激励机制能引导人与AI协作时产出更多元创意。
Incentives shape how humans co-create with generative AI
- 用原创性奖励替代质量奖励，提升集体创作多样性。
- 原創獎勵组使用AI更少直接照搬，多用于头脑风暴和局部修改。
- 适合关注AI协作中激励设计的研究者与团队管理者。
生成式AI正快速融入日常工作中。早期研究表明，尽管它能提升个人效率，却可能削弱集体创意多样性，缩小想法范围。我们的研究通过预注册的随机对照实验发现，在可交互使用AI的创意写作任务中，激励机制能缓解AI的同质化影响：相比仅以质量为奖励标准的参与者，以相对原创性为奖励的参与者产生了更具多样性的集体作品。这一差异并非源于放弃使用AI，而是使用方式不同——原创性激励组较少直接采纳AI建议，而是更选择性地将模型用于头脑风暴、校对和针对性修改。结果表明，生成式AI的影响不仅取决于技术本身，更受使用行为策略和激励结构的调节。
原文摘要 · Abstract (English)
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.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。