Incentives shape how humans co-create with generative AI

TL;DR

This study demonstrates that incentive structures influence how humans use generative AI, with originality rewards fostering more diverse and selective AI use in creative writing tasks.

Contribution

It provides experimental evidence that incentives shape AI co-creation, affecting diversity and usage strategies in collaborative human-AI tasks.

Findings

Rewarding originality increases collective diversity in AI-assisted writing.

Incentivized participants use AI suggestions more selectively.

Incentive structures influence behavioral strategies in AI co-creation.

Abstract

Generative AI is quickly becoming an integral part of people's everyday workflows. Early evidence has shown that while generative AI can increase individual-level productivity, it does so at the cost of collective diversity, potentially narrowing the set of ideas and perspectives produced. Our research stands in contrast to this concern: through a pre-registered randomized control trial, we show that incentives mediate AI's homogenizing force in a creative writing task where participants can use AI interactively. Participants rewarded for originality relative to peers produce collectively more diverse writing than those rewarded for quality alone. This divergence is driven not by abandoning AI, but by how participants use it: those incentivized for originality incorporate fewer AI suggestions verbatim, relying on the model more selectively for brainstorming, proofreading, and targeted edits. Our results reveal that the effects of generative AI depend not only on the technology itself, but also the behavioral strategies and incentive structures surrounding its use.