Which AI economics and governance research most needs independent expert evaluation? (help The Unjournal prioritize it)

The Unjournal commissions public expert evaluations and ratings of research (and “pivotal questions”) with potential for global impact. We’re currently making a push to consider AI economics and governance research.[1] We’re seeking input from people who use this: which themes, which papers/projects, which claims, who should evaluate them, what should evaluators focus on, and why? (If you only have a moment, skip to “What would help most”.) Why do this? (Why us, and why now?) The usual story, which you’re ~probably on board with: AI is advancing rapidly, and becoming more clearly and deeply important to most major global priorities. It’s having large actual and predicted impact on the economy and the concentration of power. This is itself entangled with AI safety and AI global catastrophic risks. “How fast will capabilities grow and replace human work?” “How will gains flow to labor versus capital?” “How will revenue and compute accumulate in a few firms and countries?” “Will regulation change which models get released where?” Questions like these impact the nature of catastrophic AI-risk (resources, race dynamics, human empowerment, state capacity, etc.), as well as the strategic approaches to handling it. There are also direct implications for global poverty, global health systems, and for non-AI GCR (e.g., bioengineered pandemics).[2] These questions (and ‘cruxes’) seem to directly impact a set of live decisions surrounding AI safety strategy, philanthropic funding, regulation and legal safeguards, public spending, international controls, advocacy, and more. Economists, social scientists, and policy analysts have been moving into this area. Some of the work crosses disciplinary lines. Economists are now modeling AI scaling and recursive self-improvement. Growth theorists are co-authoring scenario models with funding and data from frontier labs. Forecasting researchers are eliciting and synthesizing beliefs and predictions from economists, AI-company staff, an