Prompting protection: copyright eligibility of human-AI collaborative works under Section 22(3) of Kenya’s copyright legislation
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Strathmore University
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This study explores whether works created through human-AI collaboration—particularly when humans guide AI through prompts—qualify for copyright protection under Section 22(3) of Kenya's Copyright Act. It examines the legal criteria of originality and sufficient effort in the context of AI-assisted creativity, analyzing both local and international perspectives. The research focuses on Kenya’s copyright framework and incorporates comparative legal analysis to assess how other jurisdictions address AI-generated works. Using doctrinal legal research, the study reviews statutory provisions, case law, and scholarly debates to determine how AI-assisted works fit within existing copyright laws. Findings reveal that human-AI collaboration represents a novel form of creative expression, challenging traditional copyright interpretations. The study demonstrates that users' contributions—through structured prompt engineering and refinement—often constitute substantial creative effort, potentially meeting copyright eligibility requirements and protection. To address these challenges, the study recommends establishing clearer legal frameworks to define copyright eligibility for AI-assisted works. It also suggests implementing licensing mechanisms for AI training data to prevent copyright disputes and providing specialized training for policymakers and legal professionals on AI and copyright matters. Furthermore, fostering AI research and development in Kenya is essential to encourage innovation and economic growth. These measures will help modernize Kenya’s copyright laws, ensuring they remain relevant in the evolving digital landscape while protecting both human creators and AI-assisted works.
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Gitau, N. M. W. (2025). Prompting protection: Copyright eligibility of human-AI collaborative works under Section 22(3) of Kenya’s copyright legislation [Strathmore University]. https://hdl.handle.net/11071/16609