To answer my own question, here is my best guess for how “good judgment” is different from “skill at forecasting.”
Good judgment can roughly be divided within 2 mostly distinct clusters:
Forming sufficiently good world models given practical constraints.
Making good decisions on the basis of such (often limited) models.
Forecasting is only directly related to the former, and not the later (though presumably there are some general skills that are applicable to both). In addition, within the “forming good world models” angle, good forecasting is somewhat agnostic to important factors like:
Group epistemics. There are times where it’s less important whether an individual has the right world models but that your group has access to the right plethora of models.
It may be the case that it’s practically impossible for a single individual to hold all of them, so specialization is necessary.
Asking the right questions. Having the world’s lowest Brier score on something useless is in some sense impressive, but it’s not very impactful compared to being moderately accurate on more important questions.
Correct contrarianism. As a special case of the above two points, in both science and startups, it is often (relatively) more important to be right about things that others are wrong about than it is to be right about everything other people are right about.
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Note that “better world models” vs “good decisions based on existing models” isn’t the only possible ontology to break up “good judgment.”
- Owen uses understanding of the world vs heuristics. - In the past, I’ve used intelligence vs wisdom.
To answer my own question, here is my best guess for how “good judgment” is different from “skill at forecasting.”
Good judgment can roughly be divided within 2 mostly distinct clusters:
Forming sufficiently good world models given practical constraints.
Making good decisions on the basis of such (often limited) models.
Forecasting is only directly related to the former, and not the later (though presumably there are some general skills that are applicable to both). In addition, within the “forming good world models” angle, good forecasting is somewhat agnostic to important factors like:
Group epistemics. There are times where it’s less important whether an individual has the right world models but that your group has access to the right plethora of models.
It may be the case that it’s practically impossible for a single individual to hold all of them, so specialization is necessary.
Asking the right questions. Having the world’s lowest Brier score on something useless is in some sense impressive, but it’s not very impactful compared to being moderately accurate on more important questions.
Correct contrarianism. As a special case of the above two points, in both science and startups, it is often (relatively) more important to be right about things that others are wrong about than it is to be right about everything other people are right about.
___
Note that “better world models” vs “good decisions based on existing models” isn’t the only possible ontology to break up “good judgment.”
- Owen uses understanding of the world vs heuristics.
- In the past, I’ve used intelligence vs wisdom.