Bharat Chandar is a labor economist working on understanding AI’s impact on work. His recent projects include work with Erik Brynjolfsson and Ruyu Chen tracking “canaries in the coal mine” for entry-level employment changes in jobs exposed to AI. He also recently surveyed the state of knowledge about AI and labor markets.
His ongoing work has focused on three areas. The first asks, how will workers adjust if we see AI-driven changes in hiring? Which workers will have an easier or more challenging time if displaced, and where should we target support? The second asks, how can we use AI to make it easier for people to learn new things and pursue new forms of work? Third, how will impacts of AI differ across the world?
Bharat also writes essays about AI and economics on Substack.
Prior to joining the lab he received his PhD in economics from Stanford GSB, advised by Rebecca Diamond, Chris Tonetti, and Nick Bloom. His dissertation studied how expansion in college access has slowed down the growth in inequality between more- and less-educated workers.
Before his PhD, Bharat spent two years as an economist at Uber, where he worked on research studying methods like tipping, ratings, and nudges to promote service quality. He also had a stint at Oracle working on measuring causal impact of social media advertising. He received an MS in statistics and BA in economics at the University of Chicago.
