Human perception of risk
By: Ben Mark
Tags: Risk Taking, Safety Management, Risk Analysis, Risk, Risk Management

Just like a novice pilot flying in cloud, human intuitive perceptions of probability, risk and reward are surprisingly poor, and very hard to overcome, which is why RiskFlag advocates a structured, disciplined approach to assessing and managing risk. There are several main ways in which we can struggle to comprehend risk, and they are worthy of deeper consideration.

A focus on outcomes

It is in our nature to focus on the outcome of a particular event, rather than the factors that determined it. This principle is even a part of our criminal justice system, where the same human failing might attract a very different sentence depending on an outcome which was largely driven by chance. A pub brawl might result in a charge of assault or affray, for example, but the same fight might result in a manslaughter charge if somebody falls the wrong way and is fatally injured.

It is also human nature to attribute success to skill or good judgment, even if the situation was largely one of chance. This is known as self-attribution bias, and has been well-studied in financial trading, where skill and luck can be difficult to separate¹. The effect also occurs in many other aspects of life. Read any account of a contest, be it a famous battle or a sporting event, and it is usually the victor whose tactics and strategy are held up as superior, even if chance events played a big part in the victory. A gambler who risks their life savings on a game of roulette and wins might describe their decisions as correct, or even wise, even though their choice was arguably foolish.

When managing risk, particularly in situations like aviation safety where catastrophic outcomes are normally very unusual, we have to be very careful not to confuse a lack of accidents, for example, for good risk management. We must look at the inputs to the system and to other warning indicators, and not just the outcomes.

The sunk cost fallacy

When confronted with a decision about whether to undertake a course of action or not, our thinking should be solely focussed on the potential future benefits and pitfalls of the activity in question. However, human nature tends to be swayed by what effort, money or time we have expended on that same activity already. This is the ‘good money after bad’ problem², and is related to the behaviour known as ‘loss aversion’, first identified by psychologist Daniel Kahneman in 1979³. It is exacerbated by our societal tendency to praise and reward people who exhibit a dogged determination and a stubborn refusal to quit in the face of adversity. This rightly laudable quality of never giving up can often lead to poor decisions in situations where withdrawing from a poor investment, or ceasing an increasingly dangerous activity would actually be the wiser course of action.

Understanding large odds

Humans struggle to process very large and very small numbers, and this is particularly true of events with very low probabilities. The UK’s National Lottery flagship game, ‘Lotto’, requires the matching of 6 numbers from a set randomly drawn from 59 balls in order to win or share in the jackpot. The chance of achieving this with one £2 ticket is 1 in 45,057,474, roughly the same likelihood as correctly choosing a randomly selected person from the entire population of Spain. It is clear from lottery sales patterns that the size of the jackpot on offer is a key motivator for people purchasing tickets, but yet evidence suggests that most players have very little understanding of how incredibly unlikely it is that they will win⁴.

Finding patterns in randomness

If an event is truly random, then by definition it cannot depend in any way on what has gone before. This means that, for example, a coin toss or dice roll, assuming a ‘fair’ environment, is not in any way influenced by preceding results. This seems obvious, but human nature tends to find patterns and meaning in random sequences, a failing ruthlessly exploited by the gambling industry, and widely known as the gambler’s fallacy. It might feel to an unlucky gambler on a losing streak that the universe owes them a victory, but their chances on any particular game do not depend on prior results. A sequence of five heads in a row on a fair coin toss does not change the 50% chance of another heads on the sixth toss. In the same way, experiencing an unfortunate accident or loss does not in any way reduce the chance of experiencing a similar event shortly afterwards.

Understanding new information

Human inability to understand probability is well-illustrated by the Monty Hall dilemma, which seems wrong and counter-intuitive even after the mathematics behind it are explained. The problem, named after the host of the American game show Let’s Make a Deal, involves the contestant choosing one of three doors to be opened. Behind one of the doors is an attractive prize, such as a car, and behind the other two doors are joke, or ‘zonk’, prizes, typically a goat. After a door is chosen, Monty makes things more interesting by opening one of the other two doors to reveal one of the goats, and then asks the contestant if they wish to stick with their original selection, or swap to open the other closed door instead.

The intuitive answer is that the two closed doors seem to be equal; there should be no advantage of one door over the other. However, the surprising correct answer is that the contestant is better off swapping. There is a 1/3 chance that the car is behind the door the contestant first chose, and a 2/3 chance that the car is behind the other door.

Interestingly, aside from incorrectly assessing the odds between the two remaining closed doors as even, when playing a simulation of the game⁵ players were found to remain with their initial selection 91% of the time, thereby exhibiting another cognitive bias called the endowment effect. This is the tendency to attribute greater value to the status quo than is merited; another important consideration in organisational decision-making.

Lessons for risk management

Knowing these fallibilities can help enormously when assessing risk. Like a well-trained pilot trusting their flight instruments over their own senses, using a structured, evidence-based risk management process will improve the quality of decision-making and the allocation of finite resources. In the next article in the series, we will explore the RiskFlag structured methodology for identifying, assessing and managing risk.

Notes and references