Overview
I primarily work on topics in tech policy and social policy. Right now I’m especially interested in AI regulation, biases embedded in legal institutions, and the future of work. I use tools from behavioral economics and machine learning. My approach allows me to develop the basic science of decision-making while yielding policy insights. Here’s what I’ve found so far:
Public interest technology clinics help students learn the hardest part of ethical data work: how to make responsible decisions under uncertainty when critique alone is not enough. (FAccT 2026)
Algorithmic recommendation systems learn our subconscious biases and spread them across online communities. (WP)
Money is more motivating for Western workers than it is for workers elsewhere in the world. (NHB 2024)
Venture capitalists consistently invest in startups that are predictably doomed to fail. (WP)
Criminal justice algorithms are vulnerable to biased usage above and beyond any bias in the algorithms themselves. (WP)
Groupthink causes juries to systematically convict defendants, independent of guilt. (PNAS 2020)
Here are some questions I’m thinking about:
How much of our motivation to work is driven by economic need versus mere socialization?
Is the consolidation of dating app companies distorting modern dating?
Are differences in today’s local laws traceable to local differences in the intensity of historical slavery?
Is there a reliable cure for groupthink?