Tag Archives: institutions

Reshuffle – or how productivity happens

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Term time is not conducive to doing a lot of reading, but I have managed a couple of interesting books recently. One was Abundance – I’ll jot down some thoughts about that later. The other was Reshuffle: Who wins when AI restacks the knowledge economy by Sangeet Paul Choudary, which I read and then listened to a presentation by the author organised by the Dynamic Competition Initiative.

I liked the book because it focuses on an aspect of the impact of AI that is underemphasised in public discussion and to some extent in academic circles. That’s its likely catalysing significant organisational change. So much discussion focuses on labour market change and the specific tasks within jobs that will be automated, and how tasks will be rebundled into new jobs. This is a rich literature, flagging up the interaction between the automatability of tasks and the level of expertise required in each task. However, less attention has been paid (though this is changing) to the consequent changes in processes, work flows and business models.

The core point in Reshuffle is that understanding AI’s impacts on the economy requires thinking about tasks as nested within organisations, which in turn sit within systems of production. The focus needs to be directed towards the broader structural architecture, the book argues. It has a construct of being ‘above’ or ‘below’ the AI – I think this means having or not having agency in decision-making – with implications for distribution. “Much of the value associated with a job is not derived from the task alone but also from the system within which the task is executed.”

I wholeheartedly agree with this perspective, that value creation in organisations has an essential social dimension. Firms are more than a collection of individuals. There was years ago an excellent book making exactly this point, Chasing Stars by Boris Groysberg.

The book also majors on the way AI will unbundle some knowledge tasks from humans – often described as codifying tacit knowledge – and the consequences. Such forms of knowledge are more flexible (there is no human or long-term contractual relationship involved) and can be more easiry reproduced or rebundled. So for these reasons I like Reshuffle.

On the other hand, the author wrote it as an airport-style business book, a perfectly valid decision but irritating for me – it’s somewhat repetitive and fond of diagrams that seem less clear than the words. More irritating is the econ-bashing. Yes, economists have been focused on task-based labour market approaches, but there is now a lot of  economic research taking an institutionalist, transactions cost perspective, building on Luis Garicano’s now-classic work, and the earlier tradition of institutional economics all the way back to Coase.

Nevertheless, Reshuffle is an interesting read, with some useful insights – and can indeed be read on a flight or train ride.

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The political economy of horses for courses

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It was the fact of a lecture by Dan Breznitz at the University of Manchester for National Productivity Week that alerted me to his book Innovation in Real Places. Sadly I couldn’t get to Manchester for the lecture but I really recommend the book. Its core argument is that the shape of innovative businesses depends on the specifics of their economic context, making the hope to become the next Silicon Valley a forlorn one for most places, and requiring innovation policy to be appropriately tailored.

The aims of innovation policy are common: make sure companies and individuals concerned have the capabilities they need, and support the whole cosystem in which they operate. There are also several policy fundamentals: ensure local firms are plugged into production networks (including internationally); provide the necessary public goods (skills, prototyping production facilities, trade shows…); focus on the whole local ecosystem including whether financing and business models cohere; adjust policy over time as the ecosystem grows.

Given the basics, the book sets out four different pathways with examples about how specific places have followed each. The one that dominates the innovation policy imaginary is the Silicon valley model – frontier innovation, VC finance, star entrepreneurs. (This is looking less good than it did a while ago. And as the book comments in the introduction, “There is nothing like a dosage of competition to shake comfortable oligopolies out of their stranglehold on power.”) Tech startups – like all startups – require extensive social networks, but in this sector they are geographically extended rather than locally-rooted. So even if a Silicon-whatever gets going, the people involved may end up moving to Menlo Park or Mountain View when they succeed – the book gives an example of a tech cluster starting successfully in Atlanta, Georgia, but subsequently moving away. The book argues that the conditions for such clusters are rare in any case, and that the model leads to inequality rather than broad-based prosperity and good jobs in the region.

The second model is the design, prototyping and production engineering stage, with Taiwan being the exaplar. The third is innovation in components and second generation products, “the unsung and despised hero of economic growth,” with examples in Germany and some in China. The final model is production and assembly, so successfully adopted in China’s Pearl River delta region, with extremely successful innovation in modes of production, assembly and also logistics.

Having set out these broad models, the rest of the book is packed with examples of innovation policies both good and bad. As it points out, much policy thinking is lazy. If it gets beyond the aim of being the next Silicon Valley, “one of the most comon ways for regions to fail is to focus on the trendiest complementarity, be it venture capital, university parks, green tech or AI.” Prof Breznitz’s key message is that there is no substitute for detail, and indeed constant willingness to adjust policies as circumstances change. The book identifies a core political challenge: successful innovation policies often succeed by flying below the radar of political attention, but if they do succeed there’s no avoiding that politicization – and rightly so in many ways. Innovation policy is hard enough to get right, but the political economy challenge may be harder still.

Anyway, a wise book, lots of great examples, and hopefully the lecture will go online before long.

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The narrow path from votes of despair

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I read Sam Freedman’s Failed State: Why Nothing Works and How We Fix It with a mixture of nods of recognition and gasps of disbelief. It’s all too apparent  that – as the subtitle puts it – nothing works in aspects of life in the UK dependent in some way on the successful design and implementation of government policy (which is most aspects tbh). Those of us who have engaged with the policy world in some way will have our own experiences; the relevant chapters of the book reflect my own very accurately. What makes this an incredibly sobering book (although well-written, with humour) is the accumulation of evidence across all eight chapters, covering everything from parliament and the excessive growth of executive power, the House of Lords, political parties and the character of MPs, the judiciary, the criminal justice system, the civil service, local government, non-departmental public bodies and the media. A relentless accumulation of depressing dysfunction.

I’m very much on board with the book‘s main recommended fix, substantial devolution of power from central to sub-national governments – this is a journey I’ve been advocating since first getting involved with Greater Manchester’s case for greater powers from 2008 on. But this is not a simple matter. Many people point to the hollowing out of capacity in local government – true to some extent but one can see how to tackle that. Harder are the questions of accountability that raises. But – as the book argues – it’s hard to see any other plausible change that would shift the dial on interconnected institutional reforms. And equally hard to see how nothing can change: “Public trust in politicians and politics – never high – has crashed through the floor.” The governance travails of the Labour Government in the few weeks since the election suggest the time for something to change can’t be far away – surely? There has at least being slowly growing consensus about the need for decentralisation from Whitehall and Westminster, as a potentially feasible path for reducing the powers of an over-dominant executive branch that can’t deliver and can’t cope.

This book joins other incisive critiques and reviews of how the UK is governed – my colleague Mike Kenny led a major inquiry into the constitution, the Institute for Government documents failures across the board, and others such as Martin Stanley are excellent on specific aspects (the civil service and regulatory state in his case). It’s cold comfort that other countries are experiencing similar failures against a background of slow growth and hyper-fast social media, and colder still that in so many extremist parties are capturing the votes of despair. It’s a narrow path from today’s failures to a less disturbing outcome. The book ends posing a question to those in central government with the power and opportunity to start the process of change: if the UK goes down the path of crisis and reaction, “Politicians will find themselves asking: why didn’t we do things differently when we had the chance?”

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The public option

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I’m on my way to a workshop at The New Institute in Hamburg, where I will talk about the scope for a public option in (especially) digital markets. As preparation, I’ve read a recent short (and moderately technical) book surveying the literature on ‘mixed oligopoly’ by Joanna Potoygo-Theotoky; these are oligopolistic markets with a mixture of private and public provision, where the public competitor has a broader objective function than profit maximisation – such as social welfare broadly, or ESG motivations, or universal service obligations. The basic idea is that by having a different objective function, the presence of the public provider acts as a regulatory function; private firms will choose a lower price/higher quantity or will select to compete on a different level of quality.

I’m most interested in the latter area, where the formal results can go both ways. Public firms can either decide to offer a ‘basic’ package to deliver universal service or can offer a higher quality package than the private sector. Think of public schools vs private schools providing great sports fields and additional subjects in the former case, or public broadcasters ensuring provision of children’s programmes or religious programmes in the latter case. Given the concentration in digital markets and the limited tools governments other than the US and China have to affect the behaviour of Big Tech, provision of a public option in some domains is worth thinking about.

The book, Mixed Oligopoly and Public Enterprises, is a very nice survey and introduction to the mixed oligopoly literature, much of it focused on the price and quantity decisions and the optimal mixture of private and public, but covering some more recent literature on issues like R&D, quality and ESG standards. It also ends outlining a fascinating research agenda – introducing issues of motivation of employees, and even wider objectives such as creating jobs and reducing inequality.

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Unaccountable

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I read a proof of The Unaccountability Machine by Dan Davies with a view to blurbing it, and was more than happy to recommend it. This is a fascinating book. The subtitle indicates its scope: “Why Big Systems Make Terrible Decisions and How the World Lost Its Mind”. The book asks why mistakes and crises never seem to be anybody’s fault – it’s always ‘the system’. Davies uses the concept of the ‘accountability sink’ – a policy or set of rules that prevent individuals from making or changing decisions and thus being accountable for them. He writes: “For an accountability sink to function, it has to break a link; it has to stop feedback from the person affected by the decision from affecting the operation of the system. The decision has to be fully determined by the policy, which means that it cannot be affected by any information that wasn’t anticipated.” I predict that the more machine learning automates decisions, the more accountability sinks we will experience. Think Horizon. But there are plenty of non-automated examples. Davies cites, for example, Gill Kernick’s wonderful book on the Grenfell disaster (and others), Catastrophe and Systemic Change.

The book draws heavily on Stafford Beer’s cybernetics, providing the public service of digesting all of his writings and making them accessible. Cybernetics was of course concerned with using the flow of information and enabling feedback. Decisions about how to make decisions are part of the system. Hence the often-quoted principle that “the purpose of a system is what it does” – and not what it says it does. The book has several chapters describing how systems operate, including how to conceptualise a ‘system’ in the complex, messy real world. Davies observes that this requires a representation that is “both rigorous and representative of reality.” The selection of categories and relationships in a system is a property of the choices about description and classification made by the analyst rather than inherent reality. He describes – using plentiful examples – how systems so often malfunction.

The book has a chapter specifically diagnosing the strengths but also malfunctions of economics. He writes: “Economics has been a major engine of information attenuation for the contrl system. Adopting the economic mode of thinking reduces the cognitive demands placed on our ruling classes by telling them there are a lot of things they don’t have to bother thinking about. … when decisions are made that have disastrous long-term conseqneuces as a result of relatively trivial short-term cash savings, the pathology is often directly related to something that seemed like a good idea to an economist.”  There’s an interesting section on ‘markets as computing fabric’, a ‘magic calculating machine’. This was echoed recently in some terrific posts by Henry Farrell and Cosma Shalizi. It’s a fruitful way of thinking about collective economic outcomes. I also strongly agree with the sections about collecting the data – classification and data collection is a super-power (as I’ve been writing for years in connection with GDP and beyond). The book says, “Numbers are collected for a purpose and it’s often surpriginly hard to use them for any other purpose.” Moreover, many numbers are not collected, which makes it hard to ‘prove’ claims about the potential for the system to operate differently.

The book ends by returning to system dysfunction – ‘morbidity’. From the toxic idea of shareholder value maximisation to the fentanyl crisis in the US, from the collapse of public infrastructure networks to the advers effects of private equity (which Brett Christophers has dissected forensically in his book), economic and financial systems need a redseign. Davies suggests one step that he thinks would have a big impact: make these investors liable for company debts. Oh, and make sure the economists are not in charge: “Every decision-making system set up as a maximiser needs to have a higher-level system watching over it.”

The Unaccountability Machine does not directly address my current preoccupation, which is the implications for automated decision-making in public services, in particular, of GOF machine learning and generative AI, but is higly relevant to it. It’s a cracking read and I highly recommend it.

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