Executive summary: This exploratory post argues that Effective Altruism’s heavy reliance on measurable outcomes may cause it to overlook high-impact opportunities—such as systemic reforms—simply because they are harder to quantify, and it calls for broader evaluative tools and risk-tolerant funding models to address this blind spot.
Key points:
Core critique: EA’s emphasis on measurement and legibility risks biasing us toward interventions like bednets that are easier to quantify, while undervaluing complex, potentially more impactful systemic changes.
Illustrative analogy: The author contrasts easily measured interventions (e.g. bednets) with harder-to-evaluate systemic reforms (e.g. healthcare system strengthening), suggesting we may favor the former not because they’re more effective, but because they’re more countable.
Limitations of expected value (EV): Numerical models like EV can obscure high failure probabilities and reinforce our tendency to prefer safe, measurable options over riskier ones with large upside.
Rebuttal of common objections: The post defends the idea of incorporating qualitative evidence and expert judgment as a form of expanded rigor—not a retreat from it—and challenges the notion that systemic interventions are too slow, political, or uncertain to pursue.
Proposed path forward: The author recommends a dual approach: (a) dedicating a share of funding to high-risk, hard-to-measure systemic interventions, and (b) improving tools for evaluating qualitative, long-term, and root-cause-based strategies.
Underlying question: How can EA retain its analytical discipline while broadening its conception of impact to include the less quantifiable but potentially more transformative?
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Executive summary: This exploratory post argues that Effective Altruism’s heavy reliance on measurable outcomes may cause it to overlook high-impact opportunities—such as systemic reforms—simply because they are harder to quantify, and it calls for broader evaluative tools and risk-tolerant funding models to address this blind spot.
Key points:
Core critique: EA’s emphasis on measurement and legibility risks biasing us toward interventions like bednets that are easier to quantify, while undervaluing complex, potentially more impactful systemic changes.
Illustrative analogy: The author contrasts easily measured interventions (e.g. bednets) with harder-to-evaluate systemic reforms (e.g. healthcare system strengthening), suggesting we may favor the former not because they’re more effective, but because they’re more countable.
Limitations of expected value (EV): Numerical models like EV can obscure high failure probabilities and reinforce our tendency to prefer safe, measurable options over riskier ones with large upside.
Rebuttal of common objections: The post defends the idea of incorporating qualitative evidence and expert judgment as a form of expanded rigor—not a retreat from it—and challenges the notion that systemic interventions are too slow, political, or uncertain to pursue.
Proposed path forward: The author recommends a dual approach: (a) dedicating a share of funding to high-risk, hard-to-measure systemic interventions, and (b) improving tools for evaluating qualitative, long-term, and root-cause-based strategies.
Underlying question: How can EA retain its analytical discipline while broadening its conception of impact to include the less quantifiable but potentially more transformative?
This comment was auto-generated by the EA Forum Team. Feel free to point out issues with this summary by replying to the comment, and contact us if you have feedback.