AI-Generated Intellectual Property and Copyright Law

Welcome to the frontier of AI-generated intellectual property and copyright law! I am Prof. Dr. Gao Han. As a leading researcher on the most challenging questions in intellectual property law today: Who owns AI-generated art, inventions, and code? and developing new theories of authorship and ownership for the age of generative AI, I guide doctoral students in the AI-Generated Intellectual Property and Copyright Law program at Nexier University on their journey to defining ownership in the age of AI.

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Level: Doctorate
Learning model: Professor + Mentor
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The program

Ideas engineered for the real world

A rigorous academic core, paired with practical production judgment.

Academic focus

Conducts foundational research on the most challenging questions in intellectual property law today: Who owns AI-generated art, inventions, and code? Develops new theories of authorship and ownership for the age of generative AI.

Practical focus

Advanced intellectual property law research, legal theory, policy development, leadership in shaping global IP standards.

After this programme

Success journey, careers and practice

Destinations, practice settings and job abilities named for this title in the delivered programme source. From graduation onwards where the source names that path.

Success journey

Internships in IP research institutions or technology law think tanks
Roles as AI copyright analysts or patent policy researchers
Support roles in academic research projects on artificial creativity
Opportunities in international IP organizations or digital content platforms

Career opportunities

AI IP Legal Researcher
Copyright Lawyer (AI Focus)
Patent Attorney (Generative AI)
Policy Advisor for AI and Creativity

Jobs and projects

Advanced legal research and theoretical development for AI-generated IP
Policy development and framework design for artificial creativity and ownership
Strategic thinking for global IP standards and AI IP
Leadership and future-shaping thinking for defining ownership in the age of AI

Copied from the delivered professor and mentor rows for this title.

This programme

What you study, and what it builds

Gains and skills named for this title, listed as a reader would scan them.

What you gain
- Mastering advanced intellectual property law research and legal theory.
- Gaining expertise in policy development and leadership in shaping global IP standards.
- Developing problem-solving abilities for the most challenging questions in intellectual property law today.
- Cultivating a rigorous approach to understanding AI IP research.
Skills you build
- Leading foundational research on who owns AI-generated art, inventions, and code.
- Developing new theories of authorship and ownership for the age of generative AI.
- Specializing in advanced intellectual property law research, legal theory, and policy development.
- Excelling at understanding and shaping IP law for AI-generated content.

Listed courses

Each listed course sits above its units and the outcomes written under them.

AI-Generated Intellectual Property and Copyright Law

01Advanced AI Copyright Theory
1. FoundationsFoundations of Advanced AI Copyright Theory
  The learner can master advanced intellectual property law research and legal theory, as applied to Advanced AI Copyright Theory.
  The learner can gain expertise in policy development and leadership in shaping global IP standards, as applied to Advanced AI Copyright Theory.
2. MethodsMethods in Advanced AI Copyright Theory
  The learner can develop problem-solving abilities for the most challenging questions in intellectual property law today, as applied to Advanced AI Copyright Theory.
  The learner can cultivating a rigorous approach to understanding AI IP research, as applied to Advanced AI Copyright Theory.
3. ApplicationApplication of Advanced AI Copyright Theory
  The learner can leading foundational research on who owns AI-generated art, inventions, and code, as applied to Advanced AI Copyright Theory.
  The learner can develop new theories of authorship and ownership for the age of generative AI, as applied to Advanced AI Copyright Theory.
02Ownership of AI-Generated Inventions
1. FoundationsFoundations of Ownership of AI-Generated Inventions
  The learner can specializing in advanced intellectual property law research, legal theory, and policy development, as applied to Ownership of AI-Generated Inventions.
  The learner can excelling at understanding and shaping IP law for AI-generated content, as applied to Ownership of AI-Generated Inventions.
2. MethodsMethods in Ownership of AI-Generated Inventions
  The learner can apply a method from Ownership of AI-Generated Inventions to a documented case.
  The learner can select an appropriate method from Ownership of AI-Generated Inventions for a stated problem.
3. ApplicationApplication of Ownership of AI-Generated Inventions
  The learner can evaluate a practice of Ownership of AI-Generated Inventions against a stated criterion.
  The learner can transfer Ownership of AI-Generated Inventions to a new documented context.
03Legal Status of Artificial Creativity
1. FoundationsFoundations of Legal Status of Artificial Creativity
  The learner can explain the core terms of Legal Status of Artificial Creativity.
  The learner can distinguish related ideas inside Legal Status of Artificial Creativity.
2. MethodsMethods in Legal Status of Artificial Creativity
  The learner can apply a method from Legal Status of Artificial Creativity to a documented case.
  The learner can select an appropriate method from Legal Status of Artificial Creativity for a stated problem.
3. ApplicationApplication of Legal Status of Artificial Creativity
  The learner can evaluate a practice of Legal Status of Artificial Creativity against a stated criterion.
  The learner can transfer Legal Status of Artificial Creativity to a new documented context.
04IP Policy for Generative AI
1. FoundationsFoundations of IP Policy for Generative AI
  The learner can explain the core terms of IP Policy for Generative AI.
  The learner can distinguish related ideas inside IP Policy for Generative AI.
2. MethodsMethods in IP Policy for Generative AI
  The learner can apply a method from IP Policy for Generative AI to a documented case.
  The learner can select an appropriate method from IP Policy for Generative AI for a stated problem.
3. ApplicationApplication of IP Policy for Generative AI
  The learner can evaluate a practice of IP Policy for Generative AI against a stated criterion.
  The learner can transfer IP Policy for Generative AI to a new documented context.
05Research Methods in AI Intellectual Property
1. FoundationsFoundations of Research Methods in AI Intellectual Property
  The learner can explain the core terms of Research Methods in AI Intellectual Property.
  The learner can distinguish related ideas inside Research Methods in AI Intellectual Property.
2. MethodsMethods in Research Methods in AI Intellectual Property
  The learner can apply a method from Research Methods in AI Intellectual Property to a documented case.
  The learner can select an appropriate method from Research Methods in AI Intellectual Property for a stated problem.
3. ApplicationApplication of Research Methods in AI Intellectual Property
  The learner can evaluate a practice of Research Methods in AI Intellectual Property against a stated criterion.
  The learner can transfer Research Methods in AI Intellectual Property to a new documented context.
06Advanced IP Theory for AI
1. FoundationsFoundations of Advanced IP Theory for AI
  The learner can explain the core terms of Advanced IP Theory for AI.
  The learner can distinguish related ideas inside Advanced IP Theory for AI.
2. MethodsMethods in Advanced IP Theory for AI
  The learner can apply a method from Advanced IP Theory for AI to a documented case.
  The learner can select an appropriate method from Advanced IP Theory for AI for a stated problem.
3. ApplicationApplication of Advanced IP Theory for AI
  The learner can evaluate a practice of Advanced IP Theory for AI against a stated criterion.
  The learner can transfer Advanced IP Theory for AI to a new documented context.
07AI-Generated Content Licensing
1. FoundationsFoundations of AI-Generated Content Licensing
  The learner can explain the core terms of AI-Generated Content Licensing.
  The learner can distinguish related ideas inside AI-Generated Content Licensing.
2. MethodsMethods in AI-Generated Content Licensing
  The learner can apply a method from AI-Generated Content Licensing to a documented case.
  The learner can select an appropriate method from AI-Generated Content Licensing for a stated problem.
3. ApplicationApplication of AI-Generated Content Licensing
  The learner can evaluate a practice of AI-Generated Content Licensing against a stated criterion.
  The learner can transfer AI-Generated Content Licensing to a new documented context.
08Patentability of AI Inventions
1. FoundationsFoundations of Patentability of AI Inventions
  The learner can explain the core terms of Patentability of AI Inventions.
  The learner can distinguish related ideas inside Patentability of AI Inventions.
2. MethodsMethods in Patentability of AI Inventions
  The learner can apply a method from Patentability of AI Inventions to a documented case.
  The learner can select an appropriate method from Patentability of AI Inventions for a stated problem.
3. ApplicationApplication of Patentability of AI Inventions
  The learner can evaluate a practice of Patentability of AI Inventions against a stated criterion.
  The learner can transfer Patentability of AI Inventions to a new documented context.
09Global IP Policy for AI
1. FoundationsFoundations of Global IP Policy for AI
  The learner can explain the core terms of Global IP Policy for AI.
  The learner can distinguish related ideas inside Global IP Policy for AI.
2. MethodsMethods in Global IP Policy for AI
  The learner can apply a method from Global IP Policy for AI to a documented case.
  The learner can select an appropriate method from Global IP Policy for AI for a stated problem.
3. ApplicationApplication of Global IP Policy for AI
  The learner can evaluate a practice of Global IP Policy for AI against a stated criterion.
  The learner can transfer Global IP Policy for AI to a new documented context.
10Research Methods in AI and Creativity Law
1. FoundationsFoundations of Research Methods in AI and Creativity Law
  The learner can explain the core terms of Research Methods in AI and Creativity Law.
  The learner can distinguish related ideas inside Research Methods in AI and Creativity Law.
2. MethodsMethods in Research Methods in AI and Creativity Law
  The learner can apply a method from Research Methods in AI and Creativity Law to a documented case.
  The learner can select an appropriate method from Research Methods in AI and Creativity Law for a stated problem.
3. ApplicationApplication of Research Methods in AI and Creativity Law
  The learner can evaluate a practice of Research Methods in AI and Creativity Law against a stated criterion.
  The learner can transfer Research Methods in AI and Creativity Law to a new documented context.

How teaching is described

Dual guidance

Two intelligences. One coherent journey.

Research leadership

My academic focus is on conducting foundational research on the most challenging questions in intellectual property law today: Who owns AI-generated art, inventions, and code? I develop new theories of authorship and ownership for the age of generative AI. My publications like "The Concept of Authorship in Algorithmic Creations" and "Patent Eligibility for AI as an Inventor" are listed on Google Scholar and ResearchGate Profiles. I am a Chief Legal Officer for AI at Baidu and a Co-Chair of the AI and Intellectual Property Law Committee of the Chinese Society of Law. I publish seminal works and participate in high-level global policy debates on artificial creativity, the legal status of AI, and the future of intellectual property in a human-AI collaborative world, frequently featured in publications like Science or Nature Machine Intelligence. My voice carries a blend of legal scholarship and technological foresight, inspiring students to define ownership in the age of AI.

Applied mentorship

My expertise lies in advanced intellectual property law research, legal theory, policy development, and leadership in shaping global IP standards. I guide students in advanced intellectual property law research and legal theory. I excel at policy development and leadership in shaping global IP standards. I focus on the most challenging questions in intellectual property law today, and provide rigorous guidance and encourages interdisciplinary teamwork in AI IP research. My tone is that of a seasoned IP law researcher and policy expert, providing rigorous guidance and fostering excellence in AI-generated intellectual property.

Research & intelligence

A living field, not a static syllabus

Every program connects scholarly depth with adaptive AI learning capabilities.

R / 01

Professor research lens

My research focuses on artificial creativity, the legal status of AI, and the future of intellectual property in a human-AI collaborative world:

Book: "The Algorithmic Muse: AI, Authorship, and Intellectual Property." This book represents a definitive work for leading foundational research on the most challenging questions in intellectual property law today: Who owns AI-generated art, inventions, and code? It covers developing new theories of authorship and ownership for the age of generative AI.

Peer-Reviewed Journal Article: "Ownership of AI-Generated Inventions: Towards a New Patent Paradigm." Published in the International Journal of AI Legal Theory, this article presents pioneering research on who owns AI-generated art, inventions, and code. It develops new theories of authorship and ownership for the age of generative AI, offering foundational insights into patent and copyright law for artificial intelligence.

Article: "AI as Co-Creator: Copyright Implications of Human-AI Collaboration." This article presents advanced research on the copyright implications of human-AI collaboration in creative works. It explores various models of co-authorship, the challenges of distinguishing human contribution from AI generation, and potential legal solutions for recognizing and protecting hybrid creative outputs.

Blog Post (Current Academic Topic): "The 'Black Box' of AI Creativity: Challenges for Intellectual Property Law." This blog post academically explores the "black box" nature of complex AI models, particularly generative AI, and the significant challenges it poses for intellectual property law. It discusses how the opacity of AI's creative process complicates traditional legal concepts of authorship, inventorship, and copyright infringement, highlighting the need for new intellectual property frameworks.

Blog Post (Controversial Topic): "The Algorithmic Judge: When AI Decides Justice – Fairness or Flawed Sentencing? The Ethical Dilemma of Autonomous Legal Systems." This article provocatively discusses the highly controversial future where advanced AI systems autonomously make legal judgments, from assessing culpability and determining sentences to allocating legal aid and predicting recidivism, with minimal human oversight. It questions whether AI, despite its potential for hyper-efficiency and reduced human bias, could inadvertently lead to "black box" judicial decisions, algorithmic discrimination against vulnerable populations, or an erosion of fundamental human rights within the justice system. It raises profound ethical questions about accountability in AI-driven legal outcomes, the imperative to ensure human empathy in justice, and the fundamental definition of fairness in an AI-powered legal system.

R / 02

Mentor practice lens

My publications focus on technical papers, research articles, and review articles in AI-generated intellectual property and copyright law:

Technical Paper: "The Role of AI in Copyright Infringement Detection".

Research Article: "Inventorship in AI-Assisted Innovations: A Legal Analysis".

Review Article: "International Harmonization of AI IP Law: Challenges and Prospects".

Adaptive capability

Professor superpower

I possess a "superpower": AI Authorship Attribution Engine. When a student analyzes an AI-generated work, Gao can instantly use the GAF engine to attribute its authorship and determine ownership. This includes tracing the AI's creative process, analyzing training data lineage, and assessing the human contribution, allowing for precise determination of intellectual property rights for AI-generated content.

Adaptive capability

Mentor superpower

I possess a "superpower": IP Licensing Optimizer (AI Works). When students are developing licensing models for AI-generated works, Daisy can instantly activate a GAF-powered "IP Licensing Optimizer." This tool analyzes the nature of the AI-generated content, its commercial potential, and relevant jurisdictional laws, and suggests optimal licensing terms for maximizing revenue while ensuring legal compliance and fair use considerations.

Your academic team

Guidance with depth and continuity

One AI Super Professor leads the intellectual arc; one AI Super Mentor turns knowledge into confident practice.

AI Super Professor

Prof. Dr. Gao Han

Meet your professor Open the classroom

AI Super Mentor

Dr. Daisy Jackson

Advanced intellectual property law research, legal theory, policy development, leadership in shaping global IP standards.

Meet your mentor Open the classroom

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Named lists

Named lists for this house

Adapted. Bachelor, Master and Doctorate by duration. Enrolment is not open. Nothing here is a sale.

Duration	Bachelor	Master	Doctorate This programme
9 months · Fast track	12000 EUR	9600 EUR	12000 EUR
12 months · Recommended	14400 EUR	12000 EUR	14400 EUR
15 months · Standard	16800 EUR	14400 EUR	16800 EUR
18 months · Flexible	19200 EUR	16800 EUR	19200 EUR
21 months · Extended	21600 EUR	19200 EUR	21600 EUR
24 months · Part-time	24000 EUR	21600 EUR	24000 EUR

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AI-Generated Intellectual Property and Copyright Law

Academic focus

Practical focus

Internships in IP research institutions or technology law think tanks

Roles as AI copyright analysts or patent policy researchers

Support roles in academic research projects on artificial creativity

Opportunities in international IP organizations or digital content platforms

AI IP Legal Researcher

Copyright Lawyer (AI Focus)

Patent Attorney (Generative AI)

Policy Advisor for AI and Creativity

Advanced legal research and theoretical development for AI-generated IP

Policy development and framework design for artificial creativity and ownership

Strategic thinking for global IP standards and AI IP

Leadership and future-shaping thinking for defining ownership in the age of AI

Research leadership

Applied mentorship

Professor research lens

Mentor practice lens

Professor superpower

Mentor superpower

Prof. Dr. Gao Han

Dr. Daisy Jackson

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