Fall 2024 EconCS Seminars

Abstract: As algorithms increasingly interact with rational, self-interested individuals, their design must take participants’ incentives into account. The traditional focus in algorithmic game theory literature has been the design of algorithms that...

Abstract: We study how people form expectations about the performance of artificial intelligence (AI) and consequences for AI adoption. Our main hypothesis is that people rely on human-relevant task features when evaluating AI, treating AI failures on...

We study worst-case VCG redistribution mechanism design for the public project problem. We use a multilayer perceptron (MLP) with ReLU activation to model the payment function and use mixed integer programming (MIP) to solve for the worst-case type...

(joint works with Ran Ben Moshe, Noam Nisan, and Yannai Gonczarowski) Abstract: Selling multiple goods is a notoriously difficult problem. Inter alia, the following non-monotonicity phenomenon has been exhibited by Hart and Reny (2015): the willingness to...

We introduce the infinite horizon Markov exchange economy, a dynamic stochastic general equilibrium (DSGE) model that explicitly incorporates time and uncertainty, generalizing both the Radner stochastic exchange economy and the infinite horizon...

Title : GemNet: Menu-Based, Strategy-Proof Multi-Bidder Auctions Through Deep Learning (Jeff Jiang) Automated mechanism design (AMD) uses computational methods for mechanism design. Differentiable economics is a form of AMD that uses deep learning to...

Title: Persuasion and Optimal Stopping (joint work with Sivakorn Sanguanmoo (MIT) and Weijie Zhong (Stanford GSB)) Abstract: We analyze the interplay between persuasion, timing, and commitment. A principal conducts a sequence of statistical experiments to...

Abstract: Algorithmic predictions are increasingly guiding societal resource allocations by identifying individuals for intervention. Fueling their adoption is their strong performance in standard evaluation settings. Yet, these settings are narrow and...

Abstract: The immense success of ML systems relies heavily on large-scale high-quality data. The high demand for data has led to several paradigms that involve selling, exchanging, and sharing data. This naturally motivates studying economic processes...

Abstract: Fair division is an age-old problem that deals with the allocation of items among agents with diverse preferences in a fair and efficient way. It naturally arises in various real-life situations, from interpersonal to international conflicts. In...