Tag Archives: review

Wolves on the trading floor

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My lockdown days have become filled with Zoom meetings at the expense of reading on tubes and trains. I’m definitely going to try to cut down on the online calls, which are exhausting (& I hope tech-land is working out why, and trying to fix it).

Meanwhile, I read a very good biography of Walter Gropius by Fiona MacCarthy, another of the wonderful Maigret novels, and also The Hour Between Dog and Wolf: risk taking, gut feelings, and the biology of boom and bust by John Coates.

It’s a really interesting book about the role biological/neurological responses in decision-making, applied to the financial market context. It will surprise nobody to learn that testosterone is one of the key players, generating bull markets (hah!) and excess risk-taking. “Traders are walking time bombs, and banks invariably light the fuse, dangling before them huge risk limits and bonus payments.” There seem some obvious regulatory interventions in the financial context eg ban bonus structures and mandate 50% female employees on trading floors. The book points out that at most 5% of traders are women, even though they outperform men over the long term.

The book braids together sections on the biology and sections tracking the various hormones and nervous impulses in a financial market boom. It’s a terrific read and super-clear. The author is a financial markets guy turned research scientist and having both sets of insights is illuminating.

The part that most interested me though – and that put me on to the book via an FT article about the impact of uncertainty on our health – was pondering what it means for a computer to think and make decisions when human decision-making is so firmly embodied, driven by our physical features, the way the chemicals in the blood stream and the nervous signals shape perception and emotion. The book I’ve now started (Economic Life in the Real World by Charles Stafford ) cites Antonio Damasio’s work in Descartes’ Error: people whose emotions are affected by brain injury are worse at making ‘rational’ decisions. Reason and emotion – involving biochemical and neurological phenomena – go hand in hand. Meanwhile, we are building AIs according to an idea of ‘reason’ modelled on homo economicus.

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Frank Ramsey

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Cheryl Misak’s biography Frank Ramsey: A Sheer Excess of Powers is terrific. It’s the first full biography of the lost genius of economics, philosophy and maths – he died at the age of just 26 having already made fundamental contributions in each field, each of which has its Ramsey rule or principle. There’s also the ‘Ramsey effect’ of having a brilliant idea only to discover that Frank Ramsey had it first. There is an earlier biography of him by Karl Sabbagh, Shooting Star, which is also well worth a read but it doesn’t have the scale or ambition of this new one.

Misak takes us to the intellectual environment of the 1920s, Moore and also Russell ascendant in Cambridge philosophy, Keynes in economics, logical positivism and the Vienna circle getting into gear. The personal story – growing up in Cambridge as one of four children of a not particularly inspired and narrowly religious mathematics don – is threaded alongside the intellectual journey. Ramsey was sent to Winchester, which sounds hellish, then did the maths Tripos at Trinity College – his entire life centred on Cambridge.

As a teenage undergraduate student he was identified as the right person to translate Wittgenstein’s Tractatus – the only person who might understand it. Wittgenstein – what an absolutely dreadful man. I for one have also always found both early and late Wittgenstein totally unintelligible, although accepting there does seem to be a consensus that he was a genius. Ramsey seems to have thought so, while disagreeing with key arguments in the Tractatus; they continued their conversation until Ramsey’s death, albeit with Wittgenstein having a big sulk of several years in the middle, refusing to correspond with him.

Anyway, on graduation Ramsey was snapped up by Kings as a Fellow (at 21), and embarked on foundational work in mathematics with massively influential sidelines in Philosophy and economics. (The biography has useful boxes written by distinguished scholars explaining Ramsey’s main contributions in each field.) Economists such as Keynes and Pigou used him to check their maths, and he also reviewed submissions to the Economic Journal for Keynes. Sraffa was a friend. There are intriguing signs in his last paper that Ramsey would have taken forward the pragmatism of C.S.Peirce (another pretty unintelligible writer – or maybe it’s me and philosophy…). Who knows what other contributions he would have made in economics.

But Ramsey was no narrow, dull academic. He socialised with the Bloomsbury set, advocated free love, went to Vienna to be psychoanalysed, joined societies, played tennis, and like everyone at the time wrote countless letters – Misak has clearly spent vast amounts of itme in the archives.

A sheer excess of powers. A shooting star. Both seem apt descriptions. In just a few years he had published a dozen or so transformational papers spanning three fields. It must be Ramsey’s tragic early death that explains why he isn’t more widely known. This biography is my book of the year so far.

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Reading about AI

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There have been quite a few general books about AI published recently. I’ve read a few and wrote about them here. The post also lists a number of books on the subject recommended by people on Twitter. Subsequently I also really enjoyed Janelle Shane’s hilarious You Look Like A Thing and I Love You – I literally cried with laughter. And actually there are many others that are less about AI itself and more about its consequences; Cathy O’Neill’s Weapons of Math Destruction, for instance, on AI bias.

This week I added to the roster also The Road to Conscious Machines: The Story of AI by Michael Wooldridge, which is another very good introduction. It is for the most part a chronological account of how AI developed to where it is today, with clear explanations of the successive approaches (with some appendices setting out more detail). The final chapters turn to possible risks and consequences. Wooldridge is impatient with the obsession about ethics and the trolley problem but alert to challenges like bias, the effect of automation on jobs, and safety of autonomous vehicles. He’s rather positive about the potential for AI alongside humans to make great achievements in some areas such as healthcare.

The Road to Conscious Machines is probably closest to Melanie Mitchell’s Artificial Intelligence: A Guide for Humans. Having read so many of these books now, quite a lot of it was pretty familiar. But I still enjoyed reading it. This is a clear and accessible history of AI, one that performs the useful service of debunking both the hype and the hysteria. If you’re only going to read one book about AI, this would be a good one to choose. But whichever you go for, you should read at least one book about AI: this is an important technology and it will still be there in the post-pandemic world.

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Chaos, tools and thoughts

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It has been unsurprisingly hard to concentrate this week, but I did finish Everyday Chaos: Technology, Complexity and How We’re Thriving in a New World of Possibility by David Weinberger. Publishers love thise long subtitles and with one so long you might think there was no need to read the book. This one does the author a disservice. The book is nothing like the giddy Silicon Valley techno-optimistic tract it seems to indicate (and how badly that would have dated in current circumstances). I’d bill it as a follow-up to two much earlier books – The Cluetrain Manifesto of 2000 (of which Weinberger was a co-author) and Kevin Kelly’s 1992 Out of Control.

Everyday Chaos is concerned with the implications of AI everywhere and the always-on internet. It’s broad hypothesis is that the business environment and world more broadly need to take complexity seriously: “At last we are moving from Chaos Theory to chaos practice.” (Chaos Theory being the flapping butterfly in one place causing a hurricane across the world thanks to the non-linear complex dynamics of weather systems.) That means expecting small interventions to sometimes have huge consequences. It implies organisations need to be ‘agile’ (ie flexible), open, less hung up on causality and more willing to live with (shifting) correlations.

It’s particularly interesting on the flexibility of the concept of interoperability, which can be made to build bridges between organisations in different ways. The book advocates a “networked, permeable” view of business rather than the hard boundaries we are used to thinking about. “The knocking down of old walls that were definitional of a business is better understood as a strategic and purposive commitment to increasing a business’s interoperability with the rest of the environment.” Rather than narrowing down to a small number of strategic options, Weinberger’s advice is: “In an interoperable world in which everything affects everything else, the strategic path forward may be to open as many paths as possible.”

The book also reminded me about the very interesting work by Andy Clark and his argument that our tools – pen and paper, whiteboard, screen, spreadsheet – determine how we think (this is a terrific New Yorker profile and here’s a famous paper with Dave Chalmers on the ‘extended mind’). Knowledge is a function of what’s outside our heads. As Weinberger concludes, we are neither an effect of thing (technodeterminism) or nor to we straightforwardly cause things. new tools – machine learning – will end up with us understanding the world in a different way.

Everyday Chaos is also really well written and engaging, so it’s well worth ignoring the airport bookshop packaging. Not that there will be many chances to buy in airport bookstores for quite a while…

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All that we don’t know

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What a month – what a week – and much more to come.

Meanwhile, I enjoyed reading David Hand’s new book Dark Data: Why What You Don’t Know Matters. A former president of the Royal Statistical Society, Hand has written an excellent guide to the many reasons for caution in interepreting data. He uses the overall metaphor of ‘dark’ data (like dark matter in the universe) to categorise these pitfalls, which is a nice way of organising a book that could have ended up being a list of the rather varied things statisticians need to worry about. The book ends with a very useful, rather sobering, taxonomy of the 15 data issues a careful empiricist should be aware of.

For example these include missing data we know about; missing data or omitted variables we are unaware of (the unfairly mocked Rumsfeldian ‘unknown unknowns’); sample selection bias; gaming and feedback; fraudulent data; measurement error; extrapolation; counterfactuals; and even the process of scientific discovery. This is still obviously quite a varied collection of issues which does lead to some tangents (such as why Sigmund Freud was not a scientist, how Facebook breached the Nuremberg Convention, and that Randolph Churchill found decimal places mysterious).

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But it is all very clearly and amusingly written so it is an excellent overview of all the potential mis-steps a student (or practitioner) might make, from p-hacking to omitted variable bias, Simpson’s Paradox to the Hawthorne Effect.The final section has some positive suggestions too: linking datasets, replication, RCTs, and anonymisation. A very useful book and one I will recommend to students.

There are limits of course: sometimes the uncertainty is irreducible, as we are learning now.

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