Saturday, May 26, 2012

Evaluating The Regret Heuristic, Part II

In a comment to my post on how our regrets change over time, Eric Schwitzgebel asks, 
But why adopt regret minimization as a goal at all? Regret seems distorted by hindsight bias, status quo bias, and sunk cost bias, at least.
I've written before that projecting your future views about your present actions can be a good way to make decisions. So, Eric's prompting is a good occasion to re-evaluate that.

Given perfect information, the theoretically best way to make decisions is to 1) calculate the costs and benefits of each possible outcome, 2) estimate how your choice affects the relative probability of those outcomes, 3) use the costs and benefits as inputs to some sort of valuation function, and 4) make the decision with the highest probabilistic value. 

Cost-benefit analysis is a common way to implement this, with, say, QALYs as the value measure. If you have perfect information, this is just math. 

But as Ben Casnocha says, if you don't have enough information, that framework can break down. In particular, even when #2 is pretty straightforward, #1 can still be very tricky. For example, although studying for the LSAT makes it much more likely that I will earn a JD, it's still hard to quantify the precise costs and benefits of entering that earning that degree. 

Here is where the regret heuristic can be useful. Instead of explicitly tallying each cost and benefit, it asks: in total, which would you regret more: studying or not studying? 

This is in fact a simplifying measure, but there remains oodles of freedom in how you perform the regret estimation. For example, you can:
Ultimately, I still think that the regret heuristic can be a useful one. But tread carefully, as there are many crucial micro-decisions to make; it's not magic.