When Code Creates: Landscape Report on IP Issues in AI
This landscape report offers a comparative study of the global legal landscape regarding the intersection of artificial intelligence and intellectual property law. It examines key issues such as whether AI systems can be named as inventors or authors, patentability requirements, copyright protection for AI-generated works, design and trademark implications, and the challenges of IP infringement in the age of AI. Published as a collaboration between the Intellectual Property Office of Singapore and the SMU Centre for AI and Data Governance, the report serves as a resource for policymakers, lawmakers, technology developers, and civil society.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
This report is designed to serve as a resource for policymakers, lawmakers, technology developers and deployers, IP creators and rights owners, and civil society.
What the document contains
The report addresses the intersection of artificial intelligence and intellectual property law, specifically examining patents, copyright, registered designs, trademarks, passing off, the right of publicity, and IP infringement issues related to machine learning and generative AI outputs.
The report does not delve into broader political economy questions surrounding the role of IP rights in incentivisation, nor does it systematically explore law reform issues, deepfakes, or online harms outside the scope of intellectual property law.
- Existing patent and copyright laws globally are premised on human inventorship and authorship, meaning AI systems generally cannot be named as inventors or authors.
- The use of copyrighted works for text and data mining (TDM) and machine learning raises complex questions around copyright infringement and the applicability of statutory exceptions or fair use doctrines.
- Jurisdictions differ significantly in their approach to TDM exceptions, ranging from permissive frameworks in Japan to restrictive and opt-out regimes in the European Union.
- Evidentiary hurdles such as the black box nature of AI make it exceptionally difficult to prove copying or patent infringement in AI-generated outputs.
- Attributing liability for IP infringement involving AI requires navigating complex relationships between developers, system owners, and end-users.
· Foreword · Introduction · Chapter 1. AI and Patents · Chapter 2. AI and Copyright · Chapter 3. AI and Other Forms of IP · Chapter 4. AI and Infringement · Conclusion
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
2/5Clear responsibility for AI outcomes
Who would be liable for IP infringement?
Chapter 4
screening score · 2026-10-23
Fairness
0/5Non-discrimination and equitable treatment
n/a
screening score · 2026-10-23
Human Dignity
0/5Respect for the inherent worth of persons
n/a
screening score · 2026-10-23
Human Oversight
0/5Humans remain in control of consequential decisions
n/a
screening score · 2026-10-23
Privacy
0/5Protection of personal data and private life
n/a
screening score · 2026-10-23
Enforcement
0/5Consequences and compliance mechanisms with real force
n/a
screening score · 2026-10-23
Impact Assessment
0/5Required assessment of an AI system's risks/impacts before or during use
n/a
screening score · 2026-10-23