High-impact decisions—like choosing careers, allocating grants, or prioritizing causes—often rely on intuition rather than quantitative estimates. This leads to misallocated resources, redundant efforts, and inconsistent comparisons across domains. A standardized approach to estimating expected impact could help redirect billions of dollars or decades of talent toward more effective outcomes, particularly in fields like effective altruism where optimization matters.

How It Could Work

One way to address this is by creating reusable, modular estimates for high-stakes decisions. These estimates would quantify impact (e.g., disability-adjusted life years per dollar, counterfactual career influence) while documenting assumptions and methodologies transparently. For example, a career-path estimate might model the expected influence of an AI policy role by combining probabilities of policy change, scale of impact, and counterfactual substitution by others. These components could then be repurposed for other domains, like climate advocacy or think-tank roles.

Who Would Benefit

This approach could serve:

• Individuals making career or skill-building decisions.
• Organizations evaluating grants or prioritizing interventions.
• Researchers comparing cause areas or methodologies.

Stakeholders like estimate producers (e.g., research groups) might contribute to build reputation, while end users save time and improve decisions. The broader community could benefit from shared learning and iterative improvements.

Execution Strategies

A minimal version could start with 2–3 high-leverage domains (e.g., AI safety careers and biosecurity grants), using open-source tools like Guesstimate or Squiggle. Estimates could be published in a centralized repository with version control and feedback mechanisms. Scaling up might involve:

• Expanding to other domains with templatized methodologies.
• Developing interactive tools for sensitivity analysis.
• Curating community contributions to avoid redundancy.

Existing efforts, like 80,000 Hours' qualitative career reviews or Open Philanthropy’s grant investigations, lack reusable quantitative frameworks. By focusing on modularity and collaboration, this could become a hub for evolving decision-making tools—like a "GitHub for impact estimation."