Fields like economics become ineffective when they prioritize conforming to disciplinary norms—like mathematical modeling—over solving complex, real-world problems. This professionalization creates monocultures where researchers focus on what is publishable within their field's narrow framework, rather than collaborating across disciplines to generate useful knowledge for issues like prison reform.

Every research paper presented at major conferences is paired with an official critic, or "discussant." This person's job is to translate the work for a broader audience, identify key takeaways, and provide constructive, public feedback, ensuring rigor and clarity.

The most significant gap in AI research is its focus on academic evaluations instead of tasks customers value, like medical diagnosis or legal drafting. The solution is using real-world experts to define benchmarks that measure performance on economically relevant work.

Don't dismiss high-leverage but hard-to-measure interventions like government capacity building. Use "cost-effectiveness thinking": create back-of-the-envelope calculations and estimate success probabilities. This imposes quantitative discipline on qualitative decisions, avoiding the streetlight effect of only focusing on what's easily measured.

Economist Michael Greenstone recounts how his academic communication style, efficient among peers, was perceived as abrasive and exclusionary in government, nearly getting him fired. To have real-world impact, experts must translate specialized jargon into accessible ideas, a skill academia doesn't teach or reward.

An aid agency's budget is dwarfed by a host country's ministry spending. Therefore, instead of running parallel programs, the most impactful approach is "system strengthening": working directly with local government to integrate evidence and optimize how they allocate their own, much larger, budgets.

Focusing solely on accelerating research with AI misses its primary purpose. The true value of research is its transformative effect on the organization. It's about creating shared understanding and changing perspectives, not just generating insights as quickly as possible.

Despite having the freedom to publish "inconvenient truths" about AI's societal harms, Anthropic's Societal Impacts team expresses a desire for their research to have a more direct, trackable impact on the company's own products. This reveals a significant gap between identifying problems and implementing solutions.

Academic journals often reward highly specialized, siloed research. This creates a professional dilemma for economists wanting to tackle complex, real-world policy problems that require an interdisciplinary approach, as that work is less valued by traditional publishing gatekeepers.