Introduction

(Written with extensive AI-assistance, including in drafting)

Effective altruism has moved billions of dollars toward evidence-based interventions and saved lives. The analytical machinery the community has built (cost-effectiveness models, uncertainty quantification, comparative frameworks) represents a real contribution to how philanthropy works. These achievements are what makes the problem I'm describing so costly.

EA assembled one of the most capable, motivated, and intellectually diverse groups of people on earth. Tens of thousands of people with backgrounds spanning medicine, technology, policy, behavioral science, philosophy, and more, drawn together by a shared commitment to figuring out how to do the most good.

Then it built a system that asks for their labor and money while largely ignoring what they know.

EA is exceptionally good at one epistemic task: given a cause area, identifying the most cost-effective interventions within it. But there's a different task, discovering entirely new categories of opportunity, that the community is structurally resistant to performing.[^1] The primary reason is that EA treats its members as resources to be deployed, not as sources of insight to be listened to.

This post argues that EA's most important epistemic resource is the distributed knowledge and diverse perspectives of its members, and [...]

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Outline:

(00:13) Introduction

(02:10) The Telescope Array

(03:57) How Ideas Actually Enter EA Priorities

(07:59) The Exceptions That Prove the Rule

(11:17) Why Path 5 Fails

(16:06) Why the Equilibrium Persists

(18:19) What Would a Functional Path 5 Look Like?

(20:19) Conclusion

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First published:

Source:

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Narrated by TYPE III AUDIO.