EconCS Seminars

Speaker 1: Johann Gaebler (Harvard University) Title 1: A Simple, Statistically Robust Test of Discrimination Abstract 1: In observational studies of discrimination, the most common statistical approaches consider either the rate at which decisions are...

Time & Location: Friday, December 5, 1:30pm - 2:30pm at SEC LL 2.221 Title: Natural Centralization in Decentralized Finance (joint with Adrian Casillas and Maryam Farboodi) Abstract: Can centralization arise absent barriers to entry? We confront this...

Time & Location: Friday, November 21, 1:30pm - 2:30pm at SEC LL 2.221 Speaker 1: Itai Shapira (Harvard University) Title 1: Dis tribution over rewards for pluralistic AI alignment Abstract 1: Current alignment pipelines based on human feedback, typically...

Nikhil Garg (Cornell Tech) Recommendations in high-stakes settings Recommendation and search systems are now used in high-stakes settings, including to help find jobs, schools, and partners. Building public interest recommender systems in such settings...

Tina Eliassi-Rad (Northeastern) The Trilemma of Truth in Large Language Models In our human-AI society, we often attribute human characteristics to large language models (LLMs) and claim that they "know" things. LLMs have an internal probabilistic...

Kehang Zhu (Harvard): TBA

Vijay Vazirani (UC Irvine) Cardinal-Utility Matching Markets: Pricing is Intractability, but Nash Bargaining Works! For a mechanism to be truly impactful, it must combine strong game-theoretic properties with computational efficiency -- a classic example...

Tracy Liu (Tsinghua University) When Experimental Economics Meets Large Language Models: Evidence-based Tactics Advancements in large language models (LLMs) have sparked a growing interest in measuring and understanding their behavior through experimental...

Hanna Halaburda (NYU) - 60 min The Impossibility of Transparent and Decentralized DeFi Trading Decentralized finance (DeFi) aspires to replace traditional intermediaries with transparent, decentralized markets. Yet we show that transparency itself creates...

Ruru Hoong (Harvard) Artificial intelligence (AI) signals are increasingly deployed as human decision-making aids across many critical applications, but human cognitive biases can prevent them from improving outcomes. We propose calibrated coarsening...