arXiv AI By Yueqi Xie, Tao Qi, Jingwei Yi, Xiyuan Yang, Ryan Whalen, Junming Huang, Qian Ding, Yu Xie, Xing Xie, Fangzhao Wu

Measuring Human Contribution in AI-Assisted Content Generation

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The paper "Measuring Human Contribution in AI-Assisted Content Generation" addresses the challenge of determining how much human input influences content produced with generative AI. It proposes an information-theoretic framework that calculates the mutual information between human input and AI output relative to the self-information of the output, thereby quantifying the proportion of human contribution. Experiments across various creative domains show that this measure can distinguish different levels of human involvement in AI-assisted works.

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