The globots are coming

Richard Baldwin’s latest book, The Globotics Revolution, is a terrific primer on two trends promising to disrupt the world of middle class work in the rich economies. One is competition from ‘Remote Intelligence’ or in other words a tidal wave of talent in countries such as China and India increasingly well able to compete with better-paid professionals in the OECD. The other is comptition from AI, increasingly well able to compete with etc etc. Combine more globalisation and robotics and you get the ‘globotics’ of the title (a terrible word, but never mind). The book argues that the combination is something new and significant in scale, more than just a bit more of existing trends.

The bulk of the book considers each of the two elements in turn, providing excellent, accessible summaries of the economic research and the projections of the likely impact on work. Some of the forces identified may not manifest as fast as expected –  the spread of autonomous vehicles, for instance. The book is also more gung-ho about the continuation of Moore’s Law than many others who pay close attention to the computer industry.

I’m also a little sceptical about the extent to which remote workers will substitute for highly paid professionals, mainly because there is something separately valuable in the know how and experience gained from face to face contact in specific places. With hindsight, it was a mistake for so much manufacturing to be offshored because of loss of engineering know how (see for example this great article by Gregory Tassey); this will be truer in services. Mancur Olson’s point in Big Bills Left on the Sidewalk – that an immigrant to a rich country from a poor one becomes more productive overnight because of the social and physical capital around them in their new environment – applies.

Even so, the bottom line is that job disruption at the lesser and slower end of the range of possibilities will still have a profound impact on people’s livelihoods. We should be getting prepared. Baldwin argues that there is no mystery about the policies needed. He argues for Denmark-style flexicurity, with ease of being fired compensated by significant transitional funding and training – or even for slowing down the pace of change by making it harder to fire people (despite the evidence this contributes to high unemployment rates). With the need to prepare – and to implement far more effective policies than was the case in the earlier phases of deindustrialisation and automation – it’s surely impossible to disagree.

The book ends on an oddly positive note, given the jobs-ocalypse it predicts: “I am optimistic about the long run.” In the very long term it forsees an economy where the things machines (and I guess offshore workers) cannot do: more local, more human and more prosperous (thanks, robots!) society. “Our work lives will be filled with far more caring, sharing, understanding, creating, empathizing, innovating and managing …. The sense of belonging to a community will rise and people will support each other.” This is wonderfully upbeat, a world where machines do all the drudge work and humans brew craft beer and care for each other. It’s hard to see how to get there from today’s fractious world where the absence of a sense of community is pretty manifest in many places and only the few can afford the craft beer. I hope he’s right, though.

Agree with the book’s rosy long-term vision or not, it’s a thorough introduction to the economic debates about globalization and automation, and the forces that are going to change our world in the next few decades, populist backlask or no.

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Vision and serendipity

As the year hurtles toward its end, and what looks sure to be a tumultuous 2019, I’ve been retreating under the duvet with Mitchell Waldrop’s The Dream Machine, published in a handsome edition by Stripe Press. The book is a history of the early years of the computer industry in the US, centred around JCR Licklider and his vision of human-computer symbiosis.

It has therefore quite a narrow focus, being a detailed history of the people involved in a small slice of the effort that went into creating today’s connected, online world. Licklider played a decisive role at DARPA in prompting and funding the creation of the Arpanet and hence ultimately the Internet. I got quite caught up in the detail – the triumphs and setbacks of particular researchers, their job moves, who fell out with whom, and so on. (Better than the painful minutiae of our Brexit humiliation, for sure.)

One of the striking aspects of the tale is how serendipitous the outcomes were. There are some popular Whig interpretations of digital innovation, as if the creation of the personal computer, GUI, Internet etc were purposive. It wasn’t like that at all. Licklider for sure had a vision. It might or might not have worked. It was sort of chance that he ended up in DARPA with his hands on a suitable budget to fund the networking. It certainly wasn’t an intentional US government industrial strategy, as some accounts would have it. The Dream Machine was a Heath Robinson contraption. There are lessons in such histories both for scholars of innovation and for would-be industrial strategists.

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Humanity’s future…

I read On the Future: Prospects for Humanity on the train back from the Festival of Economics. (See the #EconomicsFest hashtag – recordings will go online soon.) This short and compelling book by Martin Rees, the Astronomer Royal (and a Cambridge colleague), was a bit of a dampener on my good cheer. Our prospects are not great. It turns out that the risk of a large asteroid causing mass extinction is one of the lesser worries about our future. Other existential risks have a higher probability with the same mass death/end of civilisation impact.

Take biotech terrorism: “Whatever can be done will be done by someone, somewhere,” the book calmly states in passing. Even more exotically, another: “Scary possibility is that the quarks [produced by high energy physics experiments] would reassemble themselves into compressed objects called strangelets. That in itself would be harmless. However, under some hypotheses, a strangelet could, by contagion, convert anythign else it encountered into a new form of matter, transforming the entire Earth into a hyperdense sphere about a hundred meters across.” I gather this is a remote prospect indeed, but it takes some of the gloss off the Large Hadron Collider. Strangelets, eh.

The early scientists (natural philosophers, as they called themselves) were considered ‘merchants of light’ yet science and technology have come to seem pretty scary. This book is a perfect antidote to worrying about Brexit or Donald Trump or neo-fascism, as it offers so many much bigger problems to worry about.

It tries to strike a positive note by saying science and tech offer potential solutions too. Martin Rees thus ends by calling for scientists to engage more with philosophy. I think they should be engaging more with social scientists. The barriers to taking action to safeguard humanity from any devastating effects of climate change or AI are not mainly about science and technology, but rather about what people believe and how they behave.

 

 

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Made by Humans: the AI condition is very human indeed

A guest review by Benjamin Mitra-Kahn, Chief Economist, IP Australia

There is a lot of press about the coming – or going – of artificial intelligence, and in Made By Humans: The AI Condition  Ellen Broad has written a short but comprehensive account of the state-of-play which deserves to be read by anyone wanting to know what is happening in AI today, certainly if you want to get in on the conversation.

The book is very contemporary, and if you haven’t had the time to attend every conference and workshop on AI since 2015, then you’re in luck. Broad has been to them all, and this book will catch you up on all the developments. The book also offers a series of insights into the challenges that AI and big data present – because it is about both – and the questions we should ask ourselves. These are not the humdrum questions such as who a self-driving car should choose to crash into (although a randomized element is suggested), but some bigger and much more interesting questions about whether we need to be able to inspect the algorithm that made the decision. Does the algorithm need to be open source or does it need to be exposed to expert review to ensure best practice, and should the data that trained the algorithm be openly accessible or available for peer-review. Using every example about data and AI from the last three years, Broad steps through the issues under the hood that are only now being thought about.

This naturally brings up the question of government regulation. This is something Broad has changed her mind about, which she discusses openly in a book that moves between a technology story, personal discovery and ethical discussions. There is a role for regulation says Broad, and the fact that we don’t yet know what that regulation could be, or should be, is handled with some elegance. Technology is not a nirvana , computer code sometimes held together with “peanut butter and goblins” and written by people who are busy, under-funded or just average. Simply aiming to ‘regulate AI’ however is akin to wanting to regulate medicine: It is complex, dependent on who you impact, their ability to engage, and the risks as well as the situation. It is a human-to-human decision ultimately. Not perhaps the argument one expects in a book on AI by the ex-director of policy for the Open Data Institute and previous head of the Australian Digital Alliance. But it is about humans, and the AI condition is about humanity – about fairness, intelligibility, openness and diversity according to Broad.

The book finishes with US Senators questioning Facebook about Cambridge Analytica, and the recent implementation of the GDPR (data governance, not a new measure of GDP), which quickly dates the book, but that is a choice the author makes explicitly. This book is about the current conversation on big data and AI, and it is about participating in that conversation. It is not about the last 50 years of ethics and the history of computers. There is an urgency to the writing, and as someone interested in this, I found myself updated in places, and challenged in others. Reading this book will allow anyone to particpate in the AI debate, knowing what Rahimi’s warning about Alchemy and AI is, being able to discuss the problems around the COMPAS sentencing software, or seeing why Volkswagen’s pollution scandal was a data and software scandal first. If this is a conversation you want to engage with, Broad’s book is an excellent starting point and update.

 

 

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Work (and more) in digital times

This week I’ve been dipping in to Work in the Digital Age: Challenges of the Fourth Industrial Revolution, edited by Neufeind, O’Reilly and Ranft. This is a collection of short essays brought togoether by Policy Network, the centre-left ‘progressive’ think tank. It’s a chunky book, starting with sections essays on prospects for employment and the character of work. These cover, for example, the likely impact of automation in destroying and creating jobs, and the nature of work in the ‘gig’ economy. A section on labour relations and the welfare state follows. There are then chapters on individual European countries, ordered according to the ‘digital density’: Scandinavia and the Netherlands are classed as high, the UK and Germany medium, France, Italy and Central and Eastern Europe as low. There are also chapters on the US, Canada and India. The comparisons between countries were at the heart of the project, and I admit to not having read these chapters.

Given that I read so much of the economic literature on these issues, I haven’t found anything startlingly new so far, although there are some interesting perspectives. For example Martin Kenney and John Zysman consider the question of financing technology start-ups when they face a long period of losses because of what’s known in the platform literature as the chicken and egg problem: a platform needs users on both sides – riders as well as drivers for instance – because it won’t attract riders without enough drives and won’t have enough drivers unless it has a user base. The winner-take-all success stories then look for a long period of rents to recover those early losses, although many platforms simply fail. The essay argues that it is not clear whether this financing model is creating economic and social value. (I argue in a forthcoming paper that this is one aspect of the wider failure of competition economics to have figured out how to compare static welfare gains and losses to dynamic ones.)

In other chapters, Ursula Huws et al report new surveys on the extent of gig work or crowd work – from 9% in the UK to 22% in Italy, usually as part of a broader spectrum of casual work; Monique Kremer and Robert Went set out an agenda for ensuring automation does not increase inequality, covering the direction of robotisation, the enhancement of complementary skills, and distributional policy instruments; and in an introductory essay Luc Soete on the productivity paradox discusses similarities with and differences from previous technological revolutions. The final chapter sets out a reform agenda – education and training; work transitions; social protection; redistributive taxes and transfers; and investing in infrastructure and innovation. This is high level stuff, and therefore a bit motherhood and apple pie. Having contributed essays to this kind of collection myself, I know this pitch of generality is inevitable, but do ache for some policy specifics as opposed to ‘a new inclusive narrative’.

For an overview of the technology and work debate, this is a useful volume, though, and it can be downloaded free from here. It’s certainly a good place to start for a comparative perspective, and the references to country-specific literature look really useful.

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