In Psychology of Intelligence Analysis, Richards Heuer advocates that we quantify expressions of uncertainty: “To avoid ambiguity, insert an odds ratio or probability range in parentheses after expressions of uncertainty in key judgments.”
His suggestion reminds me of my pet peeve about the unquantified notion of reasonable doubt in the American justice system. I’ve always wanted (but never had the opportunity) to ask a judge what probability of innocence constitutes a reasonable doubt.
Unfortunately, as Heuer himself notes elsewhere in his book, we human beings are really bad at estimating probabilities. I suspect (with a confidence of 90 to 95%) that quantifying our uncertainties as probability ranges will only suggest a false sense of precision.
So, what can we do to better communicate uncertainty? Here are a couple of thoughts:
- We can calibrate estimates based on past performance. It’s unclear what will happen if people realize that their estimates are being translated, but, at worst, it feels like good fodder for research in judgment and decision making.
- We can ask people to express relative probability judgments. While these are also susceptible to bias, at least they don’t demand as much precision. And we can always vary the framing of questions to try to factor out the cognitive biases they induce.
Also, we talk about uncertainty, it is important that we distinguish between aleatory and epistemic uncertainty.
When I flip a coin, I am certain it has a 50% chance of landing heads, because I know the probability distribution of the event space. This is aleatory uncertainty, and forms the basis of probability and statistics.
But when I reason about less contrived uncertain events, such as estimating the likelihood that my bank will collapse this year, the challenge is my ignorance of the probability distribution. This is epistemic uncertainty, and it’s a lot messier.
In summary, we have to accept the bad news that the real world is messy. As a mathematician and computer scientist, I’ve learned to pursue theoretical rigor as an ideal. Like me, you may find it very disconcerting to not be able to treat all real-world uncertainty in terms of probability spaces. Tell it to the judge!