Recognizable Human Input, Copyrightable AIGC

This article examines the evolving intersection of copyright law and AI-generated content (AIGC) through the lens of “recognizable human input” as a potential threshold for copyrightability. As generative AI technologies advance, courts and policymakers face increasing challenges in determining when AIGC deserves copyright protection. We propose that the degree of recognizable human input—encompassing creative choices, prompting techniques, and pre-and post-generation editing—provides a coherent framework for copyright analysis that aligns with traditional copyright principles. We also offer a spectrum of different levels of human input and their recognizability through a creative experiment on 939 participants.

BIAN Renjun is an Assistant Professor at Peking University Law School. She is an interdisciplinary legal researcher interested in intellectual property law and empirical legal studies. Her current research examines both AI for IP law and IP law for AI, i.e., the incorporation of artificial intelligence into traditional IP studies and the impact of artificial intelligence on the current IP law framework. Renjun received her J.S.D. and LL.M. from the University of California, Berkeley, and her LL.B. from Peking University.

Moderator: Benjamin Chen, Associate Professor & Director of the Law and Technology Centre, The University of Hong Kong Faculty of Law

To register, please go to https://hkuems1.hku.hk/hkuems/ec_regform.aspx?guest=Y&UEID=98068. A paper will be circulated in advance and attendees will be expected to have read the paper before the seminar.