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 [amazon_link id=”0300213557″ target=”_blank” ]Humans Need Not Apply: A Guide to Wealth and Work in the Age of Artificial Intelligence[/amazon_link] 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 [amazon_link id=”0241003636″ target=”_blank” ]Flash Boys[/amazon_link]. 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, [amazon_link id=”000752076X” target=”_blank” ]Who Gets What and Why[/amazon_link], 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.

Machines and humans

A couple of interesting tech-related books have arrived. I’ve started [amazon_link id=”0300213557″ target=”_blank” ]Humans Need Not Apply: A guide to work and wealth in the age of artificial intelligence[/amazon_link] by Jerry Kaplan & am enjoying it. He is a tech entrepreneur now teaching at Standford’s computer science department. The book starts with a useful overview of the history of AI, which is as far as I’ve got. It’s very engagingly written and is good at bringing the subject to life.

[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]

The other is [amazon_link id=”0262029510″ target=”_blank” ]A Prehistory of the Cloud[/amazon_link] by Tung-Hui Hu, which looks fascinating, a part of the history of the internet that is rather unfamiliar. For example, there’s a chapter on data centers. I’m fascinated by the relationship between the embodied and the disembodied parts of the networks & we know so little about the buildings and wires. There is [amazon_link id=”014104909X” target=”_blank” ]Tubes: Behind the Scenes at the Internet [/amazon_link], which was a good read but disappointed me in terms of hard information. So I’m looking forward to reading this new book. Paging through, it clearly covers social and institutional issues as well as the technology – or in other words the humans too.

[amazon_image id=”0262029510″ link=”true” target=”_blank” size=”medium” ]A Prehistory of the Cloud[/amazon_image]

Which way to the future?

I’ve enjoyed reading Bernard Carlson’s [amazon_link id=”0691165610″ target=”_blank” ]Tesla: Inventor of the Electrical Age[/amazon_link] (although, as I confessed, skipping over the physics). How exhilarating to read about the exceitement as thousands of people crammed into lecture halls to hear Tesla speak about his discoveries. “The demand for seats was so great that tickets were being scalped outside the hall for three to five dollars,” Carlson writes of an 1893 lecture in St Louis (that’s $80-130 in today’s dollars).

[amazon_image id=”0691165610″ link=”true” target=”_blank” size=”medium” ]Tesla: Inventor of the Electrical Age[/amazon_image]

The book is particularly interesting on the lack of form and direction in the early stages of commercial development of a new technology. Standards had not been agreed. Different technical approaches seemed equally viable. Companies were forming – and going into receivership – and the investment risk was substantial. Rich investors (hello J.P.Morgan) were trying to corner new markets. Patent litigation was common.Tough choices had to be made between promoting ideas and licensing the patents versus holding patents and going into manufacturing.

In this confusion, sober analysis was insufficient to make technical and financial choices. What Carlson calls ‘illusion’, the building of sufficient belief in a single path to the future, was critical: “We need to understand and appreciate how inventors and entrepreneurs forge relationships that foster a balance between imagination and analysis.” The inventor has to inspire his (or her) backer, the businessman has to keep the creative genius grounded (no pun intended). One could see it as creating the focal point in a game with many possible outcomes, and hence sometimes the phenomenon of [amazon_link id=”0141031638″ target=”_blank” ]lock-in[/amazon_link] to what might be not the best technical outcome.

So, a fascinating read on the early development of an important new technology, as well as an extraordinary character. As the book observes, there was always a kind of minority interest in Tesla, a real maverick; but he deserves this fine biography.

Investing in electric dreams

I’ve got some way into Bernard Carlson’s book [amazon_link id=”0691165610″ target=”_blank” ]Tesla: Inventor of the Electrical Age, [/amazon_link]which is out in paperback now. It’s very interesting, although the physics washes over me. The difference between a rotor, a stator, a transformer and a conductor? It just doesn’t stick. It must be like this for non-economists reading about economics. Anyway, the terms make sense once if you concentrate really hard but then just evaporate from the mind.

[amazon_image id=”0691165610″ link=”true” target=”_blank” size=”medium” ]Tesla: Inventor of the Electrical Age[/amazon_image]

On the other hand, I’m finding the depiction of the early electrical industry in the US and Europe very interesting – the fierce competition, patenting of different approaches, seriously risky capital investment, the uncertainty over what would emerge as an industry standard, the dastardliness of some rich investors, the works.

One chapter describes Tesla’s early investors and how they got interested in electricity. One had started with a telegraph line between Washington DC and Chicago: “Peck discovered that there were banks and merchants who were interested in leasing dedicated wires in order to conduct their business securely.” So, as now, the finance industry was a big customer of the new technologies.

I also liked this parallel with modern times: Tesla persuaded his investors to provide more funds with a demo involving spinning an egg on its pointy end on a wooden table thanks to some electrical whatevs underneath. They loved it. “This episode taught Tesla that invention would require a degree of showmanship in order to create the right illusions about his creations. People do not invest in inventions built out of tin cans; they invest in projects that capture their imagination.”

And, to my delight in these early chapters, Tesla turns out to have got his start at the Ganz electrical works in Budapest. I visited the factory in early 1990, when it took immediate advantage of the collapse of communism to look for western investors, and hired a stockbroker from London who took some journalists (including me) on a trip. It was fascinating. The managing director’s secretary had the only key to the cupboard in which the toilet paper was kept so she knew exactly when everybody in the party had to go – clearly a powerful woman in the enterprise. The factory itself was ginormous and took in steel, ore and coal at one end and turned out trams and ligh bulbs at the other end. Spectacular. Monstroously inefficient.

I’m 4 chapters in. Have always loved this image of Tesla.

Nikola Tesla

Nikola Tesla

Robots for the people

In between Lionel Davidson’s cracking 1994 thriller – recently reissued – [amazon_link id=”0571324215″ target=”_blank” ]Kolymsky Heights[/amazon_link] and Colum McCann’s moving novel [amazon_link id=”0812973992″ target=”_blank” ]Let the Great World Spin[/amazon_link], I read (at last) Martin Ford’s [amazon_link id=”0465059996″ target=”_blank” ]Rise of the Robots: Technology and the Threat of a Jobless Future[/amazon_link]. 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 theĀ [amazon_link id=”0812928504″ target=”_blank” ]’Downsizing of America'[/amazon_link] 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, [amazon_link id=”B00I2WNYJW” target=”_blank” ]Thomas Piketty’s tome[/amazon_link] on inequality hardly mentioned technology amid its quotations from [amazon_link id=”0192835696″ target=”_blank” ]Balzac[/amazon_link] and [amazon_link id=”0747549079″ target=”_blank” ]Austen[/amazon_link], but it did plant this issue firmly at the centre of policy debates. Tony Atkinson’s impressive book [amazon_link id=”0674504763″ target=”_blank” ]Inequality[/amazon_link] 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, [amazon_link id=”1480574732″ target=”_blank” ]Rise of the Robots[/amazon_link] 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 [amazon_link id=”B00D97HPQI” target=”_blank” ]The Second Machine Age[/amazon_link]. 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.