Intellectual Property Protection for Collaborative Human–AI Innovation

Isabelle Laurent

Intellectual Property Protection for Collaborative Human–AI Innovation

Author(s)	Dr. Isabelle Laurent
Country	Togo
Abstract	Artificial intelligence increasingly participates in creative and inventive processes that were previously attributed almost entirely to human intellectual activity. Designers use generative systems to explore product configurations, researchers employ machine learning to identify promising scientific hypotheses, software developers work with code-generating systems, authors and artists iteratively modify machine-generated material, and engineering teams use AI to search large solution spaces. These practices complicate conventional intellectual property concepts because the economically valuable result may emerge from repeated interaction among human judgment, existing intellectual property, proprietary data, algorithmic tools, and machine-generated intermediate outputs. This study examines how copyright, patent, licensing, provenance, contractual, and trade-secret mechanisms can protect innovation arising from collaborative human–AI workflows without treating artificial intelligence itself as a conventional legal author or inventor. Current United States policy strongly preserves the human contribution threshold. The U.S. Copyright Office's 2025 copyrightability report states that copyright can protect human-authored expression, sufficiently creative human modifications, and selection or arrangement incorporating AI-generated material, while prompts alone do not ordinarily provide sufficient expressive control under currently available technology. The D.C. Circuit similarly held in Thaler v. Perlmutter in March 2025 that a work must initially be authored by a human being to qualify under the U.S. Copyright Act. Patent law follows a comparable direction: the USPTO's revised November 2025 guidance states that the ordinary inventorship standard applies to AI-assisted inventions and that only natural persons may be identified as inventors. The European Union addresses a related but distinct issue through its AI and copyright framework; Article 53 of the AI Act requires general-purpose AI providers to adopt policies for compliance with Union copyright law and to publish prescribed summaries concerning training content, while the relevant GPAI rules have applied since August 2, 2025. Using comparative doctrinal analysis and a synthetic dataset of 480 hypothetical collaborative innovation projects, the study compares four IP-governance conditions ranging from undocumented AI use to integrated governance combining contribution records, provenance, contractual allocation, confidentiality controls, and pre-filing IP review. Simulated IP protection readiness rises from 38.4 to 56.7, 78.9, and 90.6 across the four conditions. These values are illustrative rather than empirical. The article concludes that the most defensible model for human–AI innovation is not an attempt to give AI independent intellectual property status, but a provenance-centered system capable of demonstrating which protectable intellectual contributions came from humans, which materials originated elsewhere, how AI was used, who owns resulting rights, and which outputs require licensing or confidentiality safeguards.
Keywords	artificial intelligence, intellectual property, human–AI collaboration, copyright authorship, patent inventorship, generative AI, IP ownership, provenance, licensing, trade secrets
Field	Engineering
Published In	Volume 2, Issue 6, November-December 2021
Published On	2021-12-24

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American Journal of Advanced Multidisciplinary Innovation and Research

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Intellectual Property Protection for Collaborative Human–AI Innovation

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