activity
20182026
collaborators

8 papers

cs.AI2026

Algorithmic Impact Reveals the Hidden Social Choice Structure of Alignment

Zachary Wojtowicz, Michelle Si, Finale Doshi-Velez +1

When an AI algorithm makes decisions that affect more than one person, aligning it becomes a problem of social choice: how should people's divergent preferences about system behavi…

cs.LG2026

From Weights to Words: Expressing and Editing Preference Model Inferences in Natural Language

Zachary Wojtowicz, Ayush Nayak, Jacob Andreas

The growing use of statistical learning algorithms to infer human preferences from high-dimensional choice data runs up against a fundamental challenge: choice alternatives typical…

cs.CY2024

When and Why is Persuasion Hard? A Computational Complexity Result

Zachary Wojtowicz

As generative foundation models improve, they also tend to become more persuasive, raising concerns that AI automation will enable governments, firms, and other actors to manipulat…

cs.CY2024

Undermining Mental Proof: How AI Can Make Cooperation Harder by Making Thinking Easier

Zachary Wojtowicz, Simon DeDeo

Large language models and other highly capable AI systems ease the burdens of deciding what to say or do, but this very ease can undermine the effectiveness of our actions in socia…

cs.CY2024

Push and Pull: A Framework for Measuring Attentional Agency on Digital Platforms

Zachary Wojtowicz, Shrey Jain, Nicholas Vincent

We propose a framework for measuring attentional agency, which we define as a user's ability to allocate attention according to their own desires, goals, and intentions on digital…

q-bio.NC2020

From Probability to Consilience: How Explanatory Values Implement Bayesian Reasoning

Zachary Wojtowicz, Simon DeDeo

Recent work in cognitive science has uncovered a diversity of explanatory values, or dimensions along which we judge explanations as better or worse. We propose a Bayesian account…