(2019-11-15) Hobart Bayesian Goal Updating

Pamela J. Hobart: Bayesian Goal Updating. One day, you wake up and set a goal. Goal A...you do not achieve Goal A. It's not even clear you're making good progress.

all of the intermediate steps between goal setting, revision, and abandonment remain basically murky.

You start with a prior hypothesis that you ought to do something.

Next, you go try whatever it is and get some feedback from the world. Or, you fail to attempt reaching your goal, which also constitutes a piece of evidence.

Other types of problems carry weight but not conclusive weight - like partial progress up to a surmountable but difficult roadblock. Or maybe you're not really good at the thing you're attempting, but you really want to do it.

On the other hand, you may have often experienced flow while working towards your goal, achieved some markers of success, and felt basically good throughout. All these signs point to becoming more certain that your goal-hypothesis is a good one.

Goals are hypotheses about what one ought to pursue. (Thinking In Bets)

They are cyclical, not binary. And you can be wrong about your goals.

These goal-hypotheses live at the confluence of what you want now, what you want later, what you're currently capable of, what you might later be capable of, what seems good all-things-considered within the totality of your life, and what else is going on in the world.

This process can and will happen over and over and you gather new considerations about what it will take to learn something, what the payoff is, what your opportunity costs are, and how you feel.