A University of Chicago economist argues that price elasticity data is the missing piece needed to understand AI's impact on jobs. While companies like Anthropic and OpenAI analyze AI exposure of tasks, economist Alex Imas says this alone provides an illusory understanding of job displacement risk. Current tools can't predict whether AI productivity gains will create or destroy jobs.

Imas points out that the US government's occupational task database, while useful, doesn't capture the crucial question of how demand responds when AI reduces costs. For example, a dating app developer using AI coding tools might complete work in one day instead of three, but whether this leads to layoffs or hiring depends entirely on how much demand increases when prices drop. This price elasticity varies dramatically across industries.

Imas calls for a "Manhattan Project" to collect comprehensive price elasticity data across all sectors, similar to how supermarket scanner data tracks grocery prices. Without this information, policymakers are "operating in the dark" when planning for AI's workforce impact. The economist emphasizes that fields not currently exposed to AI will become exposed, making comprehensive data collection essential for understanding our AI-enabled economic future.