Cognitive engineers, not choice architects

Although I’ve been reading at least as much as ever, it’s been difficult to find time to post about the books, given the length of my To Do list and the depth of untackled emails. One book I finished a while ago and wanted to flag up was Cognitive Gadgets: the cultural evolution of thinking by Cecilia Heyes. This is outside my territory, but as she incorporates cognitive science and linguistics in her work, I’ll be bravely inter-disciplinary too.

The book’s argument – as the subtitle flags up –  is that humans’ distinctive cognitive abilities are due to cultural evolution rather than genetic. It considers the evidence for cognitive differences between human babies and newborn chimps, and concludes that are rather subtle although importantly including a greater human ability to learn, and to remember. Then as humans grow we acquire our far greater distinctive cognitive skills from the society around us – they are not encoded in our minds, they are not simply shaped by social learning, but rather mechanisms or ways of thinking that have been built by cultural evolution: “They are cognitive gadgets rather than cognitive instincts: pieces of mental technology that are not merely tuned but assembled in the course of childhood through social interaction.” Some parts of the gadgetry will of course be inherited genetically, but the assemblage is the result of natural selection operating on cultural variation.

The book argues that this approach overcomes one of the issues with the idea of memes, because the issue is what units are memes measured in? What does the force of natural selection actually operate on – tunes, ideas and other memes? This seems unlikely. Heyes suggests the memes are grist to the mill of cognitive mechanisms such as causal understanding, imitation, reading aloud, causal inference, language, and other ‘gadgets’. The best gadgets thrive in the cultural evolutionary process. When it comes to inheritance mechanisms, it is social and cultural learning. This can largely occur inside individuals’ minds, but can also involve social processes such as story-telling, learning to take turns, group dances, even teaching.

History suggests that these have been quite robust – here we are, after all, with all the warp and weft of modern life. However, the theory does suggest a certain vulnerability, as many of these mechanisms could fail to be passed on: “The cognitive instinct view implies that human nature is relatively invulnerable to catastrophe. In a decimated and isolated human population … the group would lose some of its knowledge and skills. However, with each birth there would be a new child equipped with Big Special cognitive instincts. … In contrast the cognitive gadgets view implies that both grist and mills would be lost.  … The capacity for cultural evolution, as well as the products of cultural evolution, could be lost.” We are already failing to pass on to many children some quite basic (you’d have thought) gadgets such as critical thinking. Heyes specifically suggests looking at how moral learning has evolved and continues to do so.

Anyway, amateur that I am, I found this a persuasive approach and a really interesting book to read. It suggests a different approach to thinking about decision-making – not for example as a matter of setting up choices in ways that nudge flawed humans to do the right thing (but then what makes the choice architects any wiser?). Instead the engineering challenge is devising better gadgets, which is surely difficult but then humanity has invented them before.

 

 

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Civilisation: primeval slime to Mars

I finished Daniel Dennett’s From Bacteria to Bach and Back, and personally have no problem with his view that human consciousness is an evolved characteristic built over time from the ground up, and that human culture evolves too, starting with language and continues through memes. In other words, it’s all cranes, not skyhooks. Some people are obviously troubled by this argument. I lack the technical knowledge to evaluate all the detail here. It fundamentally seems far more plausible to me than the alternative.

As a matter of logic, this requires me – and Dennett – to take seriously the argument that computers/AI could evolve minds and consciousness. He puts some weight on the importance of embodiment – but that might be possible although we’re not there yet. Computer vision would be different from ours, but then so is flies’ vision or cephalopods’.

More of an issue, it seems to me, is that computers/AI are very energy-hungry compared to our brains: at the moment, Dennett writes, computer intelligence is parasitical, depending on humans to feed them a lot of energy and otherwise maintain them. What’s more, computers don’t have to struggle or compete: “Down in the hardware, the electric power is doled out evenhandedly and abundantly; no circuit risks starving. At the software level, a benevolent scheduler doles out machine cycles to whatever process has the highest priority, and although there may be a bidding mechanism … this is an orderly queue, not a struggle for life.”

So for now, I’ll stick to thinking Singularity-talk is mystical hype; but will try to keep an open mind on this question.

I’ve always had a soft spot for memes. Dennett uses words as the paradigmitic examples. It reminded me of a jokey line I read once about libraries being the dominant life form on Earth because they are so good at finding new hosts who will start to accumulate books.

There’s a nice section on the importance of social trust at the end of Bacteria/Bach, citing Paul Seabright’s wonderful Company of Strangers. Trust is the invisible glue of human societies, Dennett writes, and much too recent to be a hard-wired natural instinct. “We have bootstrapped ourselves into the heady altitudes of modern civilisation, and our natural emotions and other instinctual responses do not always serve our new circumstances. Civilisation is a work in progress and we abandon our attempt to understand it at our peril.”

Looking at the news these days, that isn’t a very optimistic note on which to end. And yet yesterday brought the amazing launch of Space X’s Falcon Heavy. Astonishing. Perhaps we’ll end up on Mars while the computers colonise Earth.

 

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Fear, greed, fairness, imagination and finance

I’ve thoroughly enjoyed reading Adaptive Markets: Financial Evolution at the Speed of Thought by Andrew Lo. I should say that, apart from being a distinguished MIT finance professor and the co-author of the classic A Non-Random Walk Down Wall Street, Andrew is an old friend. But this should not put off any readers. This new book will become another essential read for anybody interested in financial markets.

The book aims to do what ultimately all of economics must do, and situate economic decisions and behaviour in the context of our biology and evolutionary history. Behavioural economics and finance have gone some way toward this in introducing the now-familiar heuristics such as loss aversion and framing effects, and herding is a familiar phenomenon in finance models. The issue with these has been how if at all they relate to rational choice models and the Efficient Markets Hypothesis. The Adaptive Markets Hypothesis is a synthesis, proposing that context makes the difference, and when conditions are sufficiently stable for long enough, financial markets are efficient. Otherwise, fear, greed, fairness, imagination – the characteristics evolution has given the human brain – kick in.

The opening chapter starts with a powerful demonstration of the potential efficiency of markets: after the Space Shuttle Challenger tragically exploded on 28 January 1986, a five month inquiry pinned the blame on a part, the O-ring, manufactured by one of four contractors, Morton Thiokol. Yet on the day of the accident, the share price of Morton Thiokol plummeted – the markets knew the company was to blame almost immediately, without the expert verdict: “Somehow the stock market in 1986 was able to aggregate all the information about the Challenger accident within minutes, come up with the correct conclusion and apply it to the assets of the company.”  The decline in its market capitalization – about $200m – was  almost exactly equal to the damages, settlement and reduced future cash flow, a later study found.

But often, of course, financial markets are all too obviously sometimes not efficient. The intellectual challenge is to figure out when they are in which mode. The book voyages through neuroscience, psychology, evolutionary biology and AI to try to answer this. The Adaptive Markets Hypothesis reverses the conventional framing: rather than thinking about a rational benchmark with a set of psychological quirks sometimes kicking in, we are a collection of quirks, but sometimes we can get beyond the heuristics to rational choice.

Frustratingly, although perhaps inevitably, there is no neat list of conditions for being in efficient rather than non-efficient mode: it depends, in particular on having had enough time in stable conditions to learn from experience. But Andrew does hold out hope for the prospects of being able to make better investment decisions – with socially useful outcomes – and being able to manage financial markets better so events like the 2008 crisis are far less likely to recur. In line with the Adaptive Markets perspective, he argues for treating financial markets as an ecosystem (so the interconnections are front of mind), using AI techniques to monitor markets and adjust regulatory instruments such as cyclical buffers. There is an interesting section on the role of technology in finance, including HFT, a technological arms race being one of the predictions of the Adaptive Markets Hypothesis. Currently, he is exploring ideas from biology such as immune responses and ecosystem management techniques. He also recommends introducing a body similar to the National Transportation Safety Board that would analyse market crashes and make recommendations for regulatory change. (One thing not spelled out here is whether this would have to be a global body.)

The book is a thoroughly interesting and enjoyable read. It is not technical, the explanations are super-clear, and there is some excellent story telling. Andrew recounts how in 1986 he and his co-author Craig MacKinlay, presenting at the NBER the work that turned into A Non-Random Walk Down Wall Street, were savaged by discussants from the world of academic finance. Since then, the academic community’s faith in the Efficient Markets Hypothesis has wavered significantly, but it is still the benchmark – as the book says, it takes a theory to beat a theory. I find the Adaptive Markets Hypothesis a persuasive theory, but then I firmly believe economics must be consistent with what we learn about ourselves from the other human sciences. I guess the test will come in the shape of how widely market participants themselves embrace it.41CpHzPtybL

 

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Not the smartest animals

The title of Frans de Waal’s latest book is a rhetorical question: Are We Smart Enough to Know How Smart Animals Are? I thoroughly enjoyed reading it. De Waal’s deep knowledge shines through every sentence, as does his delight in all the creatures (especially other primates) he has spent his career studying. The book is about the evolution of cognition and emotion in animals (including humans). It particularly debunks Skinner’s behaviourism – mental processes as a black box, but manipulable using reward and punishment. (This of course the approach behind the present fashion for behavioural economics, a fashion I find troubling because some of its enthusiasts do so clearly see themselves as omniscient scientists ordering society for the better by manipulating the choices of their less intelligent subjects.)

I learned a lot from the book, including that the elephant brain is the one with the most neurons (about 3 times as many as we do). The neural differences between humans and other primates are not sufficient to make us unique in all aspects (although we clearly are in some, notably language). De Waal argues we should assume continuity, a spectrum of cognitive abilities between different animals, rather than sharp and wide distinctions. He notes that psychology is moving to accept this assumption, but the social sciences tend to assume human discontinuity – “But what does it mean to be human?” he reports social scientists asking him. “I usually answer with the iceberg metaphor, according to which there is a vast mass of cognitive, emotional and behavioural similarities between us and our primate kin. But there is also a tip containing a few dozen differences. The natural sciences try to come to grips with the whole iceberg, whereas the rest of academia is happy to stare at the tip.”

The scientific project must therefore be to develop a unitary theory of different cognitions, how cognition operates in general, and then in the case of each particular species. The book emphasises two important contributors: sense perceptions (is vision the most important to the species? or hearing, or smell?); and social relations (is it a species with strict social hierarchies, like chimpanzees, or solitary, like the octopus?) “Cognition and perception cannot be separated… they go hand in hand,” he writes. (Interesting to reflect on what this means for AI. The question is not so much what androids dream of as what they see or hear.)

To crown a wonderful book, it ends with a quotation from David Hume: “Tis from the resemblance of the external actions of animals to those we ourselves perform, that we judget their internal likewise to resemble ours; and the same principle of reasoning, carried one step farther, will make us conclude that since our internal actions resemble each other, the causes, from which they are derived, must also be resembling. When any hypothesis, therefore, is advanced to explain a mental operation, which is common to men and beasts, we must apply the same hypothesis to both.” As Hume summed it up, “No truth appears to me more evident than that beasts are endowed with thought and reason as well as men.”

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Economics and evolutionary science

I recommend this Evonomics post about economics post-2008, and the kind of re-evaluation that’s been going on among economists, citing somewhat critically Noah Smith and also Dani Rodrik’s excellent . Author David Sloan Wilson complains: “All good, but there is something missing from the internet links that I just provided—any discussion of evolutionary theory.”

[amazon_image id=”0393246418″ link=”true” target=”_blank” size=”medium” ]Economics Rules: The Rights and Wrongs of the Dismal Science[/amazon_image]

I couldn’t resist preening a little, for my 2007/2010 book , has a whole chapter, Murderous Apes and Entrepreneurs, about the importance of the links between economics and evolutionary biology. This also forms one strand of my 2012 Tanner Lectures. In other words, I wholly agree with the argument of the Evonomics post, but thhink there has been a little bit more progress than it acknowledges.

Of course, formal evolutionary theorising is not part of the conventional economics mainstream, although it has some distinguished practitioners; but having said that informally it widely informs much business economics. There are also some leading economists who have been thinking about the overlap between economics and evolution. The ‘murderous apes’ of the chapter title was inspired by Paul Seabright’s brilliant ; Wilson cites Robert Frank’s . There is also an active strand of research on complexity theory, which and among others have written about.

[amazon_image id=”B004XCFI2Q” link=”true” target=”_blank” size=”medium” ]The Soulful Science: What Economists Really Do and Why It Matters[/amazon_image] [amazon_image id=”0691146462″ link=”true” target=”_blank” size=”medium” ]The Company of Strangers: A Natural History of Economic Life[/amazon_image] [amazon_image id=”B008W4ASGC” link=”true” target=”_blank” size=”medium” ]The Darwin Economy: Liberty, Competition, and the Common Good[/amazon_image]

Economics will have to be consistent with what we learn about human behaviour and decisions from other human sciences, not just the other social sciences, but also evolutionary biology, cognitive science and psychology.

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