Online content platforms commonly use engagement-based optimization when making
recommendations. This encourages content creators to invest in quality, but also rewards …

The advent of generative AI (GenAI) technology produces transformative impact on the
content creation landscape, offering alternative approaches to produce diverse, high-quality …

The agency problem emerges in today's large scale machine learning tasks, where the
learners are unable to direct content creation or enforce data collection. In this work, we …

Driven by the new economic opportunities created by the creator economy, an increasing
number of content creators rely on and compete for revenue generated from online content …

The design and evaluation of recommender systems often takes the perspective of
supervised machine learning, treating viewer preferences and the content catalogue as …

Online platforms such as YouTube, Instagram, TikTok heavily rely on recommender systems
to decide what content to show to which users. Content producers often aim to produce …

Generative AI (GenAI) will have significant impact on content creation platforms. In this
paper, we study the dynamic competition between a GenAI and a human contributor. Unlike …

The main result of this paper is an almost approximation-preserving polynomial-time
reduction from the most general multi-parameter Bayesian contract design (BCD) to single …

Motivated by the phenomenon of strategic agents gaming a recommender system to
maximize the number of times they are recommended to users, we study a strategic variant …

This survey overviews a new research agenda on the economics of machine learning,
pursued at the Strategic IntelliGence for Machine Agent (SIGMA) Lab at UChicago. This …