On my travels to and from the fabulous Kilkenomics Festival this weekend, I read [amazon_link id=”184794714X” target=”_blank” ]Superforecasting: The art and science of prediction[/amazon_link] by Philip Tetlock and Dan Gardner. It’s a very interesting book. If you liked Daniel Kahenman’s [amazon_link id=”0141033576″ target=”_blank” ]Thinking, Fast and Slow[/amazon_link], Nate Silver’s [amazon_link id=”0141975652″ target=”_blank” ]The Signal and the Noise, [/amazon_link]and Gerd Gigerenzer’s [amazon_link id=”0241954614″ target=”_blank” ]Risk Savvy[/amazon_link], you’ll like this book too.

[amazon_image id=”184794714X” link=”true” target=”_blank” size=”medium” ]Superforecasting: The Art and Science of Prediction[/amazon_image]

Essentially the book describes the outcome of the research project that followed on from Tetlock’s famous demonstration in [amazon_link id=”0691128715″ target=”_blank” ]Expert Political Judgment[/amazon_link] that experts are not good at predictions. One group of experts failed to do better than random guesswork – and did worse for long term forecasts. Another group did better than this but could rarely beat a simple rule of thumb such as ‘predict no change’ or ‘extrapolate the trend’. The follow up project was stimulated by the introspection of the US intelligence community post 9/11, looking to see whether it would be possible to make forecasts of political or economic events any better than the earlier dispiriting results suggested.

The bulk of the book explains that yes, it is, but it’s hard work requiring techniques and habits that help people avoid the normal cognitive short cuts (‘fast thinking’) we humans take. For example, make sure you start with what the authors call ‘the outside view’. Looking at the drop in popularity of a prime minister after an election? Start out by seeing what has happened to the ratings in the past. Watch out for the ‘bait and switch’ habit of answering an easy question rather than the hard one. Break up complex questions into smaller questions to narrow the territory of your ignorance. Take as many different perspectives as you can. Consult others and welcome diverse views – be on the alert for groupthink.  Be prepared to change your mind. Be alert to conclusions based on your strong feelings or beliefs about an issue (the Keynesians vs Austerians debate is singled out as one where the participants are captive to their prior beliefs). All of the tips are gathered in a how-to-be-a-superforecaster appendix to the book.

Summarised like this, it sounds obvious perhaps. But the book is stuffed with examples demonstrating how hard it is to put the advice into practice. Indeed, the experiment showed that some people can do far, far better than the majority, including ‘experts’ – but there are not many of them. They have specific characteristics: for example, clever (but not Mensa geniuses), open-minded, self-critical, numerate, comfortable with probabilities, willing to change their mind – plus determination. Tetlock is still looking for volunteers to have a go (www.goodjudgment.com).

The book ends with a discussion of two critiques. One is whether Nassim Taleb’s Black Swans imply superforecasting is a chimera – if history moves in jumps because a black swan appears, that must be unforecastable. The other is Daniel Kahneman’s hypothesis that even superforecasters will lose their mojo because their very success will make them as vulnerable to the same cognitive patterns as the ‘experts’ who did no better than randomness or algorithms; we are all vulnerable to complacency or ‘fast thinking’. Tetlock concludes that history does show that the possibilities for the future are radically open but nevertheless argues that his results show that: “People can, with considerable effort, make accurate forecasts about at least some developments that really do matter.”

He does, for me, describe his results convincingly, although the ‘considerable effort’ bit seems a huge barrier to seeing superforecasting habits spreading more widely. But it doesn’t matter if you end up agreeing more with the critiques; this is still a very useful guide to cultivating your own good cognitive habits and critical thinking abilities. I’ll be trying to put the lessons here into practice myself – although not to the extent of starting anything foolish like macroeconomic forecasting.

It has been a busy and dyspeptic week. [amazon_link id=”1781688451″ target=”_blank” ]The Happiness Industry: How the Government and Big Business Sold Us Well-Being[/amazon_link] by William Davies has been the perfect accompanying reading material. The enthusiasm of many of my fellow economists for behavioural economics has made me increasingly uneasy. This is, after all, a profession strongly  inclined towards social engineering, and I’ve written here before about the likelihood that nudges are seen as an exciting new tool for this job. After all, they seem to work, and as even the status quo is a nudge, why wouldn’t you design better nudges to deliver better outcomes?

[amazon_image id=”1781688451″ link=”true” target=”_blank” size=”medium” ]The Happiness Industry: How the Government and Big Business Sold us Well-Being[/amazon_image]

[amazon_link id=”1781688451″ target=”_blank” ]The Happiness Industry[/amazon_link] eloquently reinforces my suspicions. It locates the fashion for “well-being” in the long tradition of making the internal world measurable and reducing questions of morality and political choices to scientific decisions. Economics, rooted in [amazon_link id=”1508738734″ target=”_blank” ]Bentham’s utilitarian calculus[/amazon_link], plays a leading role in the story, as do the successive waves of management science from Taylorism on. Indeed, in management, the growing surveillance of employees’ ‘well-being’ by wearable devices is the latest version.

Davies points out there is an inconsistency at the heart of this: “Workplaces put a growing emphasis on community and psychological commitment, but against longer term trends towards atomization and insecurity. We have an economic model which mitigates against precisely the psychological attributes it depends upon.” Yet the emphasis on resilience or mindfulness puts all the onus on the individual to adjust: “one progressive route would involve changing [the] context. But another equivalent would be to focus on changing the way it is experienced.”

He is also critical of the economists’ use of the idea of revealed preference: that you can infer somebody’s inner preferences or desires from their choices, usually their choices about what to spend their money on. Shopping speaks louder than words. Perhaps wearables that can measure heart rate or sweat will replace money as the best revealed preference metric, but meanwhile what someone spends is a readily-measurable indicator, easier to count and compare than what people say about their emotions. “This granted money an exceptional psychological status, as it allowed others to peep into people’s private desires.”

Disliking money as a metric, Davies is therefore also critical, as many people have been, of using the technique of contingent valuation to put monetary values on, say, the impact of an environmental disaster. “What we witness in this sort of example is economics becoming used as a basis for broad public agreement well beyond the limits of the market place,” Davies writes. He’s in good company. [amazon_link id=”B007IO1X5C” target=”_blank” ]Michael Sandel[/amazon_link] and [amazon_link id=”014197558X” target=”_blank” ]George Monbiot[/amazon_link] are among those who dislike the use of money as a measure of non-monetary values, such as nature, or relationhips, or civic virtue.

However, this seems to me distinct from the reductionism of the behavioural economists and psychologists. It is one answer to the question of how you resolve conflicts when there is no market: if you have to make interpersonal comparisons, how should you go about it? Or, in the words of a well known survey article, is some number better than no number? If you want to calculate compensation after an oil spill, how else could you go about it? So I am far more comfortable with these valuation techniques than I am with the happiness tendency.

On the latter, my instincts are with Davies: ” Behaviourism stretches Bentham’s dream of a scientific politics to its limit, imagining that beneath the illusion of individual freedom lie the cold mechanics of cause and effect, observable only to the expert eye.” When I teach my students behavioural economics – and they’re very interested in it – I ask them to look at this Adam Curtis blog, From Pigeon to Superman and Back Again. While not dismissing the policy sense of some nudges, beware economists who know how to make you happy and beware even more bosses demanding it of you.