.3 Evidence of commercial deployment......................................................171.10.3.1 Size of robotics industry.................................................................................171.10.3.2 Number of WorkCover claims reducing.........................................................171.10.3.3 Number of robots increasing..........................................................................181.10.3.4 Manufacturing is shifting back to the West....................................................191.10.3.5 Suddenness of change....................................................................................19
1.11 Who’s driving this rapid change?.........................................................................201.12 Key organisations.................................................................................................20
1.12.1 IFR (International Federation of Robotics)..............................................201.12.2 DARPA 201.12.3 Pentagon.................................................................................................201.12.4 Boston Robotics......................................................................................211.12.5 Universal Robots.....................................................................................211.12.6 Yamaha 211.12.7 iRobot 211.12.8 Rethink Robotics.....................................................................................211.12.9 Key publicly traded robotic companies...................................................21
1.12.9.1 Healthcare Applications:................................................................................221.12.9.2 Defense, Security and Space Applications*:...................................................221.12.9.1 Industrial and Co-robot Applications**:.........................................................221.12.9.2 Ancillary businesses to the robotics industry:................................................23
1.13 Opinions...............................................................................................................231.13.1 Mostly positive........................................................................................23
1.13.1.1 William Lazonick.............................................................................................231.13.1.2 Hal Varian.......................................................................................................231.13.1.3 Dr. Michio Kaku..............................................................................................231.13.1.4 Frank Levy and Richard Murnane...................................................................231.13.1.5 Robin Hanson.................................................................................................231.13.1.1 W. Brian Arthur..............................................................................................241.13.1.1 Mark Thoma...................................................................................................241.13.1.1 Eliezer Yudkowsky..........................................................................................241.13.1.1 Laurence Katz.................................................................................................241.13.1.1 Robert Atkinson.............................................................................................24
1.13.2 Mostly negative (i.e. this is a big issue for society)..................................241.13.2.1 Andrew McCaffee and Erik Brynjolfsson........................................................251.13.2.2 Martin Ford....................................................................................................251.13.2.3 Kevin Drum.....................................................................................................251.13.2.4 Tyler Cowen...................................................................................................251.13.2.5 PBS.................................................................................................................281.13.2.6 Paul Krugman.................................................................................................281.13.2.7 Izabella Kaminska...........................................................................................281.13.2.8 Alex Hern........................................................................................................28
1.13.3 Totally confused......................................................................................291.13.3.1 Federico Pistono.............................................................................................291.13.3.1 Peter Diamandis.............................................................................................29
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2. Examples of robotic innovations (including AI)...............................302.1 Smart assistants...................................................................................................30
2.1.1 Expliner High-Voltage Power Transmission Line Inspection Robot.........302.1.2 Spare tyre mounting robot......................................................................302.1.3 Packing assistant.....................................................................................302.1.4 Automated vacuum cleaners..................................................................302.1.5 Toys.........................................................................................................312.1.6 Hospital assistants...................................................................................31
2.1.6.1 Medicine Picking and Delivering Robot System................................................................312.1.6.2 Surgical assistants.............................................................................................................312.1.6.3 Heavy lifter32
2.1.7 Military assistants...................................................................................322.1.8 Police assistants......................................................................................32
2.1.8.1 Spying robot:....................................................................................................................322.1.8.1 Robot micorobots/insects................................................................................................32
2.1.9 Agriculture and fisheries assistants.........................................................322.1.10 New forms of transport...........................................................................322.1.11 Manager’s assistants...............................................................................322.1.12 Bee pollination assistant.........................................................................32
2.2 Workers (in manufacturing).................................................................................332.2.1 Industrial robots......................................................................................33
2.3 Workers (in retail/service industry)......................................................................332.3.1 Burger maker..........................................................................................33
2.4 Humanoid robots.................................................................................................332.5 Personal assistants...............................................................................................33
2.5.1 Translators..............................................................................................332.5.2 Walking assistant....................................................................................332.5.3 Housemaid..............................................................................................33
3. Economic issues and concerns........................................................343.1 Glorious abundance doesn’t mean absence of scarcity.......................................343.2 Machines and humans: complements or substitutes?.........................................343.3 Cost/benefit of robots/IT/technology..................................................................34
3.3.1 Capital robots and consumption robots..................................................343.4 Say’s law and robotics..........................................................................................343.5 Overall increase in prosperity/luxury...................................................................35
3.5.1 Productivity and growth..........................................................................353.5.2 Increased expectations...........................................................................353.5.3 Really low prices......................................................................................353.5.4 Laws of investment will not change........................................................363.5.5 Rising manufacturing productivity..........................................................373.5.6 Increasing share of services in economic output....................................37
3.6 Effect on innovation and entrepreneurship.........................................................383.6.1 Start-ups are cheaper..............................................................................38
3.7 Effect on labour share..........................................................................................393.7.1 Workers’ bargaining power significantly reducing..................................393.7.2 But labour share was much lower in the past.........................................393.7.3 Industries where significant loss in labour share is occurring.................403.7.4 Most importantly, labour share is irrelevant...........................................41
3.8 Effect on jobs........................................................................................................423.8.1 Derived demand for resources and labour..............................................43
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3.8.2 Many new jobs created by technology...................................................443.8.2.1 Kinds of new jobs created.................................................................................................453.8.2.1 Number of new jobs created............................................................................................453.8.2.1 Industrial robotics has created 350,000 new jobs............................................................45
3.8.3 But job creation slower than job loss......................................................463.8.4 Jobs which have gone.............................................................................47
3.8.4.1 Library 483.8.4.1 Stevedores 483.8.4.2 Mining truck drivers..........................................................................................................493.8.4.3 Iphone workers.................................................................................................................493.8.4.1 Warehousing workers.......................................................................................................493.8.4.1 Banks 493.8.4.1 McDonald’s cashiers.........................................................................................................493.8.4.1 Telephone directory assistance........................................................................................493.8.4.1 Datacentre IT staff............................................................................................................49
3.8.5 Jobs which are next in line......................................................................503.8.5.1 Overall analysis.................................................................................................................503.8.5.2 Administration/bureaucrats.............................................................................................503.8.5.1 Call centres and helpdesk.................................................................................................503.8.5.2 Lawyers 503.8.5.3 Retail 513.8.5.4 Butchers (abattoirs)..........................................................................................................513.8.5.5 Doctors 513.8.5.6 Receptionists....................................................................................................................513.8.5.1 Call centres513.8.5.1 Pharmacies523.8.5.2 Fruit harvesters.................................................................................................................523.8.5.1 Dusting crops with pesticides...........................................................................................523.8.5.1 Cleaners 523.8.5.1 Package delivery...............................................................................................................523.8.5.1 Security guards.................................................................................................................523.8.5.2 Assembly/packaging workers...........................................................................................523.8.5.3 Farmers 523.8.5.1 Dairy farmers (robotic dairy)............................................................................................523.8.5.2 Pilots 523.8.5.1 Financial services and financial market traders................................................................533.8.5.1 Construction industry.......................................................................................................533.8.5.1 Drummers/ musicians.......................................................................................................533.8.5.1 Age carers (Social Assistive Robots).................................................................................533.8.5.1 Housemaids......................................................................................................................533.8.5.1 Ship repairers (underwater).............................................................................................533.8.5.1 Waste disposal..................................................................................................................533.8.5.1 Truck drivers.....................................................................................................................533.8.5.1 Taxi drivers543.8.5.1 Astronauts 54
3.8.6 Jobs which are mostly safe......................................................................543.8.6.1 IT related 543.8.6.2 Plumbers 543.8.6.3 Electricians 543.8.6.4 Construction industry workers.........................................................................................543.8.6.5 Hairdressers......................................................................................................................543.8.6.6 Gardeners 543.8.6.7 Old age carers and nurses.................................................................................................543.8.6.8 Key government agencies (police, justice, defence).........................................................543.8.6.9 Comedians 54
3.9 The flourishing of creativity..................................................................................553.9.1.1 Creative artists, writers and entertainers.........................................................................553.9.1.2 Exercise and fitness trainers.............................................................................................553.9.1.3 Interior designers..............................................................................................................553.9.1.4 Yoga teachers...................................................................................................................553.9.1.5 Spiritual gurus...................................................................................................................553.9.1.6 Psychologists and social workers......................................................................................55
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3.10 The challenge for unskilled youth........................................................................553.11 Effect on wages....................................................................................................55
3.11.1 Fact: Relative share of wages in GDP decline..........................................553.11.2 Hypothesis: Not technology but globalisation........................................563.11.3 Hypothesis: Permanently reduced wages...............................................573.11.4 Hypothesis: wages may not fall...............................................................57
3.12 Effect on employment..........................................................................................573.12.1 The less educated have less of a chance of finding jobs now..................573.12.2 Lower labour participation......................................................................573.12.3 Employment may not fall in the long run................................................58
3.12.3.1 Hours worked by everyone may fall...............................................................583.13 Increased inequality.............................................................................................58
3.13.1 Median income barely growing...............................................................593.13.1.1 USA.................................................................................................................593.13.1.1 Australia.........................................................................................................60
3.13.2 Divide between rich and poor rapidly growing.......................................603.13.3 Share of corporate profits rising.............................................................61
3.14 Effect on asset values...........................................................................................613.15 Rout of the middle class.......................................................................................613.16 Education is the FOUNDATION of robotics/IT revolution.....................................613.17 Reduced traffic congestion...................................................................................62
4. Social (and political/legal) consequences........................................634.1 Will liberate women.............................................................................................634.2 Ethics of robotics..................................................................................................63
4.2.1 Isaac Asimov's "Three Laws of Robotics"................................................634.2.2 Humans shouldn’t be doing such jobs anyway........................................63
4.3 Regulatory impact/ regulation of robots..............................................................634.3.1 Privacy issues..........................................................................................644.3.2 The dissolution of the nation state..........................................................64
4.4 Need for appropriate market mechanisms, business models and regulatory policy644.5 The problems of the unemployed........................................................................64
4.5.1 Meaninglessness.....................................................................................654.5.2 Mass leisure............................................................................................654.5.3 Negative effects of expectorations..........................................................65
5. Effect on nations.............................................................................665.1 Developed nations...............................................................................................66
5.1.1 Effect of robotics on USA.........................................................................665.1.2 Effect of robotics on Australia.................................................................66
5.2 Developing nations...............................................................................................675.2.1 Effect of robotics on China......................................................................675.2.2 Effect of robotics on India.......................................................................67
5.2.2.1 India has missed the boat.................................................................................................675.2.2.2 India has virtually no chance of being a manufacturing nation now.................................675.2.2.3 India is going to continue to lose top IT talent to the West..............................................675.2.2.1 Robotics research in India.................................................................................................68
6. Economics of extreme longevity (even some form of immortality) 696.1 Pensions...............................................................................................................696.2 Further reading on the biology/economics of immortality..................................70
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7. Should we be concerned? Should the government do anything?...717.1 A new equilibrium will soon emerge....................................................................717.2 Some good policies...............................................................................................71
7.2.1 Greater competition and regulatory reform...........................................717.2.2 Attract innovators/talent from across the world....................................71
7.2.2.1 The exodus of talent from Silicon Valley...........................................................................717.2.2.1 Need for talent-friendly policies.......................................................................................72
7.2.3 If you do need to spend on innovation, spend on robotics/AI/nanotechnology...................................................................72
7.2.4 Retraining................................................................................................727.3 Bad policies..........................................................................................................72
7.3.1 Progressive taxation................................................................................727.3.2 Redistribution..........................................................................................72
7.3.2.1 Citizen’s income................................................................................................................72
8. References......................................................................................738.1 Key blogs on robotics...........................................................................................738.2 Economics of a robotic economy.........................................................................738.3 Science of robotics...............................................................................................738.4 Ethics of robotics..................................................................................................76
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1. 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.
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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) http://www.youtube.com/watch?v=OAQvk7wzAu4 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: https://www.youtube.com/watch?feature=player_embedded&v=44yzn-yCCK8#t=290
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.
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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]
1.1.1 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]
1.2 Video introduction to the issuesRaffaello 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.
1.3 Agricultural age as a major discontinuity from the hunting gathering ageThis 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.
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1.3.1.1 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 MOTIVATATION (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 sufficienit adaptability.
The richness and diversity of human motivation entierly distinguishes us from robots/artilets. If any harm is caused, it will be through a human being who misuses the artilects for personal gain.
1.4 Are there any ‘hard limits’ on advances in robotics/AI?
1.4.1 Hardware limits
1.4.1.1 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.
1.4.1.1 Molecular computers
The next stage is molecular computers.
http://www.kurzweilai.net/another-breakthrough-in-replacing-silicon-in-transistors
1.4.1.2 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, http://www.youtube.com/watch?v=lEaAidCmxus, at the 4-5 minutes mark].
Quantum Computers Animated: http://www.youtube.com/watch?v=T2DXrs0OpHU
“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]
1.4.1.1 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.
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“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]
1.4.2 Software limits
1.4.2.1 AI
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.
1.4.2.1 Object recognition
This is the stage when computers can recognise generic objects (e.g. a cup). Taken further, this inclues facial recognition.
1.4.2.2 Machine learning
In this computers learn on their own
1.4.2.3 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,
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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]
1.4.2.4 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]
1.4.2.5 Quantum computer programming
Programming quantum computers are particularly hard to program:
http://gizmodo.com/why-programming-a-quantum-computer-is-so-damn-hard-1188316086
1.5 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:
o 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.
o 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.
o Advocates: Ray Kurzweil, Alvin Toffler(?), John Smart
Event Horizon:
o 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.
o 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.
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o Advocates: Vernor Vinge
Intelligence Explosion:
o 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.
o 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.
o Advocates: I. J. Good, Eliezer Yudkowsky
1.5.1.1 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: http://intelligence.org/files/IEM.pdf]
“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 IntelligenceTheorem” à la Greg Egan) which says that nothing qualitatively smarter than a human can exist.” [Source].
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1.6 Long term structural change in Australia
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.
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Which services are growing, which are falling in Australia (long term trends):
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.
1.7 Industrial machines supplemented muscle. Robots supplement our senses and brainsNew 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.
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The key is that machines now sense the environment and respond to it dynamically. They are not static any longer.
1.8 The ‘coming of age’ of robotsWhile 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.
1.8.1 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]
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1.8.2 Maturation of many related technolgiesAlthough 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.
1.8.2.1 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. (http://www.genome.gov/sequencingcosts/). In just 11 years.
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1.8.2.2 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.
https://www.youtube.com/watch?v=veHUqZ_dbNE
1.8.2.3 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]
http://med.stanford.edu/ism/2013/march/bil-gates.html
1.8.2.4 Neural networks
1.8.2.5 Recreation of detailed map of the brain
First the human genome was created. Now the full map and reproduction of the brain is underway. http://www.ted.com/talks/henry_markram_supercomputing_the_brain_s_secrets.html
1.8.2.1 Fusion
Proven prototypes of fusion (i.e. endless energy) are now not more than 20 years away.
1.8.2.1 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: http://www.youtube.com/watch?v=QnnbEsY93X4
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1.9 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.
1.9.1 Physical
1.9.1.1 2-legged robots can walk in the midst of people and on rough surfaces
ASIMO 2011: http://www.youtube.com/watch?v=zul8ACjZI18
Also, Atlas the Pentagon robot.
1.9.1.2 4-legged robots can run faster than humans
This robot (Cheetah) runs at 29 miles per hour.
1.9.1.3 4-legged robots can carry loads and walk faster uphill than humans
Robotic donkey (DARPA - AlphaDog Legged Squad Support System (LS3))
http://www.youtube.com/watch?v=gOkXRXZIFxs
Donkey that throws objects:
http://www.youtube.com/watch?v=2jvLalY6ubc
[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.]
1.9.1.4 Extreme athleticism in running/flying
Seeing is believing.
Raffaello D'Andrea: The astounding athletic power of quadcopters.
1.9.1.5 Can jump 30 feet
http://www.youtube.com/watch?v=6b4ZZQkcNEo
1.9.1.1 Can fight and ‘kill’ other robots
http://www.youtube.com/watch?v=W3gEoK44XaQ
1.9.1.1 Can dance /play games
Robots now dance, and play soccer and ping pong. China is advancing rapidly in robotics.
E.g. table tennis: http://www.youtube.com/watch?v=t_qN3dgYGqE
Dancing robots: http://www.youtube.com/watch?v=4t1NWH6G1f0
Fencing: https://www.youtube.com/watch?feature=player_embedded&v=kKKQQUMBqts
1.9.2 Dexterity
1.9.2.1 Can bounce balls and catch objects with fingers
http://www.youtube.com/watch?v=H_151R2i0G4
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1.9.2.2 Have extremely fine ‘hand-eye’ coordination
Universal robots are now able to perform extremely fine ‘hand-eye’ coordination tasks with very little training.
1.9.2.1 Can drive trains
Robotics and IT have replaced thousands of train drivers across the world. A full list of driverless trains: http://en.wikipedia.org/wiki/List_of_driverless_trains#Asia
1.9.2.2 Can drive cars and trucks and fly planes
Google has an unmanned/driverless car/s and F35 is the last manned fighter jet.
http://www.economist.com/node/18958487Hal 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?
1.9.2.1 Can fly helicopeter upside down
http://www.youtube.com/watch?v=AY4ajbu_G3k (that was 2011).
1.9.3 Verbal
1.9.3.1 Can talk
A talking robot was launched into space in August 2013. Watch the short movie. Also see the BBC report: http://www.bbc.co.uk/news/world-asia-23565121
1.9.3.2 Can sing
Singing robot: http://www.youtube.com/watch?v=mfxkhzGqZIs
1.9.4 Creative
1.9.4.1 Can sketch and make oil paintings (eDavid)
http://www.informatik.uni-konstanz.de/en/edavid/videos/
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1.9.4.1 Can make music (bands)
Singing robot: http://www.youtube.com/watch?v=mfxkhzGqZIs
Robot music band: http://www.youtube.com/watch?v=3RBSkq-_St8
1.9.1 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]
1.10 Major signs that the robotic age is upon us
1.10.1 Significant acceleration in capability
1.10.1.1 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.
1.10.1.1 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
1 http://en.wikipedia.org/wiki/Timeline_of_the_future_in_forecasts#Artificial_intelligence_and_robotics
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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: http://www.youtube.com/watch?v=jmi8KW7gZbE
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: http://www.youtube.com/watch?v=EtataLdqNvw
1.10.1.2 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.
1.10.1.3 Significant acceleration in AI
The key to the Robotic Age is the significant ramping up of artificial intelligence (software).
1.10.2 The commercial case for robots Robots are not just more powerful, they are really cheap.
1.10.2.1 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.
1.10.2.2 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: http://www.everything-robotic.com/2013/05/rethink-robotics-baxter-and-universal.html
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1.10.2.3 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]
1.10.3 Evidence of commercial deployment
1.10.3.1 Size of robotics industry
About $25 billion turnover in 2011 [Source]
1.10.3.2 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.
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1.10.3.3 Number of robots increasing
[Source]
The IFR has predicted that more than 1.5 million industrial robots will be in operation worldwide in 2015. [Source]
See the diagram below.
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Source: http://www.motherjones.com/kevin-drum/2012/04/chart-day-our-robot-overlords-will-take-over-soon
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.
1.10.3.4 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 BrooksChairman 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
1.10.3.5 Suddenness of change
“machines could go from performing 25% of jobs to 75% within four years”. [Race Against Machine].
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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: http://hanson.gmu.edu/IEEESpectrum-6-08.pdf]
1.11 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: http://www.us-robotics.us/reports/CCC%20Report.pdf]
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]
1.12 Key organisations
1.12.1 IFR (International Federation of Robotics)Download report here.
1.12.2 DARPA
1.12.3 PentagonAtlas
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1.12.4 Boston Robotics
1.12.5 Universal Robots
1.12.6 Yamaha
1.12.7 iRobot
1.12.8 Rethink RoboticsBaxter – a universal robot that can be trained. Requires NO programming. Base price $22,000.
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.
1.12.9 Key publicly traded robotic companiesSource: http://www.everything-robotic.com/2012/04/picking-robotics-stocks-is-complicated.html
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1.12.9.1 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.
1.12.9.2 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.
1.12.9.1 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
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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.
1.12.9.2 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.
1.13 Opinions
1.13.1 Mostly positive
1.13.1.1 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.
1.13.1.2 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.http://www.theaustralian.com.au/news/features/varians-analysis/story-e6frgabx-1226138793835
1.13.1.3 Dr. Michio Kaku
Are We Ready For the Coming 'Age of Abundance?
Video: http://www.youtube.com/watch?v=ceEog1XS5OI
1.13.1.4 Frank Levy and Richard Murnane
Third Way report, “Dancing with Robots”.
http://web.mit.edu/flevy/www/
The New Division of Labor: How Computers Are Creating the Next Job Market
Frank Levy & Richard J. Murnane
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1.13.1.5 Robin Hanson
Hanson, Robin. Economic Growth Given Machine Intelligence.
Hanson, Robin. Economics of The Singularity
http://www.youtube.com/watch?v=vdV_PjTEaaY
Singularity economics
http://hanson.gmu.edu/IEEESpectrum-6-08.pdf
1.13.1.1 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]
1.13.1.1 Mark Thoma
http://economistsview.typepad.com/economistsview/2013/01/robots-and-all-that.html “There will be jobs we can’t imagine right now,” says Mark Thoma, an economist at the University of Oregon. [Source]
1.13.1.1 Eliezer Yudkowsky
Intelligence Explosion Microeconomics
The Robots, AI, and Unemployment Anti-FAQ
1.13.1.1 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]
1.13.1.1 Robert Atkinson
http://www.ideaslaboratory.com/2013/09/09/robert-atkinson-robots-are-not-the-enemy/
Time for a Manufacturing Debate Based on Facts, Not Opinion
1.13.2 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
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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]
1.13.2.1 Andrew McCaffee and Erik Brynjolfsson
This talk by Andrew (already cited earlier) is worth listening:
http://www.youtube.com/watch?v=QfMGyCk3XTw
Erik’s talk here: http://www.youtube.com/watch?v=sod-eJBf9Y0
1.13.2.2 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
Blog: http://econfuture.wordpress.com/
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?
1.13.2.3 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.
1.13.2.4 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]
http://www.overcomingbias.com/2009/10/take-both-econ-tech-seriously.html
http://marginalrevolution.com/marginalrevolution/2012/12/are-robots-and-aging-demographics-self-cancelling-problems.html
If robots concentrate wealth in the hands of IP owners, wages for many workers might fall or remain stagnant. That is a problem.
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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.
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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
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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]
1.13.2.5 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. http://www.youtube.com/watch?v=wb2cI_gJUok
1.13.2.6 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]
1.13.2.7 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]
1.13.2.8 Alex Hern
http://www.newstatesman.com/economics/2013/06/basic-income-versus-robots
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.
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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]
1.13.3 Totally confused
1.13.3.1 Federico Pistono
https://www.youtube.com/watch?v=kYIfeZcXA9U&list=PLE5E136B66C03CB78
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.
1.13.3.1 Peter Diamandis
https://www.youtube.com/watch?v=sXdA1lP7DKY&list=PLE5E136B66C03CB78
Hopelessely confused socialist.
His view is that once devices become so good, then there won’t even be any professionals. He is confused since he doesn’t have understand the conception of LIMITLESS human needs. Therefore, there will still be many fields in which jobs will be creaed.
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2. 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: http://www.therobotreport.com/index.php/archive
2.1 Smart assistants
2.1.1 Expliner High-Voltage Power Transmission Line Inspection RobotA phenomenal solution for bushfire prevention in Victoria. Alternative inspection (physical/helicopter) required by the Regs is both inadequate and expensive. http://www.youtube.com/watch?v=By1yE37rjgU
2.1.2 Spare tyre mounting robotThe 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]
2.1.3 Packing assistanthttp://money.cnn.com/gallery/technology/2013/01/14/help-robots/2.html
2.1.4 Automated vacuum cleanersiRobot etc.
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2.1.5 Toys robotic hamsters (Zhu Zhu)
robotic penguins
indoor-flying iPhone controlled quad copter by Parrot.
2.1.6 Hospital assistantsMedical 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]
2.1.6.1 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)
http://www.youtube.com/watch?v=g63WUCUuCD0
2.1.6.2 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
http://www.us-robotics.us/reports/CCC%20Report.pdf
Three-armed robot known as da Vinci®, which has helped to usher in the next generation of minimally invasive surgery
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]
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2.1.6.3 Heavy lifter
http://money.cnn.com/gallery/technology/2013/01/14/help-robots/5.html
2.1.7 Military assistantsRobots in unstructured environments (e.g. iRobot bomb disposal robots)
2.1.8 Police assistants
2.1.8.1 Spying robot:
http://money.cnn.com/gallery/technology/2013/01/14/help-robots/4.html
2.1.8.1 Robot micorobots/insects
http://www.youtube.com/watch?v=cyjKOJhIiuU
2.1.9 Agriculture and fisheries assistantsIn Japan drones dust crops and track schools of tuna [Source]
2.1.10 New forms of transporthttp://www.youtube.com/watch?v=5LduYhx5lDY [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: http://www.youtube.com/watch?v=5LduYhx5lDY
Major solution to traffic congestion: http://www.youtube.com/watch?v=zb51CvptTt4
2.1.11 Manager’s assistantsTelepresence robots: http://edition.cnn.com/2013/06/19/business/telepresence-office-robots
2.1.12 Bee pollination assistantRobobee - pollinator/surveillance
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2.2 Workers (in manufacturing)
2.2.1 Industrial robotsThere 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).
2.3 Workers (in retail/service industry)
2.3.1 Burger maker This robot can make 340 burgers per hour
2.4 Humanoid robotsHUMANOID 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
2.5 Personal assistants
2.5.1 Translators GeoFluent offering from Lionbridge has brought instantaneous machine translation to customer service interactions. [Race against the machine]
http://www.theage.com.au/technology/technology-news/its-the-thought-that-counts-20130831-2sxvp.html
“"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.” [http://www.theage.com.au/technology/technology-news/its-the-thought-that-counts-20130831-2sxvp.html]
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.
2.5.2 Walking assistanthttp://www.youtube.com/watch?v=pp4XUvgqkbU (HOW TO WALK)
2.5.3 Housemaidhttp://www.youtube.com/watch?v=VELzj6Wyg3Y
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3. Economic issues and concerns
3.1 Glorious abundance doesn’t mean absence of scarcityIf 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.
3.2 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]
3.3 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.
3.3.1 Capital robots and consumption robotsDifferent treatments will apply to long lived robots vs. shortlived ones (e.g. floor cleaning robots).
3.4 Say’s law and roboticsThe 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.
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3.5 Overall increase in prosperity/luxury
3.5.1 Productivity and growth“The economics of digital information, in short, are the economics not of scarcity but of abundance”. [Source: Race Against Machines]
3.5.2 Increased expectationsThe better the health robots, the more the demand for even more of them.
The expansion of the percolation of luxuries will continue unabated.
3.5.3 Really low pricesEffect of competition and really low prices:
http://www.forbes.com/sites/timworstall/2012/12/10/that-robot-economy-and-the-rentier-class/But there is a point at which it is uneconomic to supply:
http://www.tobiasbuckell.com/2011/01/05/economists-consider-robot-economics-need-to-read-more-frederick-pohl/
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.
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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.
3.5.4 Laws of investment will not changeKey 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
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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.
3.5.5 Rising manufacturing productivity
3.5.6 Increasing share of services in economic outputConsistent with the increasing share of services in employment, the share of services in output has also been increasing.
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Source
3.6 Effect on innovation and entrepreneurshipWe’ll continue to see an exponential increase in innovation.
3.6.1 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.’’ [http://www.theaustralian.com.au/news/features/varians-analysis/story-e6frgabx-1226138793835
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
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done by a machine instead. [ [Race against the machine]
3.7 Effect on labour shareLabour 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.”
Source
3.7.1 Workers’ bargaining power significantly reducingNo 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].
3.7.2 But labour share was much lower in the pastThat IT (and ultimately robotics) has a role to play in this is not self-evident.
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Source
3.7.3 Industries where significant loss in labour share is occurringBargaining capacity of labour is reducing most in mining, transport, manufacturing and utilities.
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Source
3.7.4 Most importantly, labour share is irrelevantJust 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.
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3.8 Effect on jobs
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: https://www.youtube.com/watch?feature=player_embedded&v=wb2cI_gJUok]
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]
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3.8.1 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]
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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 http://www.ideaslaboratory.com/2013/09/09/robert-atkinson-robots-are-not-the-enemy/
3.8.2 Many new jobs created by technologyIn 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]
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3.8.2.1 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.
3.8.2.1 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]
3.8.2.1 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]
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[Source]
3.8.3 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.
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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]
3.8.4 Jobs which have gonetechnology 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]
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[Source]
3.8.4.1 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." http://www.theaustralian.com.au/news/features/varians-analysis/story-e6frgabx-1226138793835
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]
3.8.4.1 Stevedores
Stevedores replaced. This, again, is just the beginning. Only 2013 now.
http://www.portbris.com.au/news-media/port-of-brisbane-a-snapshot/a-modern-port
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3.8.4.2 Mining truck drivers
http://www.theaustralian.com.au/news/features/rise-of-the-machines/story-e6frg6z6-1226291014017
http://www.theaustralian.com.au/business/mining-energy/bhp-unveils-robot-trucks/story-e6frg9df-1226507887714
3.8.4.3 Iphone workers
1 million robots installed: http://www.theaustralian.com.au/business/world/robots-threaten-chinas-workers/story-e6frg90o-1226106476518
3.8.4.1 Warehousing workers
See: https://www.youtube.com/watch?feature=player_embedded&v=3UxZDJ1HiPE
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]
3.8.4.1 Banks
ATM machines replaced the tellers.
3.8.4.1 McDonald’s cashiers
7000 cashiers replaced: http://news.cnet.com/mcdonalds-hires-7000-touch-screen-cashiers/8301-17938_105-20063732-1.html
3.8.4.1 Telephone directory assistance
Automated, and/or through the internet.
3.8.4.1 Datacentre IT staff
IT trends of eliminating IT datacenters and consolidating on the cloud.
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3.8.5 Jobs which are next in line
3.8.5.1 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
3.8.5.2 Administration/bureaucrats
We can expect automation of administration and won’t need too much middle management in the future.
3.8.5.1 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]
3.8.5.2 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
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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]
3.8.5.3 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]
3.8.5.4 Butchers (abattoirs)
This is a very dangerous job. There is no doubt that abattoirs will soon get robotised.
http://www.youtube.com/watch?feature=player_embedded&v=UrVFcqgHSLQ#t=50
3.8.5.5 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.
https://www.youtube.com/watch?v=UUWqLo_OSIk&feature=c4-overview-vl&list=PLF9ECAAB36D53EFE8 at 12 minutes
3.8.5.6 ReceptionistsIn another 20 years expect most office receptionists to be replaced.http://www.youtube.com/watch?v=aF_8gM4urmA)
3.8.5.1 Call centres
The end of Indian call centres is nigh. "Eliza has replaced India’s Tata Consulting Services." [Source]
Also see this:
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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.
3.8.5.1 Pharmacies
Pharmacies will feature a single pill-dispensing robot in the back while the pharmacists focus on patient consulting. [Source]
3.8.5.2 Fruit harvestersFruit harvester jobs are on the line.http://www.youtube.com/watch?v=V4HnFgqvIKk
and http://www.youtube.com/watch?v=nm3WS5y3kCk
Fruit and vegetable picking will continue to be robotized until no humans pick outside of specialty farms. [Source]
3.8.5.1 Dusting crops with pesticides
“In Japan drones dust crops” [Source]
3.8.5.1 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]
3.8.5.1 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]
3.8.5.1 Security guards
Through satellites, remote cameras and drones, much security work can be centralised.
3.8.5.2 Assembly/packaging workers
Most assembly/packaging workers’ jobs are likely to go pretty soon, in the next 5 years at most: http://www.youtube.com/watch?v=MEVz20X2Kog
Speedy bots able to lift 150 pounds all day long will retrieve boxes, sort them, and load them onto trucks. [Source]
3.8.5.3 Farmers
Farmers http://www.youtube.com/watch?v=BfNBlB32TGM&list=PL000493B7BE09B9D5
[Intelligent machines are already in place]
http://www.youtube.com/watch?v=nm3WS5y3kCk
3.8.5.1 Dairy farmers (robotic dairy)
See: https://www.youtube.com/watch?feature=player_embedded&v=WHSHcH8fxyw
3.8.5.2 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
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also include passenger planes in the longer run). http://www.economist.com/node/18958487
3.8.5.1 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: http://www.theaustralian.com.au/business/wealth/high-frequency-trades-undermine-the-system/story-e6frgac6-1226496627861]
“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]
3.8.5.1 Construction industry
From 11 minutes you see why construction industry will soon be revolutionised with flying robots that build massive skyscrapers. http://edition.cnn.com/2012/03/04/opinion/ted-kumar-flying-robots
Full fledged major robots are not being designed to build entire homes – much stronger than normal homes – without any labour. http://www.youtube.com/watch?v=ehnzfGP6sq4
3.8.5.1 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.
https://www.youtube.com/watch?v=_sUeGC-8dyk
3.8.5.1 Age carers (Social Assistive Robots)
Social Assistive Robots are rapidly coming:
See this.
3.8.5.1 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.
http://www.youtube.com/watch?v=VELzj6Wyg3Y
3.8.5.1 Ship repairers (underwater)
Robots are now being created to do this job.
http://whatsnext.blogs.cnn.com/2012/10/10/how-i-learned-to-make-underwater-robots/
3.8.5.1 Waste disposal
Automatic sorting/processing is likely to become more common.
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3.8.5.1 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.
3.8.5.1 Taxi drivers
http://www.economist.com/blogs/schumpeter/2013/08/driverless-cars?fsrc=scn/fb/wl/bl/newleaf
In fact, it would be good if taxi drivers were replaced with self-driven cars, given the terrible reputation they’ve developed.
3.8.5.1 Astronauts
https://www.youtube.com/watch?feature=player_embedded&v=0eDWZ9jkRQo
3.8.6 Jobs which are mostly safeAlthough 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]
3.8.6.1 IT related
I'd strongly recommend that young people start taking Coursera courses in AI or any other technology that interests them.
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3.8.6.2 Plumbers
3.8.6.3 Electricians
3.8.6.4 Construction industry workers
3.8.6.5 Hairdressers
3.8.6.6 Gardeners
3.8.6.7 Old age carers and nurses
3.8.6.8 Key government agencies (police, justice, defence)
3.8.6.9 Comedians
If you are a really good artist/comedian/singer, you too will do well.
3.9 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 http://www.youtube.com/watch?v=ceEog1XS5OI, Michio Kaku explains the kind of creativity that will succeed.
3.9.1.1 Creative artists, writers and entertainers
3.9.1.2 Exercise and fitness trainers
3.9.1.3 Interior designers
3.9.1.4 Yoga teachers
3.9.1.5 Spiritual gurus
3.9.1.6 Psychologists and social workers
3.10 The challenge for unskilled youthThe 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.
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3.11 Effect on wagesThere 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]
3.11.1 Fact: Relative share of wages in GDP declinehttp://blogs.reuters.com/felix-salmon/2012/09/26/chart-of-the-day-the-long-decline-of-labor/
"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]
Source: http://economistsview.typepad.com/economistsview/2013/08/poverty-and-economics.html
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3.11.2 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.”
http://rwer.wordpress.com/2013/05/01/what-causes-the-share-of-labor-to-decrease-3-graphs/
Source.
3.11.3 Hypothesis: Permanently reduced wageshttp://modeledbehavior.com/2011/01/04/unlike-immigrants-robots-will-permanently-drive-down-wages/
3.11.4 Hypothesis: wages may not fallwages may not really fall:
http://future-econ.blogspot.com.au/2009/11/artificial-intelligence-economics-and.html
3.12 Effect on employment
3.12.1 The less educated have less of a chance of finding jobs nowSource: http://theforvm.org/diary/bernard-guerrero/zero-marginal-product
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3.12.2 Lower labour participationVery 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." http://www.usatoday.com/story/money/business/2013/04/07/march-labor-force-participation/2057887/
Note: Australian participation rate is still climbing. http://www.rba.gov.au/publications/smp/2013/feb/graphs/graph-c1.html
3.12.3 Employment may not fall in the long runHere 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." [http://www.theaustralian.com.au/national-affairs/opinion/fiddling-with-criteria-to-hide-unemployed/story-e6frgd0x-1226688359320]
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3.12.3.1 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]
3.13 Increased inequalitySee 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
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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]
3.13.1 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.
3.13.1.1 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]
3.13.1.1 Australia
(this is Australia) [Source: p.33: http://www.pc.gov.au/__data/assets/pdf_file/0006/122496/income-distribution-trends.pdf)
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3.13.2 Divide between rich and poor rapidly growingThe 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:http://www.pc.gov.au/__data/assets/pdf_file/0006/122496/income-distribution-trends.pdf
“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.
http://www.philosophersbeard.org/2013/05/avoiding-our-dystopian-robot-future.html
3.13.3 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]
3.14 Effect on asset valueshttp://future-econ.blogspot.com.au/2009/11/artificial-intelligence-economics-and.html
3.15 Rout of the middle classHere'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.
http://www.aim-projekt.dk/files/robot-employment.pdf
“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,
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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]
3.16 Education is the FOUNDATION of robotics/IT revolutionMichio Kaku is very concerned about the lack of good education in USA. H1-B visa
http://www.youtube.com/watch?v=ceEog1XS5OI
(from 45 minutes)
We need more physicsts and engineers.
3.17 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 https://www.youtube.com/watch?v=UUWqLo_OSIk&feature=c4-overview-vl&list=PLF9ECAAB36D53EFE8]
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4. Social (and political/legal) consequences
4.1 Will liberate womenAs they can work from home, the role of women in the economy will change.
4.2 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]
4.2.1 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.
4.2.2 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]
4.3 Regulatory impact/ regulation of robotsAnd 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]
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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: http://www.youtube.com/watch?v=vN2aEJyIq48 (killer robots – the future of war)
4.3.1 Privacy issues This will need serious regulatory work in the coming decades.
This is an eye-opening (although long but entirely worthwhile) video. http://www.youtube.com/watch?v=_tpsH05ELg4
In casinos there is total surveillance: https://www.youtube.com/watch?v=GmunFinmaGY
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.
4.3.2 The dissolution of the nation stateThe 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.
4.4 Need for appropriate market mechanisms, business models and regulatory policyIn this video, http://www.youtube.com/watch?v=ceEog1XS5OI 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.
4.5 The problems of the unemployedNotions 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
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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]
4.5.1 Meaninglessnesshttp://www.philosophersbeard.org/2013/05/avoiding-our-dystopian-robot-future.html
4.5.2 Mass leisurehttp://www.philosophersbeard.org/2013/05/avoiding-our-dystopian-robot-future.html
4.5.3 Negative effects of expectorationshttp://www.wired.com/gadgetlab/2008/10/as-computers-ge/
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5. Effect on nations
5.1 Developed nationsDeveloped 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]
5.1.1 Effect of robotics on USAUSA, 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]
5.1.2 Effect of robotics on AustraliaThe 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.
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5.2 Developing nations
5.2.1 Effect of robotics on ChinaChina 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.
5.2.2 Effect of robotics on India
5.2.2.1 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!
5.2.2.2 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.
5.2.2.3 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.
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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]
5.2.2.1 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.
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6. 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: http://www.tedxvienna.at/blog/goal-immortality/. 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.
6.1 PensionsA 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.
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6.2 Further reading on the biology/economics of immortalityI'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"
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7. 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.
7.1 A new equilibrium will soon emergeThere 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.
7.2 Some good policies
7.2.1 Greater competition and regulatory reformWe would need even more competition and regulatory reform, to make it easier for businesses to establish and operate.
7.2.2 Attract innovators/talent from across the worldRobotics/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).
7.2.2.1 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]
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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.
7.2.2.1 Need for talent-friendly policies
7.2.3 If you do need to spend on innovation, spend on robotics/AI/nanotechnologyIf 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.
7.2.4 RetrainingRetraining 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]
7.3 Bad policies
7.3.1 Progressive taxationThis is a common ‘solution’ to inequality. Excessively progressive taxation can, however, cause capital to flee.
7.3.2 Redistribution
7.3.2.1 Citizen’s income
http://www.newstatesman.com/economics/2013/06/basic-income-versus-robots
A more disastrous idea than this was never imagined.
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8. References
8.1 Key blogs on roboticsEverything robotic
8.2 Economics of a robotic economyArtificial 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
JournalAI & SOCIETY
8.3 Science of roboticsAnderson 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. http://www.medpagetoday. com/MeetingCoverage/SGO/12784. Accessed 18 Feb 2009
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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. http://news.bbc. 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) UPI.com. http:// www.upi.com/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
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Robotic Percussionist. http://www.gatech.edu/research/roboticdrummer. html. Accessed 8 May 2009
Robots seen doing work of 3.5 million in Japan (2008) Reuters.com. http://www.reuters.com/article/oddlyEnoughNews/idUST27506 220080408. Accessed 24 Jan 2009
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8.4 Ethics of roboticsArkin RC (2007) Governing lethal behavior: embedding ethics in a hybrid deliberative/reactive robot architecture, GVU Technical Report GIT-GVU-07-11, pp 1–117
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http://www.voanews.com/content/robotic-age-draws-closer-103637709/126519.html
http://qz.com/98427/in-japan-robots-could-be-mans-next-best-friend/`
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
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Spacex
Following images from: http://www.technologyreview.com/featuredstory/515926/how-technology-is-destroying-jobs/
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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.
http://www.youtube.com/watch?v=pEaBqiLeCu0
Somewhat crazy: https://www.youtube.com/watch?v=NvE4UhKmEfw
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