Decision Mechanics

Insight. Applied.

Human brains hate probability

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There was a great article published last month discussing risk communication.

Statistician Regina Nuzzo is quoted as saying

Human brains hate probability, they hate ambiguity, they hate the uncertainty. We’re just not wired to deal with this sort of thing very well.

Science journalist Tara Haelle explains that it’s difficult to separate reporting from influence. She notes that covering polls about willingness to take a vaccine set behavioural norms.

The more people question vaccines, the more people question vaccines. Vaccine hesitancy is contagious.

So, in summary, we find it difficult to think about probabilities, but are easily lead by opinion. This is why it’s increasingly essential for everyone to develop a degree of statistical literacy. With so much data flying around, and so many people commandeering it to promote their own view, we all need to be able to come to our own informed conclusions.

Photo by Naser Tamimi on Unsplash

Decision fatigue

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This Economist has an article this week on the dangers of decision fatigue.

Research suggests that people fall back into making "default" decisions when they are tired. Examples are cited from finance, law and medicine.

One thing that isn’t discussed is the obvious benefits of automated decision-making—computers don’t suffer from exhaustion. The more we can have computers advise decision-makers on routine decisions, the more humans can devote their limited energy to more complex cases.

The article notes that there may be value using software to monitor decisions and nudging people when the pattern of their decision-making changes. This is an interesting approach—have the computer critique the decision-making process rather than the decision itself.

Photo by Luis Villasmil on Unsplash

Why is everything so complicated?

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Ever expressed frustration that stuff is unnecessarily complicated? If so, a new paper published in Nature might have an explanation.

Apparently, when solving problems, we have a natural inclination to add things. For instance, when asked to make a design symmetrical, people are more likely to do so by adding features, rather than removing them.

You can see evidence of this in a range of technical domains.

  • UX designers add more cues to address usability issues when they should make the the design less "noisy".

  • Software developers add more code to fix problems instead of simplifying existing code.

  • Data scientists chase R-squared improvements by adding more features.

Simplification is a crucial component of effective decision science. Approaches such as confrontation analysis strip away extraneous details and focus your attention on your immediate dilemmas.

It’s not all doom and gloom. You can "nudge" people to simplify using appropriate cues. For instance, maybe you could display prominent "lines of code" counts, or focus on predictive R-squared when modelling.

Given our instinctive biases we must be vigilant in the search for creeping complexity. Science is showing us that it’s more work to keep it simple.

As President Woodrow Wilson explained,

If I am to speak ten minutes, I need a week for preparation; if fifteen minutes, three days; if half an hour, two days; if an hour, I am ready now.

Photo by Gayatri Malhotra on Unsplash