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Open research questions in Law, AI, and Intellectual Property

93 unresolved questions extracted from the limitations and future-work sections of 421 Law, AI, and Intellectual Property papers in our library. Each links back to the study that raised it.

What the literature leaves open

  • The current copyright system faces difficulties in dealing with generative AI works. 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

  • Further research is needed to clarify the implications of AI on copyright law, - The development of a distinct European path for regulating AI systems

    Comment of the European Copyright Society on the Request for Preliminary Ruling in Case C-250/25 (Like Company) · 2026 · DOI

  • The gap in the EU's statutory framework regarding AI and copyright law, - The lack of clarity on the scope and conditions of permitted AI training

    Comment of the European Copyright Society on the Request for Preliminary Ruling in Case C-250/25 (Like Company) · 2026 · DOI

  • The increasing risk of claims being deemed abstract or obvious due to generative AI. The need for concrete technical grounding tied to real-world operational constraints in patent claims. The challenge of drafting stronger, more durable patents in the face of generative AI.

    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 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

  • 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 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 need for transparency and accountability in the AI era. The complexity of tracing public-reliance contributions.

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

  • The difficulty in defining artificial intelligence and its implications for copyright law. The need to balance the protection of authors' rights with the encouragement of innovation. The challenge of applying the principle of territoriality in the context of artificial intelligence, which operates on a global scale.

    Copyright and artificial intelligence · 2026 · DOI

  • The issue of freedom of children or their parents to decide on the usage of AI in education is complex. The use of AI in education may generate digital divide among students and further inequalities. AI systems may raise concerns about data protection and privacy.

    IMPLICATIONS OF ARTIFICIAL INTELLIGENCE FOR THE RIGHT TO EDUCATION UNDER THE UN CONVENTION ON THE RIGHTS OF THE CHILD · 2026 · DOI

  • The paper identifies the challenge of balancing the need to provide access to digital collections with the need to protect them from AI harvesting. It notes the challenge of developing sustainable, ethical, and effective strategies for dealing with AI. The paper highlights the challenge of ensuring that digital libraries can continue to provide secure digital content in the face of AI advancements.

    Artificial Intelligence, Authentic Reactions: Tensions Between Digital Libraries and Generative AI · 2026 · DOI

  • The massive increase in coordinated scientific fraud. The difficulty in weeding out fake articles. The need to prevent the destruction of academic publishing.

    Predatory journals, paper mills, and AI could destroy academic publishing · 2026 · DOI

  • The lack of clarity on the role of IP in AI strategies in Africa. The need to balance the protection of IP rights with the promotion of innovation and access to knowledge. The challenge of developing IP rules that take into account the specific AI-IP issue in focus.

    Centering Intellectual Property in Artificial Intelligence Strategies in Africa Through a Techno-legal Analysis · 2026 · DOI

  • The study identifies the challenge of balancing state sovereignty and humanitarian intervention. The research highlights the need to reconcile outdated frameworks with contemporary realities. The analysis reveals the challenge of creating a consistent framework for human security.

    Non-Intervention Principle and Humanitarian Intervention an Unresolved Legal Contradiction · 2026 · DOI

  • The current legal regime has significant gaps in addressing AI challenges - Traditional laws were not designed to address AI challenges

    ARTIFICIAL INTELLIGENCE IN INDIA: IS THE LAW READY FOR THE FUTURE? · 2026 · DOI

  • The integration of AI in sports has created a minefield of algorithmic bias. The current regulatory framework lacks specialized expertise to address algorithmic bias and data sovereignty. The paper identifies critical failures, such as the narrowing of RTI access under Section 14(2) of the NSGA, 2025.

    The Jurisprudence of the Digital field: Addressing Algorithmic Bias and the Legal Literacy Gap in the Evolution of Indian Sports Law · 2026 · DOI

  • Future research can explore the implementation of the proposed co-ownership model of data sovereignty in Indian sports law. The study's findings can inform further research on the intersection of sports law, data privacy, and athlete rights in other jurisdictions.

    The Jurisprudence of the Digital field: Addressing Algorithmic Bias and the Legal Literacy Gap in the Evolution of Indian Sports Law · 2026 · DOI

  • The paper identifies a fundamental conflict between the data volume needed for AI innovation and copyright author protection, proposing opt-out mechanisms as a solution, but does not analyze or model how widespread adoption of such opt-out systems would affect AI model performance, training efficiency, or the economic viability of Georgian AI startups.

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

  • The paper proposes developing specialized educational programs in IP management for managers and engineers (not just lawyers) to build organizational awareness in Georgia, but does not specify the curriculum content, pedagogical approach, target organizational sectors, or success metrics for measuring whether such programs actually improve IP management practices in private and academic sectors.

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

  • At present, most countries recognize copyright exceptions for non-commercial purposes. For example, the UK Government (2022) and the European Union (2019) have enacted regulations permitting the use of copyrighted materials for non-commercial scientific research for AI training. Meanwhile, a few countries make no explicit distinction between commercial and non-commercial AI training. For example, Japan Copyright research and information center (2020) and Singapore Statutes Online (2021) have adopted even more progressive policies, allowing the use of copyrighted data for both commercial and non-commercial AI training, positioning them as the most AI-friendly countries (Hays, 2024). 2.1.3 Legal classification of scientific works under copyright law Whether scientific literature is considered copyright-protected content is a controversial issue. For exvample, UK copyright law explicitly states that “copyright work” includes “original literary, dramatic, musical or artistic works,” and “sound recordings, films,” it does not include scientific works (Legislation.gov.uk, 1988). Japanese copyright law stipulates that copyrightable works are defined as “a creatively produced expression of thoughts or sentiments that falls within the literary, academic, artistic, or musical domain” (Japan Copyright research and information center, 2020). Scientific literature is not included. Unlike most other European countries, Germany and Spain classify scientific works as copyrightable (Esteve, 2024). Spanish commentators argue that “scientific discoveries, theories, methods, and ideas” within scientific works are not protected by copyright, while the “wording, images or figures created by the author to explain the content is copyright protected” (Esteve, 2024). 2.2 Reasons for applying the U.S. Fair use framework In 1967, Article 9 (2) of the Berne Convention first explicitly introduced the “three-step test,” establishing a framework for copyright applicable to the 181 signatory countries. The three criteria are as follows: “permit the reproduction of such works in certain special cases,” “such reproduction does not conflict with a normal exploitation of the work,” and “does not unreasonably prejudice the legitimate interests of the author” (Legal Information Institute, 1971). The “special cases” identified in the first criterion allow member countries the flexibility to define the scope of exceptions according to their national legal traditions. This test allows national legislatures to define specific exceptions, but it remains a relatively static legislative model in which unlisted uses are typically not exempted. The fair use doctrine in U.S. copyright law is widely regarded as compatible with the three-step test outlined in the Berne Convention. Countries such as the Philippines, Israel, and South Korea have also incorporated fair use provisions into their national copyright laws (Geiger et al., 2014).

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

  • The unclear relationship between fair use and infringement of copyright in AI creation. 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

  • The paper identifies challenges in assessing the legal status of AI-generated outputs. 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 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

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93 open questions have been extracted from the limitations and future-work passages of 421 Law, AI, and Intellectual Property papers in our library. Each one below links back to the study that raised it, so you can read the original claim in context.

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