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  • 30th Jan 2019

Psychology of tricky decision making

It’s not for us at the Behavioural Insights Team to take a view on Brexit. But we can at least take a peek at the psychology of tricky decision making. Who knows – perhaps it will leave you with more sympathy for Westminster Parliamentarians currently wrestling with the issue (and prove interesting to non-Brits thinking about matters other than Brexit…)

The issue of how to decide has been given additional airtime in recent weeks, not least by a proposed amendment from MPs Stella Creasy and Lisa Nandy, arguing that the UK should conduct a Citizens’ Assembly. Their proposals – not selected in last night’s debate – were for 250 UK citizens, chosen at random to form a representative sample, to be given 10 weeks to come back with recommendations, and is loosely based on the Irish model.

BIT has worked with partners to run ‘deliberative forums’ on issues such as obesity and young people’s use of social media. I’ve personally made the argument that they are a potentially important part of the answer to ‘who nudges the nudgers?’ If we think an intervention like auto-enrolment to pensions, or removing chocolate from checkouts to help reduce obesity, would be effective at altering citizens behaviour, then wouldn’t it make sense to ask a sample of those citizens what they think? (See Inside the Nudge Unit, pp324-335, for more)

From what to have for dinner, to whom to employ for a job, our cognitive processes struggle to keep multiple dimensions in mind at once

A particular difficulty arises when people have to decide between options that have multiple dimensions, both positive and negative. It’s something people have to do it all the time, from what to have for dinner, to whom to employ for a job, but our cognitive processes struggle to keep multiple dimensions in mind at once.

Piaget famously argued that children below the age of seven would mistakenly say that the amount of water had changed when it was poured from a short glass to a tall one, because the child would focus on one dimension (height of water) and lose track of the other (width or cross-section). Adults are clearly better at this, but still not as good as we think.

Recruitment decisions offer a good example. The notoriously low predictive validity of conventional job interviews is thought to be due to interviewers focusing on too narrow a comparison (someone’s energy levels compared with the candidate immediately before), and/or getting distracted by non-predictive details (such as what the person looks like). To improve these kinds of decision making, we’ve built processes allowing humble humans to compare on multiple dimensions at once, while seeking to remove some of the biases that trip us up.

What’s this got to do with Brexit? Well let’s have a look at what happens if we look at even two very basic dimensions of choice, as shown by polling data. Back in December, YouGov asked 20,000 Britons to rate the three most prominent options: Remain, the Prime Minister’s Deal or No Deal, as 1st, 2nd and 3rd choices. So let’s play the elimination game. If we rank them by which people like the most (i.e. got the most first preferences), it’s a fine line as to whether ‘deal’ or ‘no deal’ gets dropped first. But what happens if we rank them by which was most disliked? Now it’s a close call between either “remain’ or ‘no deal’ getting dropped first, but the PM’s deal easily gets through.

The choice rests to a significant extent on how people weight extremes. How much weight should be put on people’s perceptions of the merits of especially good or bad outcomes, especially if they are on different dimensions? Loss aversion is a well-known example: with subjects putting more weight on a £ lost than a £ gained. Combine positives and negatives within the same choice, then it gets even more complicated. For example, when buying a car, people may act as satisficers on some dimensions (make sure that none of the wheels will fall off and the brakes work OK), but then switch to being maximisers on other dimensions (it looks beautiful and has great acceleration).

Hirsch’s account of the ‘economics of neighbouring’ illustrates the effect in an everyday context. Is it worth getting to know your neighbours? Some of them will be great. They could look out for your property when you are away. They might bring you chicken soup when you are sick. On the other hand, you might really dislike one of them. And if you say hello once, will you be stuck in obligatory conversation for ever more? Hirsch concluded that many people decide not to engage with their neighbours, even though there would be many benefits, because these seen as outweighed by the risk of a bad interaction with one neighbour (Let’s not even get into Prospect theory, and how framing choices as between risks versus gains affects what people choose).

So where does this leave us? For the ultra geeky, it suggests that we might seek to apply the same kind of rigour to political decision making as has been applied to areas such as recruitment. This might, for example, make the case for quadratic voting, so that people could express a preference in a non-linear way to signal things they really like or dislike. That’s a long way from where we are now. Political processes need not just technical robustness, but legitimacy, familiarity, and a sense of procedural justice. But it might at least suggest there is room, between referendums and Parliament, for more subtle ways of drawing out the complexities of public preference.