Gambling across borders

A blog about the productive life of risk

Posts Tagged ‘risk intelligence

Risky Business

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Rebecca Cassidy, the principle investigator of the ‘Gambling in Europe’ has contributed to the German newspaper Capital. She writes about the production and consumption of risk, charting its history from the hunter and gatherer times to the MIT blackjack card counters, whose adventures were illustrated in the film ’21’. How is risk perceived and managed today, how it relates to the way contemporary business is conducted and can we train ourselves in risk intelligence – asks Rebecca in her blog. You can read the German version or continue scrolling down for the English one.


Film 21 starring Kevin Spacey

In 1986 sociologist Ulrich Beck argued that risk had become the predominant product of modern society. Is life becoming more risky? If so, are we becoming more adept at risk management?

The survival of our primitive ancestors depended on their ability to avoid or overcome the lethal occupants of a hostile world including bear sized hyenas and sabre toothed cats. According to anthropologist Robert Sussman, ‘Man the Hunter’ was a myth derived from Judaeo Christian ideas about men as fallen and therefore naturally aggressive, ideas which were reinforced by Sir Arthur Conan Doyle’s The Lost World (1912) and Edgar Rice Burrough’s The land that time forgot (1918). Fossils indicate that primitive man was in fact prey, rather than predator, and the ability to minimise the risks involved in gathering food was key to his success. Bones found in butchery sites in Tanzania suggest that complex hunting practices may have been used as long as two million years ago by small brained, risk averse apemen. These creatures hid in trees and stabbed prey with spears as they passed beneath the branches, a far cry from the fur toga wearing, mammoth wrestling gladiators depicted in films like 1 Million Years BC. Archaeological evidence also suggests that our ancestors stole meat from predators and herded animals over cliffs. The products of these collective hunts were distributed to build social cohesion and maximise the value of gluts of protein in what are referred to as ‘immediate return societies’ with minimal facilities for storage.

One might think that all of this dodging hungry carnivores and working out ways to ambush prey would hone our perceptions of risk to a very fine degree. However, as a species we remain beset by what psychologists refer to as cognitive biases: systematic failings in our capacity to identify, and particularly to quantify, risk. Cognitive biases are produced by our reliance upon heuristics: rules which deliver good answers to questions relatively often, but also generate systematic errors. So, for example, in a seminal study in 1978 Lichtenstein and his colleagues showed that people consistently overestimated the frequency of rare causes of death. Homicide, for example, was incorrectly identified as more common than diabetes or stomach cancer. This failure was attributed to the so called ‘availability effect’: it correlated strongly with the kinds of deaths reported in newspapers. More recently, Naseem Taleb has used the availability bias to account for our failure to predict exceptionally rare events or outcomes which he refers to as Black Swans.

So what can we do to overcome these systematic failings? In Las Vegas last week members of the MIT card counting team told an audience of gambling industry executives and academics that the best possible apprenticeship in risk assessment was to count cards at blackjack tables. This experience, they argued, prepared them for successful careers as entrepreneurs. Might card counting enable us to overcome our cognitive biases? Does playing games make us better able to manage risks in everyday life?

The MIT card counting team was formed by students at the Massachusetts Institute of Technology in 1979 and functioned until the end of the 1990s. Their story formed the basis for the bestselling book Bringing Down the House by Ben Mezrick, and the film 21, starring Kevin Spacey. Card counting relies on the fact that in blackjack, unlike many other casino games, players can legally beat the house. Put simply, high cards are more valuable than low cards, and so a player who can keep track of the cards that have been dealt can calculate the probability of cards of each kind appearing in the remaining deck. The success of this approach lies in the systematic application of mathematical principles which can build in profit of approximately 2%. By framing their activities in this way the MIT team overcame the biases which lead to the inefficient staking of ordinary gamblers.

What did the MIT team learn from counting cards? These were smart individuals studying at a highly prestigious institution. So it’s perhaps unsurprising that many of them went on to be successful in creating highly lucrative companies. However, they attributed their success to their experiences at the blackjack table. By counting cards they had learned to overcome the availability bias which causes underbetting, and to bet appropriately heavily when the odds were strongly in their favour.

Like sportsmen, fighter pilots and chess players, the MIT team were trained to recognise and exploit risks within a limited frame. Card counting made the team money, and prepared them for risky business ventures. However, it also exacted a price. Success brought attention from the corporations which relied on a business model that made money from the cognitive biases of blackjack players. Members of the team were placed on a blacklist, banned from casinos and arrested in different countries around the world. They were also targeted by thieves. Their success made them vulnerable, and as a result they switched to equally lucrative, safer deployments of the knowledge they gained from counting cards: they became businessmen and professional poker players. In other words, they climbed trees and started prodding the animals as they passed beneath them.


Written by Andrea Pisac

July 9, 2013 at 8:31 am

Should we train ourselves in risk intelligence by learning from gamblers?

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In a Wall Street Journal article, Dylan Evans argues that risk intelligence is higher in certain types of personalities than in others. Namely, there are people more able to predict – in numerical terms – events and trends in realms such as international relations, economics, public health and technology. Majority of us, the article claims, often either overestimate or underestimate: our own abilities as well as outside circumstances.

However, all is not lost.

Risk intelligence is not a fixed value we are born with. We are told we can learn from gamblers: who ‘keep accurate and detailed records of their earnings and losses and regularly review strategies in order to learn from their mistakes’.

I am intrigued by the very concept of risk intelligence.

It is interesting how, over time and with varying social trends, different types of intelligence have been introduced as necessary for personal and social success. It was first emotional intelligence, an upgrade from the basic IQ, followed by a strong focus on social intelligence and the ability to connect. Risk intelligence is the next big thing – a precondition to survive and thrive in the age of uncertainty. Here, just like in the overall strategy of gambling regulation and liberalisation, risk has become an individual responsibility: risk intelligence then must be our only tool.

Can we really learn from gamblers?

Reference to the way gamblers learn from their winnings and losses mostly depict poker-players’ behaviour. Majority of them would, however, strongly argue they are NOT gamblers. I am told by my poker-playing informants that the skill of risk assessment can indeed be learned, but ‘it has nothing to do with chance or uncertainty’. On the other hand, psychologists who work with problem gamblers in my field tell me that poor risk assessment is one of the biggest indicators of uncontrollable behaviour. One of them said: ‘if someone believes they can win the roulette by betting on their lucky number, they have no idea about what risk they are taking – they are gamblers.’

Written by Andrea Pisac

May 18, 2012 at 3:17 pm

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