Tag Archives: political economy

From woolly to concrete liberalism

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I got round at last to reading Abundance by Ezra Klein and Derek Thompson, and enjoyed the book. It’s a good read and makes its case well. The pro-growth case has traction beyond the US of course. UK ministers have been on about planning regulations hampering growth ever since the July 2024 election, and a John Collison article in the Irish Times recently got the Irish chatterati talking about it.

Did I agree with the case? Yes and no. I do think restarting economic growth – in an environmentally increasingly sustainable way – is essential. Social and political phenomena have many causes so the electoral success of far right populism (anathema to me as an old fashioned woolly liberal) is not caused in a simple way by the absence of growth since the mid-2000s. But that absence is certainly part of the story. My views about this have long been shaped by my PhD adviser Ben Friedman, and his book The Moral Consequences of Economic Growth. (As for the sustainability component – of course that’s essential, but I can’t think of any far right party/government that is not claiming climate change is a hoax. So significant political change has to come first.)

So Abundance does identify some barriers to growth and describe the implications. But the book is also strangely non-political in the sense that I didn’t find anything about how to get from here to the sunlit uplands of there. The book says, “What we are proposing is less a set of policy solutions than a new set of questions around which our politics should revolve.” OK, nobody wants another list of 10 bullet point policy solutions in the final chapter. But what is the political economy of getting from today’s polarised and disgruntled world of concentrated power and authoritarianism to the Abundance-land of pro-concrete liberalism, where building new things is welcomed by communities and technology works for everybody?

Top marks for optimism to the authors, and I enjoyed the read, but it didn’t rattle my pessimism about the current moment.

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The people’s AI?

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The title of Maximilian Kasy’s new book The Means of Prediction cleverly riffs off Marx’s concept of the means of production for th age of AI. These means, Prof Kasy argues, are data, computational infrastructure, technical skills and energy. The core argument is that these means rest in few hands, so the value being created by AI is concentrated in a relatively small number of technology companies and their founders and employees. What’s more, this concentration also skews the kind of AI systems being created: AI is designed to optimise some objective function, as I argued in Cogs and Monsters (and some recent as-yet-unpublished lectures).

This makes a powerful case for democratising AI, the book argues. Unless countervailing power from workers, consumers, and politicians is brought to bear, the technology will create further inequality and will not serve the public good, only private, profit-maximising interest. Kasy convincingly argues for collective means of control, rather than just individual protections such as GDPR: “Machine learning is never about individual data points, it is always about patterns across individuals.” Control over one’s own personal data does not protect privacy as long as similar people share their data.

The book starts with a section explaining AI, followed by a section explaining how economists understand social welfare – this being the approach (as Cogs explains) that is being automated by AI. These are very clear and useful for people who are hazy about either, although as they are so introductory it did make me wonder about the target audience for the book. Having said that, there is such a lack of knowledge among the public and indeed lots of policymakers and politicians that these sections are probably sorely needed.

The final two sections go on to regulatory challenges and the need for democratising the development and use of AI. As Kasy points out, policy choices have always been choices, with winners and losers, and decisions have often involved predictions; after all this is what policy economists have been doing for decades. The increasing use of AI to make decisions automates and speeds up choices – the danger being that it does so with embedded biases and implicit decisions hidden by the technology, and the all-too-common presumption that the machine must be right.

The optimistic take on where we are is that the use of AI to make predictions and decisions will surface some of the implicit assumptions and biases, and so force more public deliberation about how our societies operate and affect different people. The pessimistic take is of course that they simply become more deeply hidden and entrenched. Depending on my mood, at present I think things could go either way. But that open prospect makes The Means of Prediction a very timely book. And – having pondered who it was aimed at – probably one that every official and politician should be made to read as they chirrup about using AI in public services.

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Building vs stopping

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I read Dan Wang’s Breakneck: China’s Quest to Engineer the Future, which some people I follow (like Henry Farrell and Richard Jones among others) have already reviewed. It is,  as they have said, a very interesting read – much more about China than about America, although the contrast he paints between the two is clear. The core of that contrast is that China’s leadership consists of engineers, and they focus on getting things built, while America’s consist of lawyers, who focus on stopping things.

However, the point Wang makes is subtler than ‘engineering good, lawyering bad’, although China’s success in building infrastructure and developing manufacturing industry has delivered astonishing increases in living standards. For, as a couple of chapters emphasise, the engineering mindset can go badly awry when applied to social issues – the one child policy and the covid lockdowns are the examples.

Nevertheless, there are lessons for the US (and the rest) in China’s approach. He writes: “[China] embraced a vision of technology radically different from Silicon Valley’s: the pursuit of physical and industrial technologies rather than virtual ones like social media or e-commerce platforms. In China. technology is not represented by shiny objects; rather, it is embodied by communities of engineering practice like Shenzen, where technoogy lives inside the heads and hands of the workforce.” This seems spot on in identifying a relative weakness of the US and UK models, both of which overlooked the importance of keeping those communities rooted at home. One of my favourite papers is Gregory Tassey’s in the 2014 Journal of Economic Perspectives, making this point. It also reminded me of Dan Breznitz’s point about the different pathways for industrial policy, and Silicon Valley not being the obvious model to emulate.

Another lesson for both countries lies in their contrasting but equally unappealing urban forms – China with its soul-less new mega-block developments and America with its bland suburbs. Neither seems to manage dense, walkable, attractive neighbourhoods on the whole – in China, Wang lived in the attractive French Concession area of Shanghai, an exception to the rule. Here is one dimension where many European countries do better than either superpower, as Chris Arnade often points out.

My other reflection on Breakout – which is a must-read – is that it already seems dated by recent developments in US politics. There are now many things the lawyers are not stopping, although still much that the engineers are not doing either. In the long run the lessons of both countries’ recent past will be relevant for economic growth and technological advance, but the short run seems much murkier than it did even a few months ago.

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The power of ideas

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Some years ago I read Masters of the Universe by Daniel Stedman-Jones, a history of the Mont Pelerin Society with a focus on how it came to have such a profound influence on policy, first in the UK and US through Thatcher and Reagan, and subsequently on the whole western world. It made a big impression on me, opening my eyes to the Milton Friedman assertion about how important it was to make sure the ‘right’ ideas were around, in the air, when a moment of crisis created political opportunities. The Mont Pelerin economists had kept the free-market faith from 1945 onwards, working at building their institutional network (mainly via Chicago) and seeding their ideas.

I’ve now read The Great Persuasion by Angus Burgin, which covers the same history from a slightly different perspective. Its emphasis is less on the practical politics, more on the evolution of the ideas of the Society’s members (including its internal rifts). One of the same points about Hayek and his colleagues jumps out, though: “In adopting this strategy [avoiding policy engagement], they demonstrated an extraordinary faith in the capacity of abstract ideas to generate substantive political change,” Burgin writes.

Indeed Milton Friedman, a great communicator, was one of the first leading lights to embrace public engagement much more actively – his most influential article was probably a New York Times essay, on maximising shareholder value, still distorting our economies. The book also underlines how much the core ideas of the Society shifted over time, from an initial postwar insistence on the importance of government and rebuttal of ‘Manchester’ laissez faire, with the shift from Europe to Chicago and the growing influence of right wing American donors – and of the dominance of economists as opposed to philosophers.

The two books are good complements, along with Quinn Slobodian’s books on neoliberalism. I haven’t yet read his latest, Hayek’s Bastards, but the earlier Globalists is well worth a read.

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Leviathan, supersized

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My dear husband gave me a Daunts book subscription for my birthday so I get a lucky dip new paperback each month. A recent one was my colleague David Runciman’s The Handover: How We Gave Control of Our Lives to Corporations, States and AIs, first published in 2023. As David writes too many books for me to keep up with, I hadn’t already read it. The core argument is that human societies have already ceded many decision-making powers to non-human entities, namely states and corporations.

I read most of the book thinking, ‘Yes, but….’, as it’s a neat argument but not watertight. It starts with Hobbes, and the idea of non-human persons as it developed in different institutional forms. A key difference with decisions made by machine agents seems to lie in their autonomy or lack of openness to change or redress; and changing that requires them to be part of states and corporations rather than separate entities.

The book does, though, sort of acknowledge this towards the end: “If the machine decides what happens next, no matter how intelligent the process by which that choice was arrived at, the possibility of catastrophe is real, because some decisions need direct human input. It is only human beings whose intelligence is attuned to the risk of having asked the wrong question.” He goes on to link this back to the claim that the state is a ‘political machine’ or ‘artificial decision-making machine’ so there is no difference really between states and AIs – but this, again, makes the use of AIs in political domains part of the state machine.

He concludes: “For now the bigger choices is whether the artificial agency of the state is joined with human intelligence or artificial intelligence.” Will AI crowd out the humanity? Looking at the US now, this seems like a question from another era, a gentler era, though. The new regime there has merged state, corporation and AI in a behemoth that dwarves Hobbes’ Leviathan.

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