Greetings listeners! It is a pleasure to introduce this week’s guest on the podcast, Ashesh Rambachan, an assistant professor of economics at MIT. I wanted to talk to Ashesh for two main reasons. First, because I wanted to, and second, because I was aware of some of his recent work in econometrics. His recent article on evaluating the fragility of parallel trends in difference-in-differences just came out in the Review of Economic Studies. I’m also intrigued by his work with Sendhil Mullainathan on machine learning, algorithmic fairness as well as generative AI. Having a specialist in both causal inference, artificial intelligence and machine learning is rare, so I thought sitting down with him to learn more about his story would be a lot of fun, not just for me, but for others too. With that said, here you go! I hope you enjoy the interview! Thank you again for all your support! Scott's Substack is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Get full access to Scott's Substack at causalinf.substack.com/subscribe