  Human-created works represent critical data inputs to artificial intelligence
(AI). Strategic behavior can play a major role for AI training datasets, be it
in limiting access to existing works or in deciding which types of new works to
create or whether to create new works at all. We examine creators' behavioral
change when their works become training data for AI. Specifically, we focus on
contributors on Unsplash, a popular stock image platform with about 6 million
high-quality photos and illustrations. In the summer of 2020, Unsplash launched
an AI research program by releasing a dataset of 25,000 images for commercial
use. We study contributors' reactions, comparing contributors whose works were
included in this dataset to contributors whose works were not included. Our
results suggest that treated contributors left the platform at a
higher-than-usual rate and substantially slowed down the rate of new uploads.
Professional and more successful photographers react stronger than amateurs and
less successful photographers. We also show that affected users changed the
variety and novelty of contributions to the platform, with long-run
implications for the stock of works potentially available for AI training.
Taken together, our findings highlight the trade-off between interests of
rightsholders and promoting innovation at the technological frontier. We
discuss implications for copyright and AI policy.
