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Open research questions in Law, AI, and Intellectual Property

127 gap statements mined from Law, AI, and Intellectual Property papers in our 4.5M-paper local library, which holds 518 papers on the topic — drawn mostly from each paper's own stated research gap, future-work, challenge and limitation notes, and its abstract. The ones listed below are a selection still marked open; each names the study that raised it, with a DOI link where the paper has one.

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What the literature leaves open

  • The paper does not explicitly state its limitations. However, it can be inferred that the research is limited to a qualitative analysis of legal and economic aspects.

    Management of Intellectual Property in the Era of Artificial Intelligence · 2026 · DOI

  • The paper identifies the need for new legal and economic mechanisms to manage intellectual property in the context of AI development. It highlights the gap in the current regulatory framework for intellectual property management. The research gap is the lack of understanding of the systemic transformation of intellectual property management.

    Management of Intellectual Property in the Era of Artificial Intelligence · 2026 · DOI

  • The study highlights the challenge of developing copyright frameworks that account for the needs of large language models trained on scientific literature.

    Limitations of current copyright frameworks for large language models trained on scientific literature · 2026 · DOI

  • Future research should focus on developing copyright frameworks that account for the needs of large language models trained on scientific literature. The study suggests that further analysis of the U.S. fair use doctrine and its application to scientific literature is necessary.

    Limitations of current copyright frameworks for large language models trained on scientific literature · 2026 · DOI

  • The existing copyright legal system is centered on human creation, and determining the legal nature of AI-generated content has become an unavoidable issue. There is a lack of clear guidelines for determining copyright ownership and infringement liability for AI-generated content.

    On the Legal Nature of Copyright for Content Generated by Artificial Intelligence · 2026 · DOI

  • The paper suggests that future research should focus on developing collaborative frameworks between humans and machines. It highlights the need for more equitable frameworks for recognizing and compensating creative labor in the age of AI.

    Artificial Intelligence and The Future of Creative Authorship · 2026 · DOI

  • It highlights the need for new legal, pedagogical, and aesthetic paradigms to navigate the transformative potential of AI in the arts.

    Artificial Intelligence and The Future of Creative Authorship · 2026 · DOI

  • The existing copyright policy has not been able to match the existing technological developments. There is a lack of clarity on who owns AI-generated works.

    Artificial Intelligence as a Creative Entity: Legal Standards, Copyright Limitations, and Emerging Frameworks for Authorship · 2026 · DOI

  • The lack of a clear compensation system for fair use of copyright in AI creation. The need for a balanced solution between the development of new technologies and the contradiction of legal lag.

    The Construction of Fair Use of Copyright and Compensation System for Artificial Intelligence Creation · 2026 · DOI

  • Jurisdictional differences remain in IP laws across jurisdictions. The regulation of AI training obligations is a challenge.

    Global laws governing intellectual property rights for AI-generated works · 2026 · DOI

  • The criteria for determining copyright and portrait right infringements in AI face-swapping activities are unclear. The principles for allocating liability among multiple subjects in AI face swapping are unclear.

    Legal Risk Determination of “AI Face Swapping” · 2026 · DOI

  • The lack of standardization in biological data and metadata poses a challenge to progress in AI-enabled biotechnology. The rapid growth of the tool ecosystem has outpaced the ability to measure each tool's performance and reliability.

    Aligning innovation and security in AI-enabled biotechnology: a framework for designing and funding mutually reinforcing approaches · 2026 · DOI

  • There is a need for a framework that balances innovation and security in AI-enabled biotechnology. The current lack of standardization in biological data and metadata poses a challenge to progress in AI-enabled biotechnology.

    Aligning innovation and security in AI-enabled biotechnology: a framework for designing and funding mutually reinforcing approaches · 2026 · DOI

  • There is a lack of clear guidelines on copyright ownership of AI-generated content.

    Research on the Identification and Copyright Ownership of Generative Artificial Intelligence Works · 2026 · DOI

  • The gap between concept and reduction to practice is compressing dramatically due to generative AI. The traditional weaknesses of many software patents, such as excessive abstraction, may be reduced.

    The AI Patent Balance: Why Generative AI Both Weakens and Strengthens Modern Software Patents and Why Supreme Court's Refusal to Hear USAA v. PNC Matters to Inventors & Startups · 2026 · DOI

  • The lack of a clear approach to liability for copyright infringement in the AI era. The need for a balance between technological innovation and copyright protection.

    The Boundaries of Infringement Liability for Generative AI Users: Theoretical Reconstruction and Pathway Optimisation · 2026 · DOI

  • The lack of clear criteria for human-AI collaborative works. The need to distinguish which part of the work belongs to the human and which part belongs to the AI. The need to improve national legislation and develop clear criteria for human-AI collaborative works.

    CURRENT ISSUES OF INTELLECTUAL PROPERTY RIGHTS PROTECTION (COPYRIGHT AND ARTIFICIAL INTELLIGENCE TECHNOLOGIES) · 2026 · DOI

  • The current laws do not have a mechanism to clearly distinguish which part of the work belongs to the human and which part belongs to the AI. There is a huge legal gap in current laws regarding human-AI collaborative works.

    CURRENT ISSUES OF INTELLECTUAL PROPERTY RIGHTS PROTECTION (COPYRIGHT AND ARTIFICIAL INTELLIGENCE TECHNOLOGIES) · 2026 · DOI

  • The lack of consensus on whether the platform has a duty of care and the degree of the duty of care. The difficulty in identifying the reasonable duty of care of generative artificial intelligence service providers due to the distinctiveness of their service structure and the limitations of strict duty of care.

    The Determination of the Reasonable Duty of Care for Providers of Generative Artificial Intelligence Services in China · 2026 · DOI

  • The challenge of computational legitimacy is often obscured by the success of adjacent technologies. Existing categories are insufficient to address this challenge. The paper identifies a need for a new infrastructure category focused on preserving the relationship between computational decisions and the information, policies, and conditions under which those decisions were made.

    Constitutional Replay-Authority: A Category-Defining Paper for Computational Legitimacy and Replay Verification · 2026 · DOI

  • The paper notes that jurisdictional differences remain in the definition of human authorship and the assessment of inventive contribution. The regulation of AI training obligations varies across jurisdictions.

    Global laws governing intellectual property rights for AI-generated works · 2026 · DOI

  • The AI era has created a new public trust problem. Disclosure that AI was used is not enough.

    How to Trace. The Minimum Trace Protocol for Public-Reliance Claims in the AI Era · 2026 · DOI

  • Further study on the application of the proposed fair use and compensation system. Research on the improvement of the regulation of the fair use of AI creations. Investigation on the impact of AI technology on the development of Copyright Law.

    The Construction of Fair Use of Copyright and Compensation System for Artificial Intelligence Creation · 2026 · DOI

  • Further study on the application of the phased-separated and subject-based liability-sharing mechanism. Research on the effectiveness of the proposed mechanism in different scenarios.

    The Boundaries of Infringement Liability for Generative AI Users: Theoretical Reconstruction and Pathway Optimisation · 2026 · DOI

  • The lack of clear guidelines for considering AI-generated products as objects of copyright, - The need to revise the legislative framework…

    ACTUAL ISSUES OF INTELLECTUAL PROPERTY RIGHT PROTECTION (Copyright AND ARTIFICIAL INTELLIGENCE TECHNOLOGIES · 2026 · DOI

Most-cited papers in Law, AI, and Intellectual Property

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Open questions raised by papers listed on this page include: (1) The research gap is the lack of understanding of the systemic transformation of intellectual property management (“Management of Intellectual Property in the Era of Artificial Intelligence”, 2026); (2) Future research should focus on developing copyright frameworks that account for the needs of large language models trained on scientific literature (“Limitations of current copyright frameworks for large language models trained…”, 2026); (3) There is a lack of clear guidelines for determining copyright ownership and infringement liability for AI-generated content (“On the Legal Nature of Copyright for Content Generated by Artificial…”, 2026); (4) The paper suggests that future research should focus on developing collaborative frameworks between humans and machines (“Artificial Intelligence and The Future of Creative Authorship”, 2026); (5) The lack of a clear compensation system for fair use of copyright in AI creation (“The Construction of Fair Use of Copyright and Compensation System for…”, 2026). 127 gap statements have been mined from Law, AI, and Intellectual Property papers in our 4.5M-paper local library, which holds 518 papers on the topic; the gaps come from whichever of those papers state one. They are mostly the research gaps the authors state and the papers' abstracts, plus future-work, limitations and challenges passages. The ones listed below are a selection still marked open; each names the study that raised it, with a DOI link where the paper has one, so you can read the original claim in context.

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