I’ve chatted to Martin Ford about his new book Rule of the Robots for a Bristol Festival of Ideas event – the recording will be out on 6 October.
It’s a good read and quite a balanced perspective on both the benefits and costs of increasingly widespread use of AI, so a useful intro to the debates for anyone who wants an entry into the subject. There are lots of examples of applications with huge promise such as drug discovery. The book also looks at potential job losses from automation and issues such as data bias.
It doesn’t much address policy questions with the exception of arguing in favour of UBI. Regular readers of this blog will know I’m not a fan, as UBI seems like the ultimate Silicon Valley, individualist, solution to a Silicon Valley problem. I’d advocate policies to tilt the direction of automation, as there’s a pecuniary externality: individual firms don’t factor in the aggregate demand effects of their own cost-reduction investments. And also policies that address collective needs – public services, public transport, as well as a fair and sufficiently generous benefits system. No UBI in practice would ever be set high enough to address poverty and the lack of good jobs: if you want to pay everyone anything like average income, you’d have to collect taxes at a level more than average income.
But that debate is what the Bristol event is all about!
I confess to having read a couple of novels this week (The Truth About the Harry Quebert Affair and Tokyo Year Zero) but prior to this, on my travels to and from Italy, I read George Packer’s Last Best Hope: America in Crisis and Renewal. I’d bought it because his big book on US decline, The Unwinding, was so good. This is a short diagnosis of the US as a failed state ending with – despite everything – a positive vision of how to get to the renewal part. In this, Packer casts back to the New Deal and Great Society, particularly some of its relatively unknown architects (Frances Perkins, Bayard Rustin).
It was striking how US-specific the diagnosis is, even though so many of the headwinds are experienced elsewhere – deindustrialisation, geopolitical pressures, demographic and therefore political change, etxreme inequality. I think it is probably because the US is today, like Britain at the start of the 20th century, in such a highly distinctive situation. The same tides are washing over different sandcastles.
One surprise was finding myself sharing a theory of change with Milton Friedman. Quoted here, Friedman wrote: “Only a crisis brings – actual or perceived – produces real change. When that crisis occurs, the actions that are taken depend on the ideas that are lying around. That I believe is our basic function: to develop alternatives to existing policies, to keep them alive and available until the politically impossible becomes the politically inevitable.”
Anyway, Last Best Hope explores previous crises in order to identify what alternatives might now reduce divisions and restore democracy in the US. For all that Packer tries to end on an upbeat note, I’m not sure I believe this is possible. For those of us who grew up with the positive vision of American dynamism, egalitarianism, and opportunity (alongside all its obvious terrible flaws), this is pretty depressing. As Adam Tooze concludes his excellent new book, Shutdown (which I’ve reviewed for Democracy, due to be online soon), history has come for us all.
For the first time in a year I managed to get abroad for a few days – the Ambrosetti Forum at the Villa D’Este on Lake Como – and apart from the inherent joy of being somewhere beautiful and sunny and foreign, it gave me plenty of reading time. One of the books I polished off is Kate Crawford’s excellent Atlas of AI. It’s a forensic exploration of the unseen structures shaping the way AI is being developed and deployed in the world, and it is fair to say she is prfoundly sceptical about whether ‘actually existing AI’ is serving society broadly as opposed to making a small minority of (mainly) men rich and powerful. “To understand how AI is fundamentally political,” she writes in the introduction, we need to go beyond neural nets and statistical pattern recognition to instead ask what is being optimized, and for whom, and who gets to decide.”
The book starts with the material basis of the industry, in particular the extraction of rare earths and its voracious and growing consumption of energy. We all surely know about the energy appetite of crypto but one point I hadn’t really appreciated is this: “The amount of compute used to train a single AI model has increased by a factor of ten every year.” The next chapter goes on to discuss the extent to which AI depends on low-cost human labour. I think the way Amazon’s Mechanical Turk works is quite well known – a nice book about this was Ghost Work – but this chapter focuses on Amazon warehouses, image-labelling work (“the technical AI research community relies on cheap crowd-sourced labour for many tasks that can’t be done by machine”), and also – nice neologism – ‘fauxtomation’ when tasks are transferred from human workers to human customers: think ‘automated’ checkouts in shops. The chapter has a nice section discussing the role of time in business models: in an evolution of the industrial organisation of time, the continuing automation of economic activity is requiring humans to work ever-faster. The battle is for ‘time sovereignity’.
There is not surprisingly a chapter on data, underlining the point that it is profoundly relational, but also making the point that the reliance on ‘data’ downgrades other forms of knowledge, such as linguistic principles, and how little questioning there is of where it comes from and what it actually measures. I hadn’t realised that many computer science departments have not had ethical review processes on the basis that they do not have human subjects for their research. It’s also a bit of a shocker to realise that some widely used AI databases are palimpsests of older collections of data embedding unpalatable classifications and assumptions.
There’s a similarly shocking chapter on facial recognition – bad enough in the ungoverned way it’s being used but I hadn’t clocked the latest trend of using it to “identify” people’s moods. And the book winds up back at power. As Crawford writes, “We must focus less on ethics and more on power.” I couldn’t agree more. There are a gazillion ethics statements and loads of ethics research but it won’t change anything. I’d add incentives too, but given the concentration of all that compute, understanding the way AI and power structures interact will shape the kind of world we are in 10 years from now. Excellent book.
Mountain Tales: Love and Loss in the Municipality of Castaway Belongings by Saumya Roy is an absolutely gripping read, but don’t expect a happy ending. (The book is called Castaway Mountain in the US.) It’s a sort of soap opera about an extended family and community who eke out their living as pickers sorting through the giant Mumbai waste mountains of Deonar. Braided with the events of their lives is the sorry tale of the city’s inability to tackle the toxic and dangerous waste, despite court cases charging them with taking action. CIty and state governments can’t agree, money runs out, for years nothing happens. Meanwhile fires break out covering the whole city in a cloud of dangerous particles and smoke, toxins leach into the water, and the giant and growing metropolis simply dumps everything from medical waste to rotting food to plastic bags and broken glass. Needless to say, accidents and illness feature prominently. So does gang violence, lack of schooling, hunger and poverty.
The author came across the community of pickers through a micro-credit agency she co-founded in 2010, and the tale stretches over several years. The book makes one feel rather helpless: the characters featured simply pile up more debt, or borrow elsewhere to repay the micro-loans. Weddings and illnesses chew up all available resources and lead to more debt. The local government is clearly incapable. And even if they could close and remedy the waste mountain (as clearly they should before a major disaster strikes), how would the pickers earn at all? So this is not an easy read, compelling as it is, and the book is not in the solutions-finding business. It is a clear-eyed, sympathetic but realistic, description of a way of life none of its readers could have imagined. And even though I’m no hoarder of stuff, it also made me determined to send even less waste to landfill. How much more plastic do we need to throw away?
I recently re-read Joseph Stiglitz and Bruce Greenwald’s (2014) Creating a Learning Society: A New Approach to Growth, Development and Social Progress (slightly amazed at how many years ago it was published, as I remember hearing Joe Stiglitz give a talk about it in Toulouse when it was just out. Seems much more recent in memory.)
It’s a masterly reframing of how to think about economic development and importantly appropriate policies in terms of quite simple models that are completely compatible with mainstream economics. The policy mix runs counter to what one could describe as conventional (mainstream) wisdom. The book advocates strategic industrial policy – because the models all involve hysteresis, so history matters and policymakers need to think about the path from here to the future; less extreme (albeit enfroced) IP rights because creating the incentive to innovate from a given pool of knowledge has to be traded off against a smaller pool of knowledge; trade/infant industry protection because learning by doing and learning from experience make production important to grow the pool of knowledge. The message about market structure – competition/concentration and static vs dynamic efficiency – is that it’s complicated. There’s no simple relationship.
Above all, when technology is endogenous there can be no presumption that market outcomes are efficient, and policies need to think about how firms and society learn, and not just about allocative efficiency. It’s a great book for students because it demonstrates how to use models to think about complex policy options, and also that it is not bad economics to challenge market first-ism. Although pitched at developing economies, I went back to it to think about the levelling up challenge within the UK economy. Knowledge sticks to people, who stick in places, and as it accumulates places can diverge a lot over time. Given that innovation also requires adequate scale and some means of mitigating the uninsurable risks associated with it, the need for significant policy interventions seems clear to me.