Zachary Wojtowicz
(why-toe-vitch)
Postdoctoral Fellow at MIT
Ph.D. in Behavioral Economics,
M.A. in Machine Learning from Carnegie Mellon University
I work at the intersection of behavioral economics and computer science. My research examines how psychological factors impact the efficiency of digital platforms, firms, and markets. I apply these insights to study how artificial intelligence, machine learning, and other algorithms can be applied to enhance people's ability to learn, decide, collaborate, and create. I am currently a postdoctoral fellow at MIT, advised by Sendhil Mullainathan, Asu Ozdaglar, and Daron Acemoglu.
Working Papers
From Weights to Words: Expressing and Editing Preference Model Inferences in Natural Language
With Ayush Nayak and Jacob Andreas
Shared Context, Coordination Costs, and the Limits of Contracting
Model Diversity and Dynamic Belief Formation
Boredom and Flow: An Opportunity Cost Theory of Motivational Attention
Publications
With George Loewenstein. The Journal of Economic Literature, 2025
Willful Inattention: Keeping Aversive Information Out of Mind
With Andras Molnar, Russell Golman, and George Loewenstein. Current Opinion in Psychology, 2025
Push and Pull: A Framework for Measuring Attentional Agency on Digital Platforms
Undermining Mental Proof: How AI Can Make Cooperation Harder by Making Thinking Easier
With Simon DeDeo. Proceedings of the AAAI Conference on Artificial Intelligence, 2025
When and Why is Persuasion Hard? A Computational Complexity Result
Proceedings of the AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society, 2024
Cognition: A Study in Mental Economy
With George Loewenstein. Cognitive Science, 2023
The Motivational Processes of Sense-Making
Curiosity and the Economics of Attention
With George Loewenstein. Current Opinion in Behavioral Sciences, 2020
From Probability to Consilience: How Explanatory Values Implement Bayesian Reasoning
With Simon DeDeo. Trends in Cognitive Science, 2020
Media Coverage
Other Research