Reasoning about the economic impacts of frontier AI: how does AI diffuse through work, how do new tasks emerge, how does household use substitute for labor, how do technical benchmarks relate to economic indicators.
About the project
I am broadly interested in mentoring researchers studying the economic impacts of frontier AI. With respect to a specific project, I am flexible and would generally like to co-design something with the mentee that is calibrated to their expertise and skills.
Some general directions of interest: Broadening task-level adoption Motivation: 50% US workers across 90% occupations use AI for just 20% tasks Tracking the emergence, utility, and endurance of new work tasks Motivation: new tasks/workflows/sectors are the base of economic growth in the long-run Testing whether consumer use substitutes for labor Motivation: consumer use for household purposes is more frequent than work purposes based on OpenAI/Google usage data analysis. Consumers using AI to navigate tasks like financial planning or tax filing could reduce demand for services and associated workers Bridging economic indicators with technical evaluations Motivation: we have growing infrastructure on both fronts like https://digitaleconomy.stanford.edu/project/indicators/ but not enough connection Eliciting user behavior from superusers whether on household or work side Motivation: huge disparities in intensity of use; could learn a lot from those who have adopted the most
Theory of change
My work has directly advanced frontier AI policy and governance in many jurisdictions (e.g. lead author on California Report that directly led to SB 53 and thereby almost all US state-level frontier AI policy; direct impact on both legislation and implementation of EU AI Act). In the past year, I have shifted from the standard governance issues to economic impacts and policy, because there is clear public and policymaker demand in this area. Therefore, this area both addresses core risks brought about by the transition to transformative AI (e.g. job loss) but also top-level national strategic policies and the financial sustainability of the frontier AI industry.
Your role
Depends on mentee
Prerequisites
No strict prerequisites. Familiarity with and interest in the research/data available on the economic impacts of frontier AI is expected. Running evals, doing data analysis, and do technical economic analysis are all useful skills. Using agents effectively in research will be useful.
Application question(s)
Write a 500-word research proposal for how to study the effects on labor brought about by consumer household use of frontier AI.
- Prioritize areas where (i) household use is already high and (ii) mappings from household use to service/labor suppression are easier to reason about, grounded in usage data analyses published by frontier labs, especially consumer-oriented labs like OpenAI and Google.
- Focus on concrete datasets and be very specific and plain in how you would execute this research.
I am asking this question to understand how you would concretely execute the research; you do not need to spend many, if any, words motivating the problem or surveying related work or so on. Focus on what you would actually do.
About the mentor
Rishi Bommasani is a senior research scholar at Stanford’s Institute for Human-Centered Artificial Intelligence. He researches the societal and economic impact of frontier AI. His research has won multiple paper awards at AI conferences and has been covered by the New York Times, Nature, Science, the Washington Post, and Wall Street Journal. His research shapes public policy: he is the lead author of the California Report on Frontier AI Policy that led to the first US laws on frontier AI, an independent expert chair of the EU AI Act Code of Practice that clarifies the first comprehensive worldwide laws on frontier AI, and an author of the International Scientific Report on the Safety of Advanced AI. Rishi received his PhD in computer science from Stanford University, where he was advised by Percy Liang and Dan Jurafsky.