"Good judgement" and its components

# ["Good judgement" and itscomponents](https://forum.effectivealtruism.org/posts/xMRpu4nAeGeAXy9ns/good-judgement-and-its-components)

by [Owen Cotton-Barratt](https://forum.effectivealtruism.org/users/owen_cotton-barratt?from=post_header)

Aug 19 20204 min read11

# 64

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_Meta: Lots of people interested in EA (including me) think that something like "good judgement" is a key trait for the community, but there isn't a commonly understood definition. I wrote a quick version of these notes in response to a question from Ben Todd, and he suggested posting them here. These represent my personal thinking about judgement and its components._

**Good judgement** is about mental processes which tend to lead to good decisions. (I think good decision-making is centrally important for longtermist EA, for reasons I won't get into here.) Judgement has two major ingredients: **understanding of the world**, and **heuristics**.

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**Understanding of the world** helps you make better predictions about how things are in the world now, what trajectories they are on (so how they will be at future points), and how different actions might have different effects on that. This is important for helping you explicitly think things through. There are a number of sub-skills, like **model-building**, having **calibrated estimates**, and just **knowing relevant facts**. Sometimes understanding is held in terms of implicit predictions (perhaps based on experience). How good someone's understanding of the world is can vary a lot by domain, but some of the sub-skills are transferrable across domains.

You can improve your understanding of the world by learning foundational facts about important domains, and by practicing skills like model-building and forecasting. You can also improve understanding of a domain by importing models from other people, although you may face challenges of being uncertain how much to trust their models. (One way that models can be useful without requiring any trust is giving you clues about where to look in building up your own models.)

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**Heuristics** are rules of thumb that you apply to decisions. They are usually held implicitly rather than in a fully explicit form. They make statements about what properties of decisions are good, without trying to provide a full causal model for why that type of decision is good. Some heuristics are fairly general (e.g. "avoid doing sketchy things"), and some apply to specific domains (e.g. "when hiring programmers, put a lot of weight on the coding tests").

You can improve your heuristics by paying attention to your experience of what worked well or poorly for you. Experience mig

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