Trailhead: Ian Leslie. "Before You Answer, Consider the Opposite Possibility". The Atlantic (2021-04-25).

I've heard of the concept that if you take the summary of a group's individual estimate about some objective measurement, e.g., the number of beans in a jar, that the average of the group is better than any of the individual estimates, even the estimates of an expert bean estimator. That phenomenon seems simple, or at least it makes intuitive sense. Getting a pile of different estimates means that you're also getting a pile of different assumptions and biases. "Pile of biases" sounds problematic, but if you take a single individual's estimate, you're still getting an assumption or a bias. However, you're only getting that one person's biases—more biases will be more diverse and will likely distribute themselves about a better value.

Can you do that in your own head? Maybe.

"Eliminating bias" or "total objectivity" sound like fine ideas, but it's nonsense to believe it's possible or true or even desirable. What you want are those biases being aligned in a way that give you multiple vantage points on what you're trying to understand. Maybe "alignment" is better when randomly distributed, but that sounds like some Monte Carlo business in a model, not a way to think in your head. What you can do in your head is consider what happens if the opposite of what you think is true, or how someone with an opposite view would think. This gives you some of the benefits of tapping into the distribution of biases that you would get from a group of people.

Keep yourself on your toes and don't grasp on to an approach too soon—especially don't take your own approach too soon. Eventually you'll have to decide what to do, and you still might do what you would have done in the first place, but considering alternative approaches will help you cover blind spots.

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