Humans need not apply

As one would of course expect from the economics correspondent of The Economist, Ryan Avent has written a very clear account of the way digital technologies, and the globalisation driven in part by technology, is changing the ways people can earn a living. The Wealth of Humans: Work and its Absence in the 21st Century brings together the debate about robots destroying jobs, arguments about the ‘death of distance’ and literature on the re-emergence of cities as economic hubs, the issue of inequality, and the more recent discussion of whether or not the world is in for an era of ‘secular stagnation’. The focus is on three related trends: automation, globalization, and the enhanced productivity of a highly skilled minority of people.

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It ends up being a rather pessimistic synthesis. The starting point is unarguable: “Society must go through a period of wrenching political change before it can agree on a broadly acceptable social system for sharing the fruits of this new technological world.” A few years ago this would have seemed hyperbole, but no more. And yet the rest of the book tends to suggest that this political change cannot happen. Essentially, Avent does not believe enough people can become educated or skilled enough to share the benefits of automation and globalisation with those happy few whose cognitive skills have made their incomes increase. He does not think as many as 50% can complete tertiary education. “The proportion of highly educated workers to less educated workers is no longer going to grow in the growth-boosting, inequality-dampening way it once did.”

Part of this, I’d take issue with. I don’t agree that skill upgrading has ‘run out of steam’. The character of tertiary education clearly needs to change; we are in a stage like the persistence of classical education in the late 19th century. The educational establishment is slow to change – but it will, or it will be disrupted. But I’m much more persuaded by James Bessen’s argument (in Learning by Doing) that in the later stages of the technological transformation of production, the necessary skills are steadily standardised and thus able to be codified and taught. And, while addressing the ‘lump of labour’ fallacy, Avent nevertheless argues that, “The problem is the sheer abundance of labour.” Yet he also sees technology replacing ‘expensive’ labour. Surely labour=people=knowledge, pretty key in an endogenous growth, knowledge-based economy. It seems more likely that ‘work’ will be redefined, with a role for appropriately skilled humans, as it has been so many times before.

There are some very nice details indeed in the book. I didn’t know that Robert Gordon used to ask audiences whether they would rather give up post-2000 technology or indoor plumbing – the answer used to be the former, until smartphones came along. And indeed in the developing world, people would clearly rather have their phones and the internet. (An aside: indoor plumbing is a great example of why technology is social more than it’s technological. It’s a simple and well-known technology, yet one many countries are unable to make work for them.) Arvind Subramanian’s term ‘fluff not stuff’ for weightlessness (cf The Weightless World) was new to me, although perhaps a little too derogatory-sounding for the source of most of the value-added in developed economies.

Avent concludes that the reason to be pessimistic is that there is ‘no-one in control’, able to pilot society wisely through the upheaval. Looking back over the past 200 years, someone thinking they are ‘in control’ seems a pretty bad idea to me. But, to get back to the starting point, the politics, I’d agree that this is the territory for pessimism. Where leadership to generate a sense of progress and confidence would be desirable (because expectations matter no end for the economy), we have politicians reacting to people’s fears. It’s understandable, but it isn’t what we need.

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Think yourself lucky

Robert Frank’s new book is a nice, brief overview of why luck plays such a big role in an individual’s economic success (or otherwise).

[amazon_image id=”0691167400″ link=”true” target=”_blank” size=”medium” ]Success and Luck: Good Fortune and the Myth of Meritocracy[/amazon_image]

This very readable book canters through some of the key evidence on how economic success depends on chance, amplified by phenomena such as winner take all markets, and by policy. Mainly, though, it is another pitch for Frank’s favourite policy prescription of a progressive consumption tax, something he’s been advocating since , and possibly before. As in those books, he relies here on the argument that much consumption consists of positional spending and the ‘arms races’ need to be limited by policy intervention.

I’m not persuaded about the consumption tax idea, because when you ask policymakers to select luxury goods will probably choose something that might be a luxury now but will become a useful mass market product. Remember Norman Lamont in 1991 taxing mobile phones as yuppie status symbols – which indeed they were at the time. (“I turn now to what I regard as one of the greatest scourges of modern life. I refer to the mobile telephone. I propose to bring the benefit of car phones into income tax and to simplify the tax treatment of mobile phones by introducing a standard charge on the private use of such phones provided by an employer. Tax will be paid of £200 for each phone for 1991-92. I hope that, as a result of this measure, restaurants will be quieter and the roads will be safer.” Budget speech 19 March 1991.) One could be on safer ground with, say, gold leaf covered sports cars, but even so my preference is for progressive income and especially property taxes.

Still, the reminder about the important role of luck is welcome, although it is surely neither wholly necessary nor sufficient for economic success. The most important conclusion to my mind is the negative one that people who are poor are most likely unlucky, whether that be in terms of their parents’ income and status or the quality of their school and neighbourhood, and poverty or unemployment can’t be blamed on laziness. As Julia Unwin pointed out so eloquently in , we often make unjustified moral judgements about poor people out of fear; we need to recognise the bad hand life has dealt them.

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Thinking, learning and doing

James Bessen’s book is excellent. It strikes a balance between meaty analysis and description of historical episodes of technical change, and is at the same time very accessible.

[amazon_image id=”0300195664″ link=”true” target=”_blank” size=”medium” ]Learning by Doing: The Real Connection Between Innovation, Wages, and Wealth[/amazon_image]

The book argues that it is important to distinguish between ideas, which can be codified and transmitted and know-how attached to workers, which takes experience to accumulate. This is familiar – Paul Romer recently blogged about the role played by this distinction in his famous model. But Bessen adds that the distinction makes it important to consider the incentives for workers to invest in new skills so that new technologies can be implemented – and the part played by these incentives is usually overlooked and yet crucial for forming views about the “future of work” when there are ubiquitous robots.

He uses the historical examples to demonstrate that in the early stages of implementation of a technology, returns to workers with generally high skills will rise. They are able to make the adjustments and minor additional innovations that get the big innovation to work. During that period, the wages of ordinary workers stagnate – as in the famous Engels’ Pause (pdf). However, when the technology is thoroughly bedded in and the technical knowledge needed to work with it is standardised, ordinary workers have the incentive to invest in in gaining skills and experience. A thick labour market develops. Workers are able to threaten credibly to switch jobs. Their real wages rise and the high-level skill premium narrows.

“The specific skills associated with a major new technology are not standardized at first, which limits the market. Initially, these skills are always limited to specific employers.'”

He emphasises the need for the necessary technical knowledge to be standardised too – the example he uses is the periodic table’s invention, standardising the chemical knowledge workers in the growing industry needed, and making it easier to teach.

Bessen then uses some new examples to demonstrate that with digital technologies, this standardisation of technology, tasks and skills has not yet happened. His example is digital publishing, where the specifics of the technology are still changing, and so do the specific technical knowledge and experience needed.

In addition to the development of a standardised know-how labour market on demand and supply sides, Bessen points out that new technologies can also raise demand and employment in existing work. His example here is the continuing increase in the number of bank tellers (still going on) even as the number of ATMs grew rapidly, with the humans’ tasks changing to focus on customer relations, and the number of bank branches and transactions increasing. This is not the case with all technologies – the job market for people making oil lanterns is tiny – but the book suggests it happens more often than one would think.

The book ends with policy reflections, of which the most interesting concerns education. The reasoning about standardised knowledge, and the importance of experience, as a technology matures points to the need for skills-focused education rather than piling as many young people as possible through conventional academic tertiary education. Bessen argues that demands to make vocational jobs such as nursing or medical assistants require a university degree represent a form of job protectionism. He also – along with many other scholars – points to the dysfunctional nature of the patent/copyright system as it operates now, especially in the US.

This is a very US-focused book, but none the less interesting for that. This review has skimmed over the top of the argument; I’d strongly recommend the book to anyone interested in the automation/inequality/employment issues. It is a broadly optimistic perspective but does underline the length of the transition and the likely impact on individuals. All the more reason to pay attention to the policy implications.

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Slightly scary AI

On the whole I haven’t been among the most pessimistic people about the likely impact of a potential Artificial Intelligence revolution on the economy and life – although not blithely optimistic either about the scale of the adjustment that will be needed in labour markets and education. But by Jerry Kaplan has made me more apprehensive. This is not because of anything he writes about the economy, which is standard fare, but rather because of something he says about AI in the first half of the book (quite a short and very readable volume).

[amazon_image id=”0300213557″ link=”true” target=”_blank” size=”medium” ]Humans Need Not Apply: A Guide to Wealth and Work in the Age of Artificial Intelligence[/amazon_image]

It starts with an account of high frequency trading and the Flash Crash of 2010. This will be familiar to anybody who has read Michael Lewis’s very entertaining . It seems pretty clear to me that financial regulators need to rein in HFT – not that they are showing any sign of interest in doing so – and there is even a proposed solution recommended in Al Roth’s terrific book about market structure, , as well as in this volume. That is to regulate to allow computer trading to occur only once every second. This would re-create liquidity in the markets (which are illiquid at the milli- or nano-second timescale) and stop the speed arms race.

However, what Kaplan points out is that other AI applications will have undesirable consequences because they will look like the swarms of computers trading in financial markets, and doing it super-well with no application of judgment. One example is the use of AI to personalize the offers made to shoppers online, which will become so efficient that the synthetic intelligence will be able to price discriminate perfectly, extract all the consumer surplus in each market, and undo the hope that online retailing would lead to less rather than more price dispersion. Nobody will be forced to buy, of course. “But while you may exercise freedom as an individual, collectively we will not. Synthetic intellects are fully capable of managing the behaviour of groups to a fine statistical precision while permitting individuals to roam in whatever direction their predictable little hearts desire.”

The book asks many other thought-provoking questions about social norms and ethics. Will my personal robot be allowed to stand in a queue for me? Or repark my car to avoid tickets all day? How can we ensure robots understand what are the moral boundaries on their actions when they’ve been programmed to fulfil a certain kind of task?

It also has one interesting policy suggestion, the “job mortgage”, a means of allowing people to train and retrain without being tied to one specific employer: the government loans people money and is repaid from their subsequent earnings. This would replace the existing student loan schemes and apprenticeships, which Kaplan sees as too restrictive for the period of upheaval ahead.

There seem to be lots of books on this subject out now, but I thought this one worth a read, especially for an economist like me, as the author’s background is a technical one and he explains the technology trends very clearly.

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Robots for the people

In between Lionel Davidson’s cracking 1994 thriller – recently reissued – and Colum McCann’s moving novel , I read (at last) Martin Ford’s . It’s good to see it made the FT Business Book Prize long list, amid terrific company.

[amazon_image id=”0465059996″ link=”true” target=”_blank” size=”medium” ]Rise of the Robots: Technology and the Threat of a Jobless Future[/amazon_image]

As one of the economists Ford has a go at in the book, I don’t believe the challenge is one of the total number of jobs jobs. These periodic waves of concern about where all the jobs are going to come from tend to prefigure a wave of job creation. It happened in the 1960s, following publication in 1964 of the ‘Triple Revolution’ report in the US, and it happened again in the 1990s after the  report in 1992. This time might be different, as Ford and so many others argue, but repeatedly over 250 years capitalist economies have shown their capacity for creating new forms of work when old forms become redundant for technological or other reasons.

Indeed, at present in the US and UK there is little sign of any direct impact of automation at all. Employment rates are high, and low labour and total factor productivity signal the absence of a significant technological impact on growth and jobs. We have too few robots, not too many. There are some significant data issues here, but that includes the question of measuring jobs in the digital economy – as often noted, Google has far fewer employees than GM, but Mike Mandel has pointed out that the statistics are not counting the extent of job creation in smaller businesses.

That’s not to say there are no challenges from robotisation. Almost as often as they have adapted, capitalist economies have proven themselves bad at the process of transition. The huge wave of automation in manufacturing in the 1980s and 1990s, the deindustrialisation and globalisation, destroyed communities and left successive generations out of work, in poverty, and scarred by the nexus of social problems experienced by so many former mill or mining towns. There is also the question of income distribution. As Ford points out, on inequality hardly mentioned technology amid its quotations from and , but it did plant this issue firmly at the centre of policy debates. Tony Atkinson’s impressive book had a detailed list of policy responses. The winners from technology will need to share the benefits if our societies are to thrive.

So I certainly don’t dismiss techno-fears, but I do think “we’re all going to be unemployed” is the wrong way to frame the problems. Having said that, is a thorough review of the impact of digital technologies on a number of areas. It covers the likely breakthroughs such as AI and driverless vehicles, going over the exponential pattern as Brynjolfsson and McAfee do in their book . Ford has chapters on industries such as health and higher education, where the impact of digital disruption has yet to be experienced.

He raises some interesting questions. For example: “Should the population at large have some sort of claim on [the] accumulated technological balance?” Meaning the vast social and public investment in research and innovation, on which the new digital fortunes are piggybacking. The answer to that is surely yes. There is also the implication of the machines’ greater ability to know what we know: no human an be aware of all research, past or present, but something like IBM Watson can be.

There is a great example in the book of two almost simultaneous cases of patients presenting themselves at different hospitals with mysterious diseases. One almost died during a heart operation, the doctors puzzled as to the diagnosis. Another was correctly diagnosed and treated because the doctor happened to have seen the same mystery symptoms on the TV series House. A smart enough computer would have known without having to have serendipitously watched the right TV programme. Ford seems to see this as a threat, but surely there is only benefit in this ability to pool past human knowledge? And I’m not persuaded that computers are yet anywhere near creating new knowledge however magical they are at collating and making sense of past knowledge. They are standing on the shoulders of human giants, absorbing humanity’s existing intellectual assets.

Well, maybe I’m delusionally optimistic. Ford ends the book with figures from the BLS. Between 1998 and 2013, there was a 42% real increase in US GDP, but no increase in the total hours worked. He thinks that’s a bad thing. I think it’s a good one – with the huge proviso that the benefits of growth must be widely shared. They haven’t been. We don’t have the people’s robots. That’s the real problem.

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