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Society is caught between blind faith in technology and resistance to progress, between technological possibilities and fears that it has a negative impact.
Increasingly Artificial Intelligence, the latest buzzword for everything software related, is stirring up much of the fears.
In an interesting paper: Is This Time Different? The Opportunities and Challenges of Artificial Intelligence, Jason Furman, Chairman of President Obama’s Council of Economic Advisers sets out his belief that we need more artificial intelligence but must find a way to prevent the inequality it will inevitably cause. Despite the labor market challenges we may need to navigate, Furman’s bigger worry is that we will not invest enough in AI.
He is more pragmatic than many economists and researchers who have written ‘popular’ books on the subject but calls for more innovation if we are truly to reap the benefits AI and Robotics will bring:
We have had substantial innovation in robotics, AI, and other areas in the last decade. But we will need a much faster pace of innovation in these areas to really move the dial on productivity growth going forward. I do not share Robert Gordon’s (2016) confidently pessimistic predictions or Erik Brynjolfsson and Andrew Mcafee’s (2014) confidently optimistic ones because past productivity growth has been so difficult to predict.
Technology, in other words, is not destiny but it has a price
My worry is not that this time could be different when it comes to AI, but that this time could be the same as what we have experienced over the past several decades. The traditional argument that we do not need to worry about the robots taking our jobs still leaves us with the worry that the only reason we will still have our jobs is because we are willing to do them for lower wages.
Replacing the Current Safety Net with a Universal Basic Income Could Be Counterproductive
Furman says that AI does not create a call for a Universal Basic Income and that the claims for implementing UBI and cancelling other social welfare programs have been greatly overstated:
AI does not call for a completely new paradigm for economic policy—for example, as advocated by proponents of replacing the existing social safety net with a universal basic income (UBI) —but instead reinforces many of the steps we should already be taking to make sure that growth is shared more broadly.
Replacing part or all of that system with a universal cash grant, which would go to all citizens regardless of income, would mean that relatively less of the system was targeted towards those at the bottom—increasing, not decreasing, income inequality.
Instead our goal should be first and foremost to foster the skills, training, job search assistance, and other labor market institutions to make sure people can get into jobs, which would much more directly address the employment issues raised by AI than would UBI.
Past Innovations Have Sometimes Increased Inequality—and the Indications Suggest AI Could Be More of the Same
Relying on the questionable study by Frey and Osborne, Furman says that work by the Council of Economic Advisers, ranked the occupations by wages and found that, according to the Frey and Osbourne analysis, 83 percent of jobs making less than $20 per hour would come under pressure from automation, as compared to 31 percent of jobs making between $20 and $40 per hour and 4 percent of jobs making above $40 per hour (see Figure 1 below).
AI has not had a large impact on employment, at least not yet
Furman says the issue is not that automation will render the vast majority of the population unemployable. Instead, it is that workers will either lack the skills or the ability to successfully match with the good, high paying jobs created by automation.
The concern is not that robots will take human jobs and render humans unemployable. The traditional economic arguments against that are borne out by centuries of experience. Instead, the concern is that the process of turnover, in which workers displaced by technology find new jobs as technology gives rise to new consumer demands and thus new jobs, could lead to sustained periods of time with a large fraction of people not working.
AI has the potential—just like other innovations we have seen in past decades—to contribute to further erosion in both the labor force participation rate and the employment rate. This does not mean that we will necessarily see a dramatically large share of jobs replaced by robots, but even continuing on the past trend of a nearly 0.2-percentage-point annual decline in the labor force participation rate for prime-age men would pose substantial problems for millions of people and for the economy as a whole.
Investment in AI
Mentioning the fact that AI has not had a significant macroeconomic impact yet, Furman indicates that the private sector will be the main engine of progress on AI. Citing references that in 2015 the private sector invested US$ 2.4 billion on AI, as compared to the approximately US$ 200 million invested by the National Science Foundation (NSF).
He says the government’s role should include policies that support research, foster the AI workforce, promote competition, safeguard consumer privacy, and enhance cybersecurity
AI does not call for a completely new paradigm for economic policy
AI is one of many areas of innovation in the U.S. economy right now. At least to date, AI has not had a large impact on the aggregate performance of the macroeconomy or the labor market. But it will likely become more important in the years to come, bringing substantial opportunities— and our first impulse should be to embrace it fully.
He indicates that his biggest worry about AI is that we may not get all the breakthroughs we think we can, and that we need to do more to make sure we can continue to make groundbreaking discoveries that will raise productivity growth, improving the lives of people throughout the world.
However, it is also undeniable that like technological innovations in the past, AI will bring challenges in areas like inequality and employment. As I have tried to make clear throughout my remarks, I do not believe that exogenous technological developments solely determine the future of growth, inequality, or employment. Public policy—including public policies to help workers displaced by technology find new and better jobs and a safety net that is responsive to need and ensures opportunity —has a role to play in ensuring that we are able to fully reap the benefits of AI while also minimizing its potentially disruptive effects on the economy and society. And in the process, such policies could also contribute to increased productivity growth—including advances in AI itself.
What are those policies? Truman indicates we need to develop more “human learning and skills,” increase investments in research and development, this includes Government investment and also “expand and simplify the Research and Experimentation tax credit,” “increase the number of visas—which is currently capped by legislation—to allow more high-skilled workers to come into the country.” “Consolidate existing funding initiatives, help retrain workers in skills for which employers are looking,” and more focused initiatives such as the “DARPA Cyber Grand Challenge.”
The bottom line is that AI managed well, with innovate government support, could offer significant benefits to humanity, but those benefits, including earning capacity, can only be achieved if governments and corporations help people up-skill.
 For private funding see https://www.cbinsights.com/blog/artificial-intelligence-funding-trends/#funding. For public funding see http://www.nsf.gov/about/budget/fy2017/pdf/18_fy2017.pdf. According to the NSF, in 2015 there was $194.58 million in funding for the NSF Directorate for Computer and Information Science and Engineering’s Division of Information and Intelligent Systems (IIS), much of which is invested in research on AI. These figures do not include investment by other agencies, including Department of Defense.
Around 1900, most inventions concerned physical reality: cars, airplanes, zeppelins, electric lights, vacuum cleaners, air conditioners, bras, zippers. In 2005, most inventions concern virtual entertainment — We have already shifted from a reality economy to a virtual economy, from physics to psychology. ~Geoffrey Miller
Many commentators and researchers have indicated a supposedly imminent end to work, or at least the infamous ‘47% of jobs will be displaced’ within 20 years or so due to the inexorable advance of machines. This is at best a distraction and at worst grossly exaggerated and overhyped, as one of the authors of the infamous papers has noted.
However if we extend the timeframe out and consider the question:
How much could the world of work plausibly change by the end of the 21st century?
Eighty-four years from now will human’s work to earn a living or will machines do all the labor?
Then I believe we have framed a different vision of the future, one where it may be more plausible to consider that human’s will work 15 hours per week (if at all) as predicted by Keynes in 1930.
 John Maynard Keynes, Economic Possibilities for our Grandchildren (1930) – “everybody will need to do some work if (s)he is to be contented – three-hour shifts or a fifteen-hour week may put off the problem for a great while. “
There is so much doom and gloom associated with robots and jobs it is time to add some common sense to the misunderstandings created by so called experts opinions about robots and jobs – thankfully authors from the OECD may have added some clarity to the debate — ‘finding that on average, across the 21 OECD countries, ‘9% of jobs rather than 47%, as proposed by Frey and Osborne face a high automatibility.’
Capitalism, the term for our global ‘free’ markets, is a uniquely future-oriented economic system in which people invest, make innovations, apply for patents, and in other ways bet on the future. Behind all of this we find the hallmark of humanity, which is our creative intelligence.
It is intelligence that drives these investments and innovations, and intelligence that forges within many of us an intense curiosity of what the future may hold.
It is also intelligence that forges in others an anxiety over what the future holds. For many the future is no longer a promise but a threat!
Pessimism is the easy way out.
This curiosity and anxiety has stirred the same debates in society for generations. On one side there is intense optimism for a future where machines can take over many of the dirty, dangerous, dull and repetitive jobs, opening up new and more ‘interesting and rewarding’ jobs for those that may be displaced.
And on the other side those who are concerned that this time really is different and the machines we are building now, or which we will soon be capable of building, will be so advanced that there really will be no ‘new types’ of jobs for humans – and so they claim the majority of jobs for humans will be eliminated.
To those pessimists I often quote Lord Thomas Babington Macaulay who in 1830 wrote about the prophet’s of gloom:
On what principle is it, that when we see nothing but improvement behind us, we are to expect nothing but deterioration before us?
In his 1995 book Jeremy Rifkin stated that ‘intelligent machines’ were being ‘hurried in to’ work environments, thus ending work for people.
Now, for the first time, human labor is being systematically eliminated from the production process… A new generation of sophisticated information and communication technologies is being hurried into a wide variety of work situations. Intelligent machines are replacing human beings in countless tasks, forcing millions of blue and white-collar workers into unemployment lines, or worse still, breadlines.
It is 21 years since Rifkin made that claim, yet somehow human ingenuity marches on and continues to create more jobs and new industries. Sometimes new technologies eliminate jobs overall, but they also create demand for new capabilities and new jobs.
Looking with both eyes open
Despite the vast improvements we have made as a society, I wonder why it is that we look with one eye open, only seeing the negative aspect of technological change, instead of opening both eyes and seeing the benefits too. Often studies by ‘research scientists’ which receive significant media attention lead to misrepresentation of the potential benefits and impacts of technology and create fears, sometimes as if it is a fait accompli, even if this is not the intention of the study authors.
A new study by Melanie Arntz, Terry Gregory and Ulrich Zierahn for the OECD argues that studies on robots or computerization eradicating jobs, such as that by Frey and Osborne, lead to a severe overestimation of job automatibility, as occupations labelled as high-risk occupations often still contain a substantial share of tasks that are hard to automate.
9 % of jobs could be automatable
The OECD authors provide far more realistic assessments than Frey and Osborne:
In contrast to other studies, we take into account the heterogeneity of workers’ tasks within occupations. Overall, we find that, on average across the 21 OECD countries, 9 % of jobs are automatable. The threat from technological advances thus seems much less pronounced.
Arntz, et al. argue that the estimated share of “jobs at risk” must not be equated with actual or expected employment losses from technological advances for three reasons.
- The utilisation of new technologies is a slow process, due to economic, legal and societal hurdles, so that technological substitution often does not take place as expected.
- Even if new technologies are introduced, workers can adjust to changing technological endowments by switching tasks, thus preventing technological unemployment.
- Technological change also generates additional jobs through demand for new technologies and through higher competitiveness.
Effectively the authors take into account that not whole occupations, but specific jobs are exposed to automatibility, depending on the tasks performed at these particular jobs.
They also demonstrate the necessity to view technological change as substituting or complementing certain tasks rather than whole occupations, which as I have mentioned before in this blog a major flaw in the Frey and Osborne study.
The OECD study authors state:
We find that in the US only 9% of jobs rather than 47%, as proposed by Frey and Osborne face a high automatibility.
We further find heterogeneities across OECD countries: while the share of automatable jobs is 6 % in Korea, the corresponding share is 12 % in Austria. The differences across countries may reflect general differences in workplace organisation, differences in previous investments into automation technologies as well as differences in the education of workers across countries.
Table 1 Automatibility by OECD Countries
The main conclusion from the paper
Automation and digitalisation are unlikely to destroy large numbers of jobs. However, low qualified workers are likely to bear the brunt of the adjustment costs as the automatibility of their jobs is higher compared to highly qualified workers. Therefore, the likely challenge for the future lies in coping with rising inequality and ensuring sufficient (re-)training especially for low qualified workers.
Too many so called research experts have created way too much fear and public perception, which in turn can lead to bad policy recommendations. We need to be thoughtful in our vision, and analytical in our implementation – and realistic in our expectations of technologies capabilities.
Herbert Spencer’s words in “From Freedom to Bondage” are as relevant today as when he wrote them in 1891:
The more things improve the louder become the exclamations about their badness.
 Thomas Babington Macaulay, Review of Southey’s Colloquies on Society, 1830 Edinburgh Review
 Jeremy Rifkin, The End of Work, 1995 Chapter 1.
 Arntz, M., T. Gregory and U. Zierahn (2016), working paper “The Risk of Automation for Jobs in OECD Countries: A Comparative Analysis”, OECD Social, Employment and Migration Working Papers, No. 189, OECD Publishing, Paris.
 Herbert Spencer, The Man Versus the State, With Six Essays on Government, Society, and Freedom (Indianapolis: Liberty Press, 1891), p. 487.
The AI chatbot who learned via the Unabomber Manifesto!
Charles and his team actually created a chatbot called cobot. It was really simple, and it was really dumb. But the users wanted it to be smart, they wanted to talk to it. So Charles and his team had to come up with a quick and easy way to make cobot appear smarter than it actually was. So they showed the robot a bunch of texts (they started, weirdly, with the Unabomber manifesto) and trained it to simply pick a few words that you said to it, search for those words in the things it had read, and spit those sentences back at you.
A fallback plan for when 95% of human labor isn’t valued or needed due to automation
Basic Income is not necessarily my ideal scenario, but Andrew gives a terrific overview of the pro’s and con’s in this excellent article. The 95% figure comes from Y Combinator Manager, Matt Krisiloff!
Silicon Valley techies hope a guaranteed income would cushion the blow as automation replaces human jobs. Those with a more utopian bent, such as the organizers of the Swiss referendum, want to open up more options, to let people create art and free the world of what Daniel Straub calls “bullshit jobs.” (Andrew Flowers at FiveThirtyEight)
Stanford’s robotic diver recovers treasures from King Louis XIV’s wrecked ship
OceanOne looks something like a robo-mermaid. Roughly five feet long from end to end, its torso features a head with stereoscopic vision that shows the pilot exactly what the robot sees, and two fully articulated arms… Every aspect of the robot’s design is meant to allow it to take on tasks that are either dangerous – deep-water mining, oil-rig maintenance or underwater disaster situations like the Fukushima Daiichi power plant – or simply beyond the physical limits of human divers. (Stanford News)
And just think Frey and Osborne said there is only an 18% probability commercial divers will lose their jobs to robots!
Progress in A.I. will affect society profoundly
The first wave of AI is already beginning to pervade our lives inconspicuously, from speech recognition and search engines to image classification. Self-driving cars and applications in health care are within sight, and subsequent waves could transform vast sectors of the economy, science and society. These could offer substantial benefits — but to whom? (Nature – Editorial)
In your old age what happens if your carer just happens to be a robot?
“There’s a pressing requirement for robots in the social care of the elderly, partly because we have fewer people of working age,” says Tony Belpaeme, a professor in intelligent and autonomous control systems at Plymouth University. Traditionally among the poorest paid of the workforce, carers are an ever more scarce resource.
Policy makers have begun to cast their eyes towards robots as a possible source of compliant and cheaper help. (Geoff Watts in The Atlantic)
What are you reading?
In 1812 the British government created an Act of Parliament which made the destruction of mechanized looms – or knitting machines – a capital felony and hence a crime punishable by death. The Act was implemented as a result of so called Luddite attacks on machines.
It should be noted that in many cases the so called Luddites were not raging against the machines taking jobs, but against the employers who failed to provide them with a ‘living wage.’
According to the esteemed historian Eric Hobsbawm, the Luddites had: “no special hostility to machines as such,” their actions were in fact, “a normal means of putting pressure on employers.” Hobsbawm wrote: “Such misconceptions are, I think, due to the persistence of views about the introduction of machinery elaborated in the early nineteenth century.” Adding:
This sort of wrecking was a traditional and established part of industrial conflict in the period of the domestic and manufacturing system, and the early stages of factory and mine. It was directed not only against machines, but also against raw material, finished goods and even the private property of employers, depending on what sort of damage these were most sensitive to. Thus in three months of agitation in 1802 the Wiltshire shearmen burned hay-ricks, barns and kennels of unpopular clothiers, cut down their trees and destroyed loads of cloth, as well as attacking and destroying their mills.
Essentially Luddites were the early trade unions and not raging specifically against the machines but seeking a ‘fair wage’ for the employees by rioting and causing damage to business owners’ property by any means to press their case.
The misconceptions of the actions of the Luddites led to poor legislation and policy in the United Kingdom.
Job security requires skills only Merlin possesses
In 2013, researchers Carl Frey and Michael Osborne of the Oxford Martin School announced that 47 percent of U S jobs were at risk of computerization:
According to our estimates around 47 percent of total US employment is in the high risk category. We refer to these as jobs at risk – i.e. jobs we expect could be automated relatively soon, perhaps over the next decade or two.
In 2014 Deloitte asked them to carry out similar research in the UK, where it was stated Frey and Osborne: “estimate that on average, 35 per cent of current jobs in the UK are at high risk over the next ten to twenty years.”
Frey and Osborne’s papers have led to a deluge of bleak headlines, such as Death of the Accountant and Auditor; Advances in artificial intelligence could lead to mass unemployment, warn experts; and whilst we are on this theme maybe the most embellished article and headline of all: Technology f*cked us all: The anxiety driving Donald Trump and Bernie Sanders is really about machines taking our jobs. The pessimistic view associated with Frey and Osborne’s paper has even led to claims that we may be headed for another Engels’ Pause: a period of stagnant living standards and higher unemployment in the face of rapid technological change.
I am worried by the seemingly incurable pessimism caused by these headlines, which are also instigating governments to champion or consider policies that may not be in the long term best interests of the population they serve.
The headlines scream that if you want to make your job ‘non-susceptible’ to automation then you should make sure it has the type of skills that only Merlin possesses
It is important to realize that the methodology in the Frey and Osborne papers have never been validated with any actual evidence. Anyone with five minutes to spare, a Maths GCSE, and a modicum of common sense could pick flaws in the selection of types of jobs shown to be at high risk of being taken over by a computer algorithm.
Nevertheless, people, including policy makers, suspend their critical judgment and believe the headlines that robots are set to become a Hobbesian nightmare of breathtaking scope.
But if we look beyond the headlines and read the Frey and Osborne paper we find the authors are not stating ‘robots’ WILL take half of all jobs but computerization ‘could’ displace people from the types of jobs they have highlighted. In fact one of the authors, Carl Benedikt Frey, recently wrote in March 2016:
Although we cannot exclude the possibility that technology may reduce the overall demand for jobs in the future, this is seemingly not an immediate concern.
Meanwhile his co-author Michael Osborne has gone as far as saying:
I think a lot of the risk to professions has been overhyped.
Frey and Osborne do a good job surveying a certain type of literature on the suggested improvements being made within robotic, machine learning, artificial intelligence, etc. Although this research tends to rely too much on sources such as the International Federation of Robotics, an industry association with, in my opinion little impartiality and other publicity afforded to various robots and A.I. providers. They provide very little actual citation of work happening within the labs of developers, nor do they analyze the capabilities of current robots in any great degree through discussions with users of these robots, rather referring to the reported capabilities (or expected capabilities) of Baxter the co-bot by Rethink Robotics with a nominal number in service. They also use research that estimates that “the market for personal and household service robots is already growing by about 20 percent annually.” Which is more or less Roomba the automated vacuum cleaner, that to the best of my knowledge has not displaced any Ukrainian housecleaners in Poland!
Evidence of any actual job displacement by the current types of robotics and computerization illustrated by the authors is not shown. What the authors are doing is predicting a demise of jobs based on their research of the available literature! In fact the authors state in the paper:
We speculate about technology that is in only the early stages of development.
Nevertheless, despite the ‘speculation,’ they do make the bold claim:
In the first wave, we find that most workers in transportation and logistics occupations, together with the bulk of office and administrative support workers, and labour in production occupations, are likely to be substituted by computer automation.
So unlikely, so unimaginable
Which jobs are not at risk of automation according to Frey & Osborne?
Occupations that involve complex perception and manipulation tasks, creative intelligence tasks, and social intelligence tasks are unlikely to be substituted by computer capital over the next decade or two.
These are what the authors terms non-susceptible task characteristics.
A sub element of manipulation is manual dexterity. An indication of the level of “Manual Dexterity” computer-controlled equipment would require to perform a specific occupation. Low (level) manual dexterity corresponds to “Screw a light bulb into a light socket”; medium (level) is exemplified by “Pack oranges in crates as quickly as possible”; high (level) is described as “Perform open-heart surgery with surgical instruments”.
It is thus obvious in Frey and Osborne’s thesis that jobs at risk of automation can be summed up as follows:
The probability of an occupation being automated can thus be described as a function of these task characteristics. As suggested by Figure I, the low degree of social intelligence required by a dishwasher makes this occupation more susceptible to computerisation than a public relation specialist, for example. We proceed to examining the susceptibility of jobs to computerisation as a function of the above described non-susceptible task characteristics.
Arriving at 47% of jobs being highly susceptible to automation
The authors relied on O∗NET, an online service developed for the US Department of Labor. O∗NET defines the key features of an occupation as a standardised and measurable set of variables. It also provides open-ended descriptions of specific tasks to each occupation.
They then asked a specific question:
Can the tasks of this job be sufficiently specified, conditional on the availability of big data, to be performed by state of the art computer-controlled equipment?
The authors further identified nine variables that describe the attributes of perception and manipulation, creativity, and social intelligence and which are required to perform the attributes. These are shown in Table 1 from the authors’ paper. They then focused on O∗NET’s description of Tasks.
It should be Work Activity and Skills not Tasks
Time and time again as I look at the types of jobs Frey and Osborne say are at high and medium risk of being done by automation I can’t help but question – is it because they specifically looked at O∗NET data with respect to Tasks and not the essential element that portrays Work Activity and Skills?
Table 1 from Frey and Osborne.
Frey and Osborne indicate that their algorithm predicts that most workers in transportation and logistics occupations, together with the bulk of office and administrative support workers, and labour in production occupations, are at risk of automation within ten to twenty years,
Much of their argument about transportation employees circulates around the advent of driverless cars. We are much closer to an understanding of when driverless cars will be available to the ‘general public’ and it certainly seems that they will not be the main mode of transport in the next 3 decades if current developments and legislation is anything to go by. I do believe that we will see more semi-autonomous trucks on the roads in the coming decade, but I do not see that they will be without a human in the cab for sometime in the future. There are just too many infrastructure problems to overcome, let alone the technical obstacles.
Sports referees, Watch Repairers, Models and Manicurists jobs to be automated
Drill into the report and look at the types of jobs that they say have the highest probability of being replaced by automation and we find all sorts of jobs even the most pessimistic luddite will find hard to accept.
One job at the highest risk of automation, using Frey and Osborne’s methodology is that of Watch Repairer. According to O∗NET statistics there are 3,000 watch repairers in the United States. Now I may accept jobs of watch repairers will dwindle as sales of watches falls due to the fact nearly everybody looks at their smart phone for the time, but not that watches will be repaired by robots! If sales of watches are dwindling why invest the time and money building a robot to repair watches? In fact I suspect that Watch Repairers will become even more of a specialized job as sales of watches focus on the high value watch. I do not expect Watch Repairers will be replaced because an automated machine can repair the watch.
Another job that the authors state is at high risk of automation is Manicurists and Pedicurists – surely that requires a high level of dexterity, precision and social skill?
They also predict the days of Animal Breeders are over (is that because we will all have pet robots?), Gaming Dealers – not social at all!, Real Estate Brokers – presumably robots will arrange to show us around prospective houses. Maybe many people’s favorite choice but not likely any time soon – Umpires, Referees, and Other Sports Officials – will be automated.
Perhaps the one I most flinch at which Frey and Osborne’s algorithm predicts is at high risk of automation is Models.
Look at the tasks O∗NET provides as key for Models.
- Pose for artists and photographers.
- Gather information from agents concerning the pay, dates, times, provisions, and lengths of jobs.
- Follow strict routines of diet, sleep, and exercise to maintain appearance.
- Record rates of pay and durations of jobs on vouchers.
- Report job completions to agencies and obtain information about future appointments.
Now look at the Work Activity O∗NET provides.
- Establishing and Maintaining Interpersonal Relationships — Developing constructive and cooperative working relationships with others, and maintaining them over time.
- Performing General Physical Activities — Performing physical activities that require considerable use of your arms and legs and moving your whole body, such as climbing, lifting, balancing, walking, stooping, and handling of materials.
- Thinking Creatively — Developing, designing, or creating new applications, ideas, relationships, systems, or products, including artistic contributions.
Social Perceptiveness — Being aware of others’ reactions and understanding why they react as they do.
Surely these Work Activities and Skills are elements that fit into Frey and Osborne’s criteria for jobs that will not be automated. I have repeated detailed analysis of over 90 of the occupations that Frey and Osborne indicate are at high and medium risk of automation and each time I question the judgment of the authors.
Policy makers are well advised to do their own analysis before using the Frey and Osborne paper to pursue policies that may not be in the best interest of their constituents.
One final word from the Frey and Osborne which is often overlooked in the hype associated with the paper:
We acknowledge that it is by no means certain that a job is computerisable given our labelling.
 The Destruction of Stocking Frames, etc. Act 1812 (https://en.wikipedia.org/wiki/Destruction_of_Stocking_Frames,_etc._Act_1812)
 Eric Hobsbawm, Machine Breakers (http://libcom.org/history/machine-breakers-eric-hobsbawm)
 Deloitte London Futures: Agiletown: the relentless march of technology and London’s response (http://www2.deloitte.com/uk/en/pages/growth/articles/agiletown-the-relentless-march-of-technology-and-londons-response.html Last accessed 11th April 2016)
 Engel`s Pause: A Pessimist`s Guide to the British Industrial Revolution. Robert C. Allen, April 2007 (http://www.economics.ox.ac.uk/materials/working_papers/paper315.pdf Last accessed 18th April 2016)
 Technology at work: How the digital revolution is reshaping the global workforce. Carl Benedikt Frey, Ebrahim Rahbari 25 March 2016 (http://www.voxeu.org/article/how-digital-revolution-reshaping-global-workforce Last accessed 11th April 2016)
 Robots are leaving the factory floor and heading for your desk – and your job, The Guardian Zoe Corbyn 9th February 2015 (https://www.theguardian.com/technology/2015/feb/09/robots-manual-jobs-now-people-skills-take-over-your-job Last accessed 11th April 2016)
Main paper cited – The Future of Employment: How susceptible are jobs to computerisation? Carl Benedikt Frey and Michael A. Osborne. September 17, 2013 (http://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Future_of_Employment.pdf)
Drone Traffic Management
This is actually quite a big deal – could new jobs be created in Drone Traffic Control?
NASA recently successfully demonstrated rural operations of its unmanned aircraft systems (UAS) traffic management (UTM) concept, integrating operator platforms, vehicle performance and ground infrastructure.
With continued development, the Technical Capability Level One system would enable UAS operators to file flight plans reserving airspace for their operations and provide situational awareness about other operations planned in the area. (NASA Ames Research Center)
Bookshelf: Here Come the Robots
Just when I’ve been thinking about creating a robot book for children along come three!
Heavy construction machinery — bulldozers, diggers, tractors and the like — seem to have cornered the market when it comes to mechanical objects that can be made into emotionally responsive, strikingly human characters in children’s books. But what about the robots? Here in the 21st century, when our vacuums are de facto robots and our cars may well soon be too, when certain parents are as likely to dream of their child learning to code as they are to dream of their child learning Mandarin, shouldn’t robots be getting more picture-book love? (New York Times)
Opening Pandora’s AI Box in Oxford
About three months ago, Dr Simon Stringer, a leading scientist in the field of artificial intelligence at the Oxford centre for theoretical neuroscience and Artificial Intelligence, fell down some stairs and broke his leg.
The convalescence period proved unexpectedly fruitful.
Freed from the daily rigmarole of academic life, you see, Dr Stringer’s mind was able to wander. And so it was, when he least expected it, that the solution to one of the biggest challenges in artificial intelligence — the so-called binding problem — struck him out of the blue. (Iza Kaminska at FT Alphaville)
Will artificial intelligence bring us utopia or destruction?
An interesting (long read) discussion featuring Nick Bostrom’s work on AI and SuperIntelligence.
Can a digital god really be contained?
He (Bostrom) imagines machines so intelligent that merely by inspecting their own code they can extrapolate the nature of the universe and of human society, and in this way outsmart any effort to contain them. “Is it possible to build machines that are not like agents—goal-pursuing, autonomous, artificial intelligences?” he asked me. “Maybe you can design something more like an oracle that can only answer yes or no. Would that be safer? It is not so clear. There might be agent-like processes within it.” Asking a simple question—“Is it possible to convert a DeLorean into a time machine and travel to 1955?”—might trigger a cascade of action as the device tests hypotheses. What if, working through a police computer, it impounds a DeLorean that happens to be convenient to a clock tower? “In fairy tales, you have genies who grant wishes,” Bostrom said. “Almost universally, the moral of those is that if you are not extremely careful what you wish for, then what seems like it should be a great blessing turns out to be a curse.” (New Yorker)
Bank of England’s Andy Haldane warns Smart machines could take 15 million UK jobs and 80 million in the US
In an important new paper based on a speech at the trade union congress in London, Andy Haldane Chief Economist at the Bank of England and Executive Director of Monetary Analysis and Statistics has examined the history of technological unemployment in which he gave a thorough review of the literature and implications for public policy. The media will likely focus on the number of jobs that can be displaced (as I did in the title) and not necessarily Haldane’s points on new jobs being created – both of which are highly important as is ‘skilling-up’.
Andy notes that arguments about “technological unemployment” – the idea that technological advance puts people out of work and bears down on wages – have been raging for centuries. According to Andy, most evidence shows that over the broad sweep of history technological progress has not damaged jobs but rather boosted wages: “Technology has enriched labour, not immiserated it.”
However, he also notes that this broad pattern obscures the fact that there has an increasing skills premium has emerged with each passing wave of technological progress. This was especially the case in the late 20th century, as new machines such as computers began replacing not only physical but cognitive labour. He finds that each phase has eventually resulted in a “growing tree of rising skills, wages and productivity”. But they have also been associated with a “hollowing out of this tree”. Indeed, this hollowing-out of jobs has “widened and deepened with each new technological wave”. This has resulted in a widening income gap between high- and low- skilled workers.
Andy states: “By itself, a widening distribution of incomes need not imply any change in labour’s share of national income: in the past, technology’s impact on the labour share appears to have been broadly neutral. But this time could be different.”
Skipping the history parts I’ve highlighted some key points of robot and automation that will displace jobs and I agree with:
Viewed over the sweep of history, then, there is essentially no evidence to suggest technology has damaged jobs and plenty to suggest it has boosted wages. Technology has enriched labour, not immiserated it. Mill was right; Ricardo was wrong. Labour is not dead wood to be carved up between tasks. It is a tree whose trunk and branches have lengthened and thickened with time. The “lump of labour” fallacy is just that.
Or is it?
Looking more closely at past phases of rapid technological change paints a more nuanced picture. Each phase has eventually resulted in a growing tree of rising skills, wages and productivity. But they have also been associated with a “hollowing out” of this tree. Indeed, this hollowing-out has widened and deepened with each new technological wave.
Further going on to indicate:
Based on past patterns, it is argued that information technology may be poised for exponential growth, as its full fruits are harvested. Indeed, we may be on the cusp of a fourth Industrial Revolution or Second Machine Age (Brynjolfsson and McAfee (2014), Ford (2015)).
Its defining feature would be that new-age machines will be thinking as well as doing, sensing as well as sifting, adapting as well as enacting. They will thus span a much wider part of the skill distribution than ever previously. As robots extend their skill-reach, “hollowing-out” may thus be set to become ever-faster, ever-wider and ever-deeper. Or that, at least, is the picture some have painted.
How much wider and deeper? Research by Carl Benedikt Frey and Michael Osborne has tried to quantify this hollowing-out, by assigning probabilities to certain classes of job being automated over the course of the next few decades. Their work was initially done for the US, but has recently been extended to the UK (Frey and Osbourne (2013), Deloitte (2015b)).
Using this methodology, the Bank has recently done its own exercise for the UK and US. Table 3 classifies jobs three ways in the US and UK – high (greater than 66%), medium (33-66%) and low (less than 33%) probability of automation. It also shows the fraction of employment these jobs represent. Chart 27 provides a more granular breakdown of these jobs.
For the UK, roughly a third of jobs by employment fall into each category, with those occupations most at risk including administrative, clerical and production tasks. Taking the probabilities of automation, and multiplying them by the numbers employed, gives a broad brush estimate of the number of jobs potentially automatable. For the UK, that would suggest up to 15 million jobs could be at risk of automation. In the US, the corresponding figure would be 80 million jobs.
Will we have robot hairdressers and elder care robots?
No-one anytime soon is I think going to choose a robot to cut their hair – I told you the hairdressers were safe. Nor are they likely to choose a robot to look after their young children or elderly parents (tempting as that can sometimes sound). When it comes to forecasting the economy, I can quite believe a thinking machine might over time displace me. But it is less likely an “Andy Robot” will be giving this lecture to the TUC even a decade from now.
However he does clarify his vision:
Even if this diagnosis is right, it nonetheless may suggest a fundamental reorientation in the nature of work could be underway. We may already be seeing early signs of that in the move towards more flexible working, with an increased incidence of part-time working, temporary contracts and, in particular, self-employment. Some have speculated that these seismic shifts could result in the emergence of a “new artisan” class : micro-businesses offering individually-tailored products and services, personalised to the needs of customers, from healthcare and social care, to leisure products and luxuries. This really will be Back to the Future.
Yet the smarter machines become, the greater the likelihood that the space remaining for uniquely-human skills could shrink further. Machines are already undertaking tasks which were unthinkable – if not unimaginable – a decade ago. The driverless car was science fiction no more than a decade ago. Today, it is scientific fact. Algorithms are rapidly learning not just to process and problem-solve, but to perceive and even emote (Pratt (2015)).
As digital replaced analogue, perhaps artificial intelligence will one day surpass the brain’s cognitive capacity, a tipping point referred to as the “singularity” (Stanislaw (1958))). Brad Delong has speculated that, just as “peak horse” was reached in the early part of the 20th century, perhaps “peak human” could be reached during this century (Delong (2014)).