BOOK REVIEW. How to take a chance on life

A fortnight ago, when Leicester City improbably won the English Premier League, betting house Ladbrokes characterised it as the “biggest sporting upset since David beat Goliath.” That’s only borderline hyperbolic, given that the odds of Leicester winning had been 5,000-1. Punters who had put down money at those incredible odds — either for a lark or, more likely, on a drunken whim — walked away with £5,000 for every pound of reckless wager.

Likewise, back in June 2015, when Donald Trump declared his candidacy for the US Presidency, the odds of him winning the election in November 2016 were 100-1, giving him less than 1 per cent chance of victory. Today, when the blustery real estate developer is on the threshold of securing the Republican party nomination, those odds have shrunk to 5-2, which translates to a 29 per cent chance of victory in November. If I were a betting man, I’d still take those odds: given the political volatility that defines the US election process today, anything is possible.

In neither of these cases would a wager at those improbable odds have been considered a rational choice. And yet, as science writer Robert Matthews points out in this masterly book on the laws of probability and their role in our lives, it is possible to sniff out “value bets” in instances where bookmakers, with all their sagacity, have significantly underrated the chances of a particular outcome.

To be abundantly clear, Chancing It is not a book of gambling tips — although there is an entire chapter on ‘How to beat casinos at their own game’ by capitalising on the loopholes in the laws of probability that gambling houses profit from. Rather, Matthews handholds you to take rational decisions about many everyday aspects of your life by better understanding the laws of chance so as to manage risks.

Indicatively, very early on, we are introduced to the notion that ‘common sense’ and everyday experiences can lead us astray when we’re trying to make sense of chance events – and that the “amazing coincidences” we may occasionally encounter are actually manifestations of patterns even in the randomness that defines our lives.

Likewise, without blinding us with science, Matthews cautions us to “fear the phenomenal”: be wary of an overly hyped-up outperformer (be it a business or a hot stock or a star fund manager or a sporting team) because they are all highly susceptible to an imminent “regression to the mean” — or the ‘average’ level of performance.

Similarly, research studies on health issues, even those carried out by reputed scientists and published in respected journals may occasionally falter at the hurdle of wider validation if they take liberties with ‘blinded’ Randomised Controlled Trials, the golden standard in testing the effectiveness of new therapies.

Given the ‘miracle cures’ that they occasionally tout — or the health scare they trigger — a greater sensitisation to the science that underlies them, such as the book provides, allows us to determine if such medical claims are serious or spurious.

Fascinating as these concepts are, and however much they may elevate our understanding of the underlying scientific precepts, it is when Matthews segues from the abstract to the practical that the book acquires heightened utilitarian value. For instance, by channelling French polymath Blaise Pascal’s thought experiment, we are taught to decide for ourselves whether “it makes sense to belief in God”.

Matthews offers other such real-world applications of the “decision theory” matrix. For instance, how should a manufacturing company respond to (unverified) news that a chemical it has been using may be bad for the environment?

Should it keep using the chemical and risk lawsuits and bad publicity if it does turn out to be toxic? Or should it “look responsible” and switch to a substitute even if there’s a possibility that the chemical may not be toxic?

Similarly, how should a family respond to unconfirmed rumours that a new road is to be built near its house: should it stay put and risk value depreciation on its home? Or should it relocate anyway, and live with (perhaps unnecessary) upheaval and expense?

And how should governments and policymakers respond to concerns about global warming, given the absence of unanimity over whether the threat is real or a myth? In each such instance, when confronted with a tricky mix of unclear probabilities and big consequences, the book equips decision-makers with the tools to arrive at rational decisions that mitigate risks and provide optimal solutions.

At a time when the emerging field of ‘Big Data’ technology is being hard-sold as the best thing since sliced bread, Matthews offers a sobering perspective by pointing out that like all data sets, it too is vulnerable to the GIGO (Garbage In, Garbage Out) syndrome.

For instance, it is possible —as Tyler Vigen, a grad student of law at Harvard established by ‘mining’ random data sets — to find a spurious ‘correlation’ between actor Nicolas Cage’s movie releases and the number of deaths in swimming pools in the US. (The correlation coefficient is a satanic +0.666!) It’s a cautionary tale of what happens when we allow geeks bearing quant models to run riot — as happened most recently during the 2008 global financial crisis.

At the end, in trying to gauge the effects of chance, it is impossible to attain ‘God-like certainty’. We must, as the author points out, all roll the dice and take our chances. But it is possible, by invoking these techniques, to exercise rational choices and give ourselves the best chance of success. In life, you can’t ask for better odds than that…

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