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Intellectual Property Law Research Paper Topics

Welcome to the realm of intellectual property law research paper topics , where we aim to guide law students on their academic journey by providing a comprehensive list of 10 captivating and relevant topics in each of the 10 categories. In this section, we will explore the dynamic field of intellectual property law, encompassing copyrights, trademarks, patents, and more, and shed light on its significance, complexities, and the diverse array of research paper topics it offers. With expert tips on topic selection, guidance on crafting an impactful research paper, and access to iResearchNet’s custom writing services, students can empower their pursuit of excellence in the domain of intellectual property law.

100 Intellectual Property Law Research Paper Topics

Intellectual property law is a dynamic and multifaceted field that intersects with various sectors, including technology, arts, business, and innovation. Research papers in this domain allow students to explore the intricate legal framework that governs the creation, protection, and enforcement of intellectual property rights. To aid aspiring legal scholars in their academic pursuits, this section presents a comprehensive list of intellectual property law research paper topics, categorized to encompass a wide range of subjects.

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• Fair Use Doctrine: Balancing Creativity and Access to Knowledge
• Copyright Infringement in the Digital Age: Challenges and Solutions
• The Role of Copyright Law in Protecting Creative Works of Art
• The Intersection of Copyright and AI: Legal Implications and Challenges
• Copyright and Digital Education: Analyzing the Impact of Distance Learning
• Copyright and Social Media: Addressing Infringement and User Rights
• Copyright Exceptions for Libraries and Educational Institutions
• Copyright Law and Virtual Reality: Emerging Legal Issues
• Copyright and Artificial Intelligence in Music Creation
• Copyright Termination Rights and Authors’ Works Reversion
• Patentable Subject Matter: Examining the Boundaries of Patent Protection
• Patent Trolls and Innovation: Evaluating the Impact on Technological Advancement
• Biotechnology Patents: Ethical Considerations and Policy Implications
• Patent Wars in the Pharmaceutical Industry: Balancing Access to Medicine and Innovation
• Standard Essential Patents: Analyzing the Role in Technology Development and Market Competition
• Patent Thickets and the Challenges for Startups and Small Businesses
• Patent Pooling and Collaborative Innovation: Advantages and Legal Considerations
• Patent Litigation and Forum Shopping: Analysis of Jurisdictional Issues
• Patent Law and Artificial Intelligence: Implications for Inventorship and Ownership
• Patent Exhaustion and International Trade: Legal Complexities in Global Markets
• Trademark Dilution: Protecting the Distinctiveness of Brands in a Global Market
• Trademark Infringement and the Online Environment: Challenges and Legal Remedies
• The Intersection of Trademark Law and Freedom of Speech: Striking a Balance
• Non-Traditional Trademarks: Legal Issues Surrounding Sound, Color, and Shape Marks
• Trademark Licensing: Key Considerations for Brand Owners and Licensees
• Trademark Protection for Geographical Indications: Preserving Cultural Heritage
• Trademark Opposition and Cancellation Proceedings: Strategies and Legal Considerations
• Trademark Law and Counterfeiting: Global Enforcement Challenges
• Trademark and Domain Name Disputes: UDRP and Legal Strategies
• Trademark Law and Social Media Influencers: Disclosure and Endorsement Guidelines
• Trade Secrets vs. Patents: Choosing the Right Intellectual Property Protection
• Trade Secret Misappropriation: Legal Protections and Remedies for Businesses
• Protecting Trade Secrets in the Digital Age: Cybersecurity Challenges and Best Practices
• International Trade Secret Protection: Harmonization and Enforcement Challenges
• Whistleblowing and Trade Secrets: Balancing Public Interest and Corporate Secrets
• Trade Secret Licensing and Technology Transfer: Legal and Business Considerations
• Trade Secret Protection in Employment Contracts: Non-Compete and Non-Disclosure Agreements
• Trade Secret Misappropriation in Supply Chains: Legal Implications and Risk Mitigation
• Trade Secret Law and Artificial Intelligence: Ownership and Trade Secret Protection
• Trade Secret Protection in the Era of Open Innovation and Collaborative Research
• Artificial Intelligence and Intellectual Property: Ownership and Liability Issues
• 3D Printing and Intellectual Property: Navigating the Intersection of Innovation and Copyright
• Blockchain Technology and Intellectual Property: Challenges and Opportunities
• Digital Rights Management: Addressing Copyright Protection in the Digital Era
• Open Source Software Licensing: Legal Implications and Considerations
• Augmented Reality and Virtual Reality: Legal Issues in Content Creation and Distribution
• Internet of Things (IoT) and Intellectual Property: Legal Challenges and Policy Considerations
• Big Data and Intellectual Property: Privacy and Data Protection Concerns
• Artificial Intelligence and Patent Offices: Automation and Efficiency Implications
• Intellectual Property Implications of 5G Technology: Connectivity and Innovation Challenges
• Music Copyright and Streaming Services: Analyzing Legal Challenges and Solutions
• Fair Use in Documentary Films: Balancing Copyright Protection and Freedom of Expression
• Intellectual Property in Video Games: Legal Issues in the Gaming Industry
• Digital Piracy and Copyright Enforcement: Approaches to Tackling Online Infringement
• Personality Rights in Media: Balancing Privacy and Freedom of the Press
• Streaming Services and Copyright Licensing: Legal Challenges and Royalty Distribution
• Fair Use in Parody and Satire: Analyzing the Boundaries of Creative Expression
• Copyright Protection for User-Generated Content: Balancing Authorship and Ownership
• Media Censorship and Intellectual Property: Implications for Freedom of Information
• Virtual Influencers and Copyright: Legal Challenges in the Age of AI-Generated Content
• Intellectual Property Protection in Developing Countries: Promoting Innovation and Access to Knowledge
• Cross-Border Intellectual Property Litigation: Jurisdictional Challenges and Solutions
• Trade Agreements and Intellectual Property: Impact on Global Innovation and Access to Medicines
• Harmonization of Intellectual Property Laws: Prospects and Challenges for International Cooperation
• Indigenous Knowledge and Intellectual Property: Addressing Cultural Appropriation and Protection
• Intellectual Property and Global Public Health: Balancing Innovation and Access to Medicines
• Geographical Indications in International Trade: Legal Framework and Market Exclusivity
• International Licensing and Technology Transfer: Legal Considerations for Multinational Corporations
• Intellectual Property Enforcement in the Digital Marketplace: Comparative Analysis of International Laws
• Digital Copyright and Cross-Border E-Commerce: Legal Implications for Online Businesses
• Intellectual Property Strategy for Startups: Maximizing Value and Mitigating Risk
• Licensing and Franchising: Legal Considerations for Expanding Intellectual Property Rights
• Intellectual Property Due Diligence in Mergers and Acquisitions: Key Legal Considerations
• Non-Disclosure Agreements: Safeguarding Trade Secrets and Confidential Information
• Intellectual Property Dispute Resolution: Arbitration and Mediation as Alternative Methods
• Intellectual Property Valuation: Methods and Challenges for Business and Investment Decisions
• Technology Licensing and Transfer Pricing: Tax Implications for Multinational Corporations
• Intellectual Property Audits: Evaluating and Managing IP Assets for Businesses
• Trade Secret Protection and Non-Compete Clauses: Balancing Employer and Employee Interests
• Intellectual Property and Startups: Strategies for Funding and Investor Relations
• Intellectual Property and Access to Medicines: Ethical Dilemmas in Global Health
• Gene Patenting and Human Dignity: Analyzing the Moral and Legal Implications
• Intellectual Property and Indigenous Peoples: Recognizing Traditional Knowledge and Culture
• Bioethics and Biotechnology Patents: Navigating the Intersection of Science and Ethics
• Copyright, Creativity, and Freedom of Expression: Ethical Considerations in the Digital Age
• Intellectual Property and Artificial Intelligence: Ethical Implications for AI Development and Use
• Genetic Engineering and Intellectual Property: Legal and Ethical Implications
• Intellectual Property and Environmental Sustainability: Legal and Ethical Perspectives
• Cultural Heritage and Intellectual Property Rights: Preservation and Repatriation Efforts
• Intellectual Property and Social Justice: Access and Equality in the Innovation Ecosystem
• Innovation Incentives and Intellectual Property: Examining the Relationship
• Intellectual Property and Technology Transfer: Promoting Innovation and Knowledge Transfer
• Intellectual Property Rights in Research Collaborations: Balancing Interests and Collaborative Innovation
• Innovation Policy and Patent Law: Impact on Technology and Economic Growth
• Intellectual Property and Open Innovation: Collaborative Models and Legal Implications
• Intellectual Property and Startups: Fostering Innovation and Entrepreneurship
• Intellectual Property and University Technology Transfer: Challenges and Opportunities
• Open Access and Intellectual Property: Balancing Public Goods and Commercial Interests
• Intellectual Property and Creative Industries: Promoting Cultural and Economic Development
• Intellectual Property and Sustainable Development Goals: Aligning Innovation with Global Priorities

The intellectual property law research paper topics presented here are intended to inspire students and researchers to delve into the complexities of intellectual property law and explore emerging issues in this ever-evolving field. Each topic offers a unique opportunity to engage with legal principles, societal implications, and practical challenges. As the landscape of intellectual property law continues to evolve, there remains an exciting realm of uncharted research areas, waiting to be explored. Through in-depth research and critical analysis, students can contribute to the advancement of intellectual property law and its impact on innovation, creativity, and society at large.

Exploring the Range of Topics in Human Rights Law

Human rights law is a vital field of study that delves into the protection and promotion of fundamental rights and freedoms for all individuals. As a cornerstone of international law, human rights law addresses various issues, ranging from civil and political rights to economic, social, and cultural rights. It aims to safeguard the inherent dignity and worth of every human being, regardless of their race, religion, gender, nationality, or other characteristics. In this section, we will explore the diverse and expansive landscape of intellectual property law research paper topics, shedding light on its significance and the vast array of areas where students can conduct meaningful research.

• Historical Perspectives on Human Rights : Understanding the historical evolution of human rights is essential to comprehend the principles and norms that underpin modern international human rights law. Research papers in this category may explore the origins of human rights, the impact of significant historical events on the development of human rights norms, and the role of key figures and organizations in shaping the human rights framework.
• Human Rights and Social Justice : This category delves into the intersection of human rights law and social justice. Intellectual property law research paper topics may encompass the role of human rights in addressing issues of poverty, inequality, discrimination, and marginalization. Researchers can analyze how human rights mechanisms and legal instruments contribute to advancing social justice and promoting inclusivity within societies.
• Gender Equality and Women’s Rights : Gender equality and women’s rights remain crucial subjects in human rights law. Research papers in this area may explore the legal protections for women’s rights, the challenges in achieving gender equality, and the impact of cultural and societal norms on women’s human rights. Intellectual property law research paper topics may also address specific issues such as violence against women, gender-based discrimination, and the role of women in peacebuilding and conflict resolution.
• Freedom of Expression and Media Rights : The right to freedom of expression is a fundamental human right that forms the basis of democratic societies. In this category, researchers can examine the legal dimensions of freedom of expression, including its limitations, the role of media in promoting human rights, and the challenges in balancing freedom of expression with other rights and interests.
• Human Rights in Armed Conflicts and Peacebuilding : Armed conflicts have severe implications for human rights, necessitating robust legal frameworks for protection. Topics in this category may focus on humanitarian law, the rights of civilians during armed conflicts, and the role of international organizations in peacebuilding and post-conflict reconstruction.
• Refugee and Migration Rights : With the global refugee crisis and migration challenges, this category addresses the legal protections and challenges faced by refugees and migrants. Research papers may delve into the rights of asylum seekers, the principle of non-refoulement, and the legal obligations of states in providing humanitarian assistance and protection to displaced populations.
• Economic, Social, and Cultural Rights : Economic, social, and cultural rights are integral to human rights law, ensuring the well-being and dignity of individuals. Topics may explore the right to education, health, housing, and adequate standards of living. Researchers may also examine the justiciability and enforcement of these rights at national and international levels.
• Human Rights and Technology : The digital age presents new challenges and opportunities for human rights. Research in this category can explore the impact of technology on privacy rights, freedom of expression, and the right to access information. Intellectual property law research paper topics may also cover the use of artificial intelligence and algorithms in decision-making processes and their potential implications for human rights.
• Environmental Justice and Human Rights : Environmental degradation has significant human rights implications. Researchers can investigate the intersection of environmental protection and human rights, examining the right to a healthy environment, the rights of indigenous communities, and the role of human rights law in addressing climate change.
• Business and Human Rights : The responsibilities of corporations in upholding human rights have gained increasing attention. This category focuses on corporate social responsibility, human rights due diligence, and legal mechanisms to hold businesses accountable for human rights violations.

The realm of human rights law offers an expansive and dynamic platform for research and exploration. As the international community continues to grapple with pressing human rights issues, students have a unique opportunity to contribute to the discourse and advance human rights protections worldwide. Whether examining historical perspectives, social justice, gender equality, freedom of expression, or other critical areas, research in human rights law is a compelling endeavor that can make a positive impact on the lives of people globally.

How to Choose an Intellectual Property Law Topic

Choosing the right intellectual property law research paper topic is a crucial step in the academic journey of law students. Intellectual property law is a multifaceted and rapidly evolving field that covers a wide range of subjects, including patents, copyrights, trademarks, trade secrets, and more. With such diversity, selecting a compelling and relevant research topic can be both challenging and exciting. In this section, we will explore ten practical tips to help students navigate the process of choosing an engaging and impactful intellectual property law research paper topic.

• Identify Your Interests and Passion : The first step in selecting a research paper topic in intellectual property law is to identify your personal interests and passion within the field. Consider what aspects of intellectual property law resonate with you the most. Are you fascinated by the intricacies of patent law and its role in promoting innovation? Or perhaps you have a keen interest in copyright law and its influence on creative expression? By choosing a topic that aligns with your passions, you are more likely to stay motivated and engaged throughout the research process.
• Stay Updated on Current Developments : Intellectual property law is a dynamic area with continuous developments and emerging trends. To choose a relevant and timely research topic, it is essential to stay updated on recent court decisions, legislative changes, and emerging issues in the field. Follow reputable legal news sources, academic journals, and intellectual property law blogs to remain informed about the latest developments.
• Narrow Down the Scope : Given the vastness of intellectual property law, it is essential to narrow down the scope of your research paper topic. Focus on a specific subfield or issue within intellectual property law that interests you the most. For example, you may choose to explore the legal challenges of protecting digital copyrights in the music industry or the ethical implications of gene patenting in biotechnology.
• Conduct Preliminary Research : Before finalizing your research paper topic, conduct preliminary research to gain a better understanding of the existing literature and debates surrounding the chosen subject. This will help you assess the availability of research material and identify any gaps or areas for further exploration.
• Review Case Law and Legal Precedents : In intellectual property law, case law plays a crucial role in shaping legal principles and interpretations. Analyzing landmark court decisions and legal precedents in your chosen area can provide valuable insights and serve as a foundation for your research paper.
• Consult with Professors and Experts : Seek guidance from your professors or intellectual property law experts regarding potential intellectual property law research paper topics. They can offer valuable insights, suggest relevant readings, and provide feedback on the feasibility and relevance of your chosen topic.
• Consider Practical Applications : Intellectual property law has real-world implications and applications. Consider choosing a research topic that has practical significance and addresses real challenges faced by individuals, businesses, or society at large. For example, you might explore the role of intellectual property in facilitating technology transfer in developing countries or the impact of intellectual property rights on access to medicines.
• Analyze International Perspectives : Intellectual property law is not confined to national boundaries; it has significant international dimensions. Analyzing the differences and similarities in intellectual property regimes across different countries can offer a comparative perspective and enrich your research paper.
• Propose Solutions to Existing Problems : A compelling research paper in intellectual property law can propose innovative solutions to existing problems or challenges in the field. Consider focusing on an area where there are unresolved debates or conflicting interests and offer well-reasoned solutions based on legal analysis and policy considerations.
• Seek Feedback and Refine Your Topic : Once you have narrowed down your research paper topic, seek feedback from peers, professors, or mentors. Be open to refining your topic based on constructive criticism and suggestions. A well-defined and thoughtfully chosen research topic will set the stage for a successful and impactful research paper.

Choosing the right intellectual property law research paper topic requires careful consideration, passion, and a keen awareness of current developments in the field. By identifying your interests, staying updated on legal developments, narrowing down the scope, conducting preliminary research, and seeking guidance from experts, you can select a compelling and relevant topic that contributes to the academic discourse in intellectual property law. A well-chosen research topic will not only showcase your expertise and analytical skills but also provide valuable insights into the complexities and challenges of intellectual property law in the modern world.

How to Write an Intellectual Property Law Research Paper

Writing an intellectual property law research paper can be an intellectually stimulating and rewarding experience. However, it can also be a daunting task, especially for students who are new to the intricacies of legal research and academic writing. In this section, we will provide a comprehensive guide on how to write an effective and impactful intellectual property law research paper. From understanding the structure and components of the paper to conducting thorough research and crafting compelling arguments, these ten tips will help you navigate the writing process with confidence and proficiency.

• Understand the Paper Requirements : Before diving into the writing process, carefully review the requirements and guidelines provided by your professor or institution. Pay attention to the paper’s length, formatting style (APA, MLA, Chicago/Turabian, Harvard, etc.), citation guidelines, and any specific instructions regarding the research paper topic or research methods.
• Conduct In-Depth Research : A strong intellectual property law research paper is built on a foundation of comprehensive and credible research. Utilize academic databases, legal journals, books, and reputable online sources to gather relevant literature and legal precedents related to your chosen topic. Ensure that your research covers a wide range of perspectives and presents a well-rounded analysis of the subject matter.
• Develop a Clear Thesis Statement : The thesis statement is the central argument of your research paper. It should be concise, specific, and clearly convey the main point you will be arguing throughout the paper. Your thesis statement should reflect the significance of your research topic and its contribution to the field of intellectual property law.
• Create an Outline : An outline is a roadmap for your research paper, helping you organize your thoughts and ideas in a logical and coherent manner. Divide your paper into sections, each representing a key aspect of your argument. Within each section, outline the main points you will address and the evidence or analysis that supports your claims.
• Introduction : Engage and Provide Context: The introduction of your research paper should captivate the reader’s attention and provide essential context for your study. Start with a compelling opening sentence or anecdote that highlights the importance of the topic. Clearly state your thesis statement and provide an overview of the main points you will explore in the paper.
• Literature Review : In the early sections of your research paper, include a literature review that summarizes the existing research and scholarship on your topic. Analyze the key theories, legal doctrines, and debates surrounding the subject matter. Use this section to demonstrate your understanding of the existing literature and to identify gaps or areas where your research will contribute.
• Legal Analysis and Argumentation : The heart of your intellectual property law research paper lies in your legal analysis and argumentation. Each section of the paper should present a well-structured and coherent argument supported by legal reasoning, case law, and relevant statutes. Clearly explain the legal principles and doctrines you are applying and provide evidence to support your conclusions.
• Consider Policy Implications : Intellectual property law often involves complex policy considerations. As you present your legal arguments, consider the broader policy implications of your research findings. Discuss how your proposed solutions or interpretations align with societal interests and contribute to the advancement of intellectual property law.
• Anticipate Counterarguments : To strengthen your research paper, anticipate potential counterarguments to your thesis and address them thoughtfully. Acknowledging and refuting counterarguments demonstrate the depth of your analysis and the validity of your position.
• Conclusion : Recapitulate and Reflect: In the conclusion of your research paper, recapitulate your main arguments and restate your thesis statement. Reflect on the insights gained from your research and highlight the significance of your findings. Avoid introducing new information in the conclusion and instead, offer recommendations for further research or policy implications.

Writing an intellectual property law research paper requires meticulous research, careful analysis, and persuasive argumentation. By following the tips provided in this section, you can confidently navigate the writing process and create an impactful research paper that contributes to the field of intellectual property law. Remember to adhere to academic integrity and proper citation practices throughout your research, and seek feedback from peers or professors to enhance the quality and rigor of your work. A well-crafted research paper will not only demonstrate your expertise in the field but also provide valuable insights into the complexities and nuances of intellectual property law.

iResearchNet’s Research Paper Writing Services

At iResearchNet, we understand the challenges that students face when tasked with writing complex and comprehensive research papers on intellectual property law topics. We recognize the importance of producing high-quality academic work that meets the rigorous standards of legal research and analysis. To support students in their academic endeavors, we offer custom intellectual property law research paper writing services tailored to meet individual needs and requirements. Our team of expert writers, well-versed in the intricacies of intellectual property law, is committed to delivering top-notch, original, and meticulously researched papers that can elevate your academic performance.

• Expert Degree-Holding Writers : Our team consists of experienced writers with advanced degrees in law and expertise in intellectual property law. They possess the necessary knowledge and research skills to create well-crafted research papers that showcase a profound understanding of the subject matter.
• Custom Written Works : We take pride in producing custom-written research papers that are unique to each client. When you place an order with iResearchNet, you can be assured that your paper will be tailored to your specific instructions and requirements.
• In-Depth Research : Our writers conduct thorough and comprehensive research to ensure that your intellectual property law research paper is well-supported by relevant legal sources and up-to-date literature.
• Custom Formatting : Our writers are well-versed in various citation styles, including APA, MLA, Chicago/Turabian, and Harvard. We will format your research paper according to your specified citation style, ensuring accuracy and consistency throughout the paper.
• Top Quality : We are committed to delivering research papers of the highest quality. Our team of editors reviews each paper to ensure that it meets the required academic standards and adheres to your instructions.
• Customized Solutions : At iResearchNet, we recognize that each research paper is unique and requires a tailored approach. Our writers take the time to understand your specific research objectives and create a paper that aligns with your academic goals.
• Flexible Pricing : We offer competitive and flexible pricing options to accommodate students with varying budget constraints. Our pricing is transparent, and there are no hidden fees or additional charges.
• Short Deadlines : We understand that students may face tight deadlines. Our writers are skilled in working efficiently without compromising the quality of the research paper. We offer short turnaround times, including deadlines as tight as 3 hours.
• Timely Delivery : Punctuality is a priority at iResearchNet. We ensure that your completed research paper is delivered to you on time, allowing you ample time for review and any necessary revisions.
• 24/7 Support : Our customer support team is available 24/7 to assist you with any queries or concerns you may have. Feel free to contact us at any time, and we will promptly address your needs.
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When it comes to writing an exceptional intellectual property law research paper, iResearchNet is your reliable partner. With our team of expert writers, commitment to quality, and customer-centric approach, we are dedicated to helping you succeed in your academic pursuits. Whether you need assistance with choosing a research paper topic, conducting in-depth research, or crafting a compelling argument, our custom writing services are designed to provide you with the support and expertise you need. Place your order with iResearchNet today and unlock the full potential of your intellectual property law research.

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Intellectual Property Law Dissertation Topics

Published by Ellie Cross at December 29th, 2022 , Revised On May 3, 2024

A dissertation or a thesis in the study area of intellectual property rights can be a tough nut to crack for students. Masters and PhD students of intellectual property rights often struggle to come up with a relevant and fulfilling research topic; this is where they should seek academic assistance from experts.

An individual, a group, an association, an organisation or a company that wants to claim ownership of a particular design, piece of art, technology, literature, or physical or virtual property must adhere to a specific set of rules. Without these regulations, known as intellectual property rights, concerning parties will not be secure, and anyone could easily steal from them. If someone else attempts to take the property, the original owners are guaranteed the right to keep and reclaim it.

So let’s take a look at the list of unique and focused intellectual property law dissertation topics, so you can select one more suitable to your requirements and get started with your project without further delay. Don’t forget to read our free guide on writing a dissertation step by step after you have finalised the topic. 

A List Of Intellectual Property Law Dissertation Topics Is Provided Below

• How can virtual companies ensure that copyright rules are followed while creating their logos, websites, goods, and designs?
• What does it mean legally to own an original work of art or piece of property?
• Can the most recent technical developments coexist peacefully with the present patent rules and system?
• Does the UK’s intellectual property legislation protect the owners and users fairly and securely?
• Is there a connection between European and British intellectual property laws?
• Comparison of the institutions and regulations governing intellectual property in the US and the UK
• What do fair pricing and fair dealing with copyright regulations mean?
• Can a business or individual assert ownership of a colour scheme or hue?
• The conflict between business law and trade secrets
• The Difficult Relationship Between Intellectual Property and Contemporary Art
• Trade-Related Aspects of IP Rights: A Workable Instrument for Enforcing Benefit Sharing
• A US-UK Comparison of the Harmonisation of UK Copyright and Trademark Damages
• The difficulties brought by digitalisation and the internet are beyond the capacity of the copyright system to appropriately address them. Discuss
• Which copyright laws can be cited as protecting software?
• The law on online copyright infringement facilitation
• The necessity for companies to safeguard their brand value should serve as the primary
• Justification for trademark protection. The general welfare is only a secondary concern. Discuss
• Intellectual property rights are being directly used by businesses and investors: IP privateering and contemporary letters of marque and reprisal
• Decisions and dynamics in understanding the role of intellectual property in digital technology-based startups
• Investigating conflicts between appropriable and collaborative openness in innovation
• Assessing the strength and scope of our system for protecting the intellectual property rights of indigenous people
• Assessing legal protections for intellectual property rights online
• Does EU copyright legislation adequately balance the requirements of consumers and inventors?
• A case study of the US is used to evaluate fair dealing in terms of copyright law.
• Contrasting and comparing the US and UK intellectual property systems
• Are consumers and owners protected and treated fairly under EU intellectual property law?
• What effects has EU legislation had on the UK’s intellectual property system?
• What more should be done to increase the efficacy of the US’s present intellectual property laws?
• Analysing how Brexit may affect the UK’s protection of intellectual property rights
• An in-depth analysis of the UK’s invention and patenting system: Can the existing, rigid system stimulate innovation?
• The Role of Intellectual Property Rights in Promoting Innovation and Economic Growth.
• Comparative Analysis of Patent Laws: Case Study of the US, EU, and China.
• Challenges and Solutions of the Copyright Protection in the Digital Age
• The Impact of Open Access Initiatives on Intellectual Property Rights.
• Emerging Issues in Trademark Protection in the Global Marketplace
• Intellectual Property Enforcement in the Era of Online Piracy.
• Intellectual Property Rights and Artificial Intelligence
• Legal Frameworks and Indigenous Right for Biopiracy and Bioprospecting
• Plant Breeders’ Rights
• Pharmaceutical Patents and Access to Essential Medicines in Developing Countries.
• Intellectual Property Rights in the Fashion Industry

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When choosing a topic in intellectual property law, make sure your selection is based on your interests.

As an intellectual property rights law student, there are many areas you might base your thesis or dissertation on. For example, a copyright lawyer can defend the rights of creative works, a patent lawyer can provide lawful protection for inventors, and a trademark lawyer can assist with the protection of trademarks.  You could also investigate rights related to plant varieties, trade dresses, and industrial designs.

Dissertations take a lot of time and effort to complete. It is essential to seek writing assistance if you are struggling to complete the paper on time to ensure you don’t end up failing the module.

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To find Intellectual Property Law dissertation topics:

• Study recent IP developments.
• Examine emerging technologies.
• Analyse legal debates and cases.
• Explore global IP issues.
• Consider economic implications.
• Select a topic aligning with your passion and career goals.

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In general, business law regulates the legal rights, conducts, and relationships of individuals with businesses engaged in trade, commerce, or other commercial activities. The subject covers a broad range of ideas that fall under the business law.

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Roles of Arbitration in International Intellectual Property Dispute Resolution

279 Pages Posted: 18 Jun 2020

Adam Richard Tanielian

Ramkhamhaeng University - Institute of International Studies; King Faisal University; National Institute of Development Administration; University of Mississippi

Date Written: 2013

This dissertation focuses on intellectual property disputes with a dual aim of proposing ways to improve time and cost efficiencies in existing dispute resolution processes, and to develop new systems. Litigation and arbitration are reviewed for their strengths and weaknesses. Arbitration has weaknesses including the mutual consent requirement, lack of appeal, absence of a system of case law, and jurisdictional variations relating to arbitrability of certain IP disputes. However, advantages of arbitration such as confidentiality, international applicability under the New York Convention, limited discovery, and use of specialized tribunals support a recommendation of arbitration as the better method. Multijurisdictional and internet disputes are highlighted. Comparative legal review and analysis is made, primarily pertaining Canada and the USA in order to clarify issues within NAFTA. Comparison of American and Canadian case law and statutes on patents, trademarks, copyrights, licensing, and trade secrets show similarities and differences between the nations. Lex loci and lex fori differences between nations like Canada and the USA make arbitration more appealing than litigation. National policies strongly favor arbitration. Despite minor differences, the Federal Arbitration Act is considered comparable to UNCITRAL Model Law implementing statutes in practice. Recognition and enforcement of foreign and domestic arbitral awards is available, and courts are most often unwilling to disturb awards rendered by tribunals. Rules of arbitration from UNCITRAL, LCIA, ICC, and WIPO are reviewed. Court cases, primarily from the USA and Canada, show interconnectedness between the FAA, Model Law, and rules of arbitration. WIPO is determined to offer the best services for IP disputes, although the degree of control over the arbitration process allows parties to tailor any proceedings to fit their particular needs. Lack of real remedies to internet piracy makes online dispute resolution a key aspect of the bright future of arbitration, which is more powerful than litigation in international disputes. Recommendations include that internet infringement disputes be referred to compulsory arbitration under a new UDRP-style system. Arbitration is recommended for the gamut of IP disputes. Parties to contracts are recommended to include clear and comprehensive provisions in contractual clauses. The continued evolution of private international trade dispute resolution is supported.

Suggested Citation: Suggested Citation

Adam Richard Tanielian (Contact Author)

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AI and IP: Theory to Policy and Back Again – Policy and Research Recommendations at the Intersection of Artificial Intelligence and Intellectual Property

• Open access
• Published: 20 June 2023
• Volume 54 , pages 916–940, ( 2023 )

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• Peter Georg Picht 1 &
• Florent Thouvenin 2  

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The interaction between artificial intelligence and intellectual property rights (IPRs) is one of the key areas of development in intellectual property law. After much, albeit selective, debate, it seems to be gaining increasing practical relevance through intense AI-related market activity, an initial set of case law on the matter, and policy initiatives by international organizations and lawmakers. Against this background, Zurich University’s Center for Intellectual Property and Competition Law is conducting, together with the Swiss Intellectual Property Institute, a research and policy project that explores the future of intellectual property law in an AI context. This paper briefly describes the AI/IP Research Project and presents an initial set of policy recommendations for the development of IP law with a view to AI. The recommendations address topics such as AI inventorship in patent law; AI authorship in copyright law; the need for sui generis rights to protect innovative AI output; rules for the allocation of AI-related IPRs; IP protection carve-outs in order to facilitate AI system development, training, and testing; the use of AI tools by IP offices; and suitable software protection and data usage regimes.

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1 Introduction

The interaction between artificial intelligence (AI) and intellectual property rights (IPRs) is one of the key areas of development in intellectual property law. After much, albeit selective, debate, it seems to be gaining increasing practical relevance through intense AI-related market activity, an initial set of case law on the matter, and policy initiatives by international organizations (e.g. WIPO, EPO) and lawmakers.

Against this background, Zurich University’s Center for Intellectual Property and Competition Law (CIPCO) is conducting, together with the Swiss Intellectual Property Institute (IPI), Footnote 1 a research and policy project (hereinafter the “AI/IP Research Project” or “Project”) that explores the future of intellectual property law in an AI context. This paper briefly describes the AI/IP Research Project (Sect. 2 ) and presents (Sect. 3 ) an initial set of policy and research recommendations (“Recommendations”) for the development of IP law with a view to AI. It concludes (Sect. 4 ) with a look at possible topics for additional recommendations. For a terminological and technical description of artificial intelligence, Footnote 2 and for further background to the Recommendations below, as well as for AI/IP aspects that they do not address, this paper refers to the rich existing literature. Footnote 3

2 The AI/IP Research Project

Initiated in 2021, the AI/IP Research Project aims at (i) gaining an overview of the current state of affairs in AI/IP, (ii) assessing issues crucial at the present stage, and (iii) deriving policy recommendations for how European jurisdictions, including Switzerland, should position themselves in international collaboration and in national law-making regarding AI/IP. Methodologically, the Project chooses a multi-component approach that has included, so far, mainly a comparative analysis of the AI/IP law situation – across the range of major IP rights Footnote 4 – in various jurisdictions, the gathering of first-hand empirical evidence through stakeholder input (e.g. industry representatives, specialized counsel, members of state and supra-state IP administrations), and an interdisciplinary exchange with innovation economists and computer scientists specializing in AI. As a backbone of its 2021/2022 activities, besides desk research work, the Project conducted a series of workshops Footnote 5 in which legal, economic and technical experts, as well as company representatives and other stakeholders, presented and discussed key AI/IP aspects. Footnote 6 Our warmest thanks go to all those who have participated and are participating in the Project. Footnote 7 Their support is invaluable in the attempt to further an appropriate IP law framework for AI. At its next stage, the Project will, inter alia , intensify the intra-disciplinary legal discourse with scholars working on AI from angles other than core IP law, e.g. data law, contract law, and liability law.

3 Policy Recommendations

We distinguish three types of Policy Recommendations: Implementation Recommendations intend to guide the next steps in law and policy-making. We think, based on previous discourse and experience, that their beneficial effects are likely enough to put them into practice. Consideration Recommendations describe courses which the law should probably take. Some further reflection and research seem, however, advisable before implementing them. Research Recommendations identify issues that research should address, to produce consideration recommendations on these matters as well.

3.1 Implementation Recommendations

3.1.1 inventorship in patent law, 3.1.1.1 recommendation.

The law should be amended to allow the designation of AI systems as inventors. Meanwhile, patent applications should be free to designate persons as “proxy inventors” while also describing the inventive activity of the AI system. There should be more disclosure on such inventive activity. AI systems’ innovative abilities must become part of the PHOSITA concept and related protectability thresholds.

Where an AI system generated inventive output without inventive human intervention, the patent application should be permitted to say so and name the AI system as the inventor, along with a natural person or legal entity who claims ownership of the patent application and a resulting patent.

Until legal rules have (where necessary) been changed to accommodate the above Recommendation, natural persons should – as a temporary workaround – be allowed to act and register as “proxy inventors”, as long as they disclose this role and the AI system for which they act as proxy. Such disclosure should be provided in the description.

More honest recognition of the increasingly innovative role AI systems play in invention processes, however, also calls for stricter requirements for patent applications to disclose details regarding the nature, extent, and mechanism of an AI system’s inventive contribution.

Furthermore, AI system abilities must become part of the PHOSITA Footnote 8 concept and related protectability thresholds. A potential raising of the protectability bar resulting therefrom is welcome as it mitigates the risk of AI patent thickets.

3.1.1.2 Background

The question of whether patent law can and should recognize AI systems as inventors, if they generate otherwise patentable technical solutions without an inventive contribution by humans, is arguably the most conspicuous issue in the current AI/IP landscape. Besides academic debate, Footnote 9 the multi-pronged DABUS litigation plays a key role as it probes into a range of the most important patent jurisdictions on whether their existing rules permit AI system inventorship. So far, the track record of patent applications based on the inventions (allegedly) made by DABUS is not a very successful one and the rejecting patent offices or courts seem right in finding that the currently applicable patent law rules are oriented to human, not AI inventorship. Footnote 10

De lege ferenda , however, at a forward-looking policy level, important reasons weigh in favour of patent applications that openly describe the role AI systems have played in the invention process. A need to definitively assess whether the human contribution to an invention, relative to the contribution made by an AI system, is sufficient to establish human inventorship, and thus patentability, unnecessarily harms legal certainty and uses patent office resources. It is one of the functions of the patent system to instruct the public about the progress of innovation and, thereby, to induce further innovation, for instance in the form of follow-on inventions. Necessitating patent applicants to disguise the true relation between human and AI contributions to an invention, because they must otherwise fear that their application will be rejected, hampers this function. Such impairment becomes even stronger where AI-generated inventions are not submitted for patenting at all but remain confined to the realm of trade secrets. In fact, industry participants in the Project state that companies do prefer trade secrets over patents for AI-generated inventions where they perceive a high risk of ending up – after having to disclose their invention in a patent application – without IP protection because the determinant role of their inventive AI systems, if admitted, prevents patentability.

Remarkably, these and further advantages of openness regarding inventive AI systems have made courts creative in searching for solutions even de lege lata , under the provisions of current patent law. The German Federal Patent Court (“ Bundespatentgericht ”) and the EPO Boards of Appeal now seem to accept a sort of proxy human inventorship. According to this concept, an application must still formally name a natural person as the inventor, but it can, at the same time, explain that the inventive acts were performed by an AI system. Footnote 11 Although unnecessarily complicated and formalistic, the proxy human inventor approach presents an acceptable transitional solution until patent laws can be changed as recommended here.

Even if this patent law reform occurs, it will not obviate the need to designate the natural – or possibly legal ( cf . Sect. 3.2.1 ) – person who becomes the initial owner of the granted patent and who, consequently, acquires the rights and obligations related to this position. Our Recommendation does not advocate patent ownership of AI systems. Since innovative human activity cannot be the parameter for determining initial ownership of patents on purely AI-generated inventions, the law must develop a set of different criteria ( cf . Sect. 3.3.2 ). This exercise is all the more worthwhile because its results are key for many an AI/IP setting: where increasing prowess and independence of AI systems render it difficult to assign legal rights to their output based on human inventorship, creatorship, or similar concepts, other parameters must step in to safeguard an allocation that is economically sound and apt to fulfil the goals of the IP system.

This is not to ignore the fact that a large part of the inventions made today and in the near future result (also) from a human contribution substantial enough to acknowledge human inventorship without difficulties. The pertinent part of the above Recommendation does not deal with AI-assisted inventions but with truly AI- generated ones. These hard cases may be rare – some would even say: non-existent – at present. But their relevance seems very likely to increase, and the law should be prepared by then.

Assessing the novelty of an invention against the state of the art researched with the help of AI systems, and only accepting steps as inventive which so appear from the perspective of a PHOSITA equipped with an ordinarily skilled AI system, will most probably raise the bar for patent protection. Footnote 12 In their contributions to the Project, some stakeholders voiced the concern that, as a result, only resourceful players, commanding exceptionally performant AI systems, may be able to acquire patents in the future. While we acknowledge the theoretical validity of this point, we do not see any empirical evidence that such a development is underway in larger sectors of the economy. Furthermore, it has always been the case that greater resources – such as laboratories with superior equipment, larger research departments, the ability to pay high wages to attract the best researchers, etc. – increased the chance of a market player to accumulate patents. In sum, we do not currently think that unlevel-playing-field concerns should prevent the integration of AI system capacities into the patentability assessment.

3.1.2 Human Authorship in Copyright Law

3.1.2.1 recommendation.

The principle of human authorship should prevail in copyright law – at least in the droit d’auteur systems. Hence, copyright protection should not be extended to works of literature and art created by an AI system without a human contribution even if they amount to a creation in the sense of copyright law. This result is achieved by applying the established criteria of human creation. At the same time, this allows for granting copyright protection for content that has been collectively created by an AI system and a natural person provided that the human contribution is sufficiently creative.

3.1.2.2 Background

Intellectual property law is traditionally based on the idea of one (or several) human creator(s). That is especially true for copyright law, at least for the droit d’auteur systems. In these systems, the idea of a human author is firmly rooted in many key provisions.

The human author plays a key role in the conditions for the protection of a work. According to settled case law of the ECJ, the concept of a work entails an original subject matter which is the author’s own intellectual creation. Footnote 13 Accordingly, there is no work without an author and such author must always be a natural person. Footnote 14 The situation is similar in Swiss law which only protects intellectual creations with an individual character (Art. 2(1) Copyright Act). The requirement of the intellectual creation means that only works created by natural persons can be protected by copyright. Footnote 15 The link of the intellectual character to a human author may be less direct but it is no less important; according to the key test, the requirement of individual character is met if no other individual would have created an identical or highly similar work. Footnote 16 The human being is also the key figure for copyright ownership as the original rightholder is always the author, i.e. the natural person who created the work. Footnote 17 In addition, droit d’auteur systems provide for a series of personality rights, such as the right to recognition as the author and the right to determine the author’s designation, Footnote 18 the right to decide on the first publication of the work, Footnote 19 the right to decide if the work may be altered and/or used to create a derivative work, Footnote 20 and the right to oppose a distortion of the work. Footnote 21 Finally, all copyright systems calculate the term of protection starting from the death of the author. Footnote 22

While some copyright systems have granted copyright protection for machine-generated content for years, Footnote 23 the droit d’auteur systems are hardly suitable to do so. A fundamental shift in these systems would be necessary to accommodate protection of machine-generated content by rethinking and adapting the provisions on the requirement of protection, the initial rightholder, the granting (and exercising) of personality rights and the duration and calculation of the term of protection. However, there are no convincing reasons why this should be done. While we acknowledge that there are some arguments for granting copyright protection to AI-generated works, these arguments seem rather weak. Most importantly, it may not necessarily be convincing to treat works that seem to be similarly “creative” in a fundamentally different way, just because one has been produced by a machine and the other by a human being. However, works of literature and art are public goods and granting exclusive rights to such goods requires a sound justification. Given that all other rationales for the justification of copyright protection (namely personality rights and the labour theory) are closely linked to human creators, the only potential rationale for granting copyright protection for machine-generated works is the need to provide incentives for creative activities. However, once an AI system has been developed, it can produce content such as text, images, music, films, and the like at almost zero marginal cost. While it may be important to grant some form of IP protection for the AI system, there is no need to incentivize the use of these systems by granting copyright protection to their output. Footnote 24

There are other instruments for protecting output that has been created in a fully automated manner and lawmakers (and courts) could improve such instruments, if necessary. Most importantly, the “copy paste” and use of AI-generated content may be captured by unfair competition law, namely by applying the general clause of most European unfair competition acts that allow to capture imitations and the copy-pasting of third-party content if certain conditions are met. Footnote 25 In Switzerland, Art. 5(c) Unfair Competition Act seems to be a good match. This provision captures all instances of taking over and exploiting another person’s marketable work product by means of a technical reproduction process without reasonable effort of the person or company that takes over and exploits the work product. Should unfair competition law prove to be insufficient to accommodate justified needs for protection, lawmakers could consider creating specific neighbouring rights for content generated by AI systems. Footnote 26 From today’s perspective, however, there seems to be no need for such new rights. Footnote 27 In addition, creative software output of AI systems – potentially including settings where an AI system creates another AI system – may be covered by the software protection regime envisaged in these Recommendations ( cf . Sect. 3.3.1 ).

In addition, it is important to bear in mind that denying copyright protection to AI-generated content does not mean that the producer cannot exploit such content on the market. Most importantly, such content can be protected by access restrictions and other technical measures, e.g. digital watermarks, to ensure that others cannot use it without paying a remuneration.

3.2 Consideration Recommendations

3.2.1 corporate iprs, 3.2.1.1 recommendation.

The law should consider allowing corporations and other legal entities to acquire initial ownership of (AI-generated) patents and patent-related IPRs (e.g. utility patents, but not copyrights), at least in cases of AI inventorship.

3.2.1.2 Background

The discussion whether legal entities should be able to acquire the right to a patent and – following the grant of the patent – initial patent ownership is not new. So far, and though dissenting ( de lege ferenda ) views always existed, Footnote 28 the prevailing response has been negative, Footnote 29 not least because today’s patent laws give much weight to a personalistic notion of inventorship, according to which there cannot be an invention without a (human) inventor. Footnote 30 When, however, an invention is generated by an AI system, this conception seems much less convincing. The assignment of legal rights and economic benefits relating to such inventions relies less on personalistic criteria. For instance, companies, and not their employees, will frequently bear the costs for building an inventive AI system and they, not their employees, will exercise legal and economic control over these systems. Insisting on human initial patent ownership in such settings risks distorting a coherent assignment of legal and economic rights to non-human inventions. The law should, therefore, consider relaxing the rules that allow for human initial patent ownership only. Footnote 31

3.2.2 Need for New IPRs Doubtful

3.2.2.1 recommendation.

Currently, there is no need to establish new sui generis IPRs for AI output. Neither current research insights nor current market realities suggest a need for new (sui generis) IPRs (including neighbouring rights) for innovative or creative AI output. Unless future research, including work done as part of the AI/IP project, proves the opposite, lawmakers should abstain from establishing such new types of IPRs.

Furthermore, there are currently no sound reasons for a two-tiered system of differing protection for human and AI inventions and creations. On the contrary, such a system seems prone to generate delimitation predicaments and to entice concealment or deliberate distortion of the genuine innovative process.

Such restraint does not exclude improvements of the current protection regime, for instance, in order to better accommodate software (including AI systems) produced by an AI system ( cf . Sect. 3.3.1 ), the way data rights are allocated, or the framework for trade secret protection.

Should future AI systems generate inventive output at a high rate and in a process that clearly lacks human inventive contribution, the situation may have to be reconsidered. Patent-like protection for such output, which is however weaker than the protective level of current patents, may become a preferable mechanism for allocating exploitation and transaction rights while avoiding over-protection.

3.2.2.2 Background

In academic discourse, proposals have been made for new types of intellectual property rights to protect the innovative or creative output of AI. Footnote 32 Sufficient IPR protection for the AI systems that generate such output seems, on the other hand, less of a concern. Our Patent Law Inventorship Recommendation ( cf . Sect. 3.1.1 ) helps to guarantee the structural availability of IPR protection for technical AI inventions. According to our Authorship in Copyright Law Recommendation ( cf . Sect. 3.1.2 ), restricted copyright protection for creative AI output constitutes not a failure but a virtue of the IPR system. A consensus against the establishment of distinct protection systems for human and AI-generated innovations has already been formed. Footnote 33 Mainly for the reasons stated in the above Recommendation, we support this position. Regarding inventive/creative output or other instances of valuable output generated by AI systems without substantial, innovative human contributions, neither the AI/IP Project nor – to our knowledge – other empirical or economic research ( cf . also Sect. 3.3.3 ) has proven current market failures or insufficient innovation incentives that necessitate the creation of new IPRs. Growing new plants in the already lush garden of IP rights comes at a cost – e.g. anti-commons problems, Footnote 34 transaction costs or interaction issues between the various IPRs – that should only be incurred based on solid evidence of their necessity. Putting another dent in the enthusiasm for new sui generis rights, none of the new IP rights introduced in the last 50 years has proven a real success. This applies, in particular, to the protection of databases through a sui generis right Footnote 35 and the legal protection of topographies of semiconductor products. Footnote 36 Even though it seems premature to assess the impact of the new neighbouring right for the protection of press publications, the chances of success of this new IP right seem doubtful as well. Footnote 37

We cannot, however, exclude the possibility that this picture may change in the future. New ways of detecting and deciding, with sufficient certainty, whether a human or an AI system generated a particular innovation may remove some qualms regarding a two-pronged protection system for human and AI inventions and creations. Extending patent protection at its current level (duration, scope of exclusivity, etc.) to AI-generated inventions may become an unacceptable impairment of dynamic efficiency and freedom to do business, if previsions come true that powerful AI systems will swamp the markets with innovative output at high rates and high quality. Then – and only then – should the law consider conceptualizing new types of limited IP protection, mainly for technical inventions. Such IPRs could combine the transactional benefits of a clear allocation of rights, Footnote 38 incentivization for the creation and maintenance of high-quality AI-systems, Footnote 39 disclosure of innovations to the public, and – for instance, through suitable licensing mechanisms – balanced access to protected content by other market participants. Utility patents do not necessarily provide a blueprint for such AI-specific, “narrow” IPRs, but at least they show that varying levels of protection for technical inventions is a concept that is workable and familiar to the IP system.

3.2.3 Broadened Research Exemption

3.2.3.1 recommendation.

Subject to further research, IP and data law should likely stipulate clearer and more permissive protection carve-outs to facilitate development, training, and testing of AI systems.

The development, training, and testing of AI systems requires the processing of very large amounts of data. Given the extremely broad definition of personal data in data protection laws, Footnote 40 much of these data are to be qualified as personal data and their use is thus subject to the provisions of the General Data Protection Regulation (GDPR) and other data protection laws. In many instances, the data used by AI systems are digital representations of works of literature and art. This is usually the case when AI systems are to recognise or produce text, images, music or films, and therefore need to be trained with corresponding copyright content. In addition, many data used by AI systems will be protected by the sui generis database right. Trade secret or patent protection, for instance, can also come into play. Using data for the development, training, and testing of AI systems may thus violate the provisions of the GDPR or infringe copyrights, the sui generis right in databases, or other intellectual property rights.

Patent and copyright laws, as well as other IP protection systems, contain provisions that allow the use of protected content for research and development, but it seems doubtful whether the existing exemptions are sufficiently broad and homogeneous across jurisdictions to allow for the desired use level of such content by AI systems. Footnote 41 The Database Directive, for instance, does not contain any research exemption for the sui generis right. European lawmakers should thus consider introducing broader research exemptions in copyright law, and creating a research exemption for the sui generis right in databases. Footnote 42

While the GDPR contains provisions that amount to a potentially quite broad research exemption, Footnote 43 it remains unclear if and to what extent this exemption can be applied to privilege the processing of personal data for the development, training, and testing of AI. Given the key importance of data (including personal data) and the lack of harm caused to data subjects by the processing of personal data in the development, testing, and training of AI systems as such (note though that harm may be caused to data subjects by using AI systems Footnote 44 ), we recommend that the GDPR’s research exemption should be interpreted in a way that facilitates such processing. Ideally, this interpretation should be explicitly promoted in an Opinion of the European Data Protection Board (EDPB) to provide legal certainty.

3.2.3.2 Background

Today’s IP and data protection laws were developed prior to the rise of AI. Footnote 45 Although patent, copyright, and data protection laws contain research exemptions, it is unclear if and to what extent these provisions can capture the use of personal data and IP-protected content if the respective data are used for the development, training, and testing of AI systems.

Regarding copyright law, the two exceptions for text and data mining introduced by the Digital Single Market (DSM) Directive Footnote 46 may mitigate the problem. The mandatory exception, however, only covers uses for scientific research by research organisations and cultural heritage institutions, thus excluding text and data mining in a commercial context. Footnote 47 The non-mandatory exception that also applies to commercial uses only covers cases in which text and data mining has not been expressly preserved by the rightholder. The scope of these exceptions is therefore limited. Moreover, the DSM Directive does not mention the use of text and data by AI systems. It is therefore unclear whether the exceptions also cover the use of copyright content for the development, training, and testing of AI systems. The recently introduced research exemption of the Swiss Copyright Act is substantially broader, covering all research and development (including for commercial purposes) and all reproductions that are necessary for technical reasons. Its deliberately broad wording should also cover the use of copyright-protected content by AI systems, both in a research and in a commercial setting.

The sui generis right allows the maker of a database to prohibit the extraction and/or re-utilization of the whole or a substantial part of the contents of a database. However, insubstantial parts may be used by lawful users of the database. While this certainly limits the restrictions of the sui generis right with respect to the use of data by AI systems, one must assume that there are many cases in which it would be useful to extract and re-use all or substantial parts of a database. Thus, the sui generis right imposes relevant restrictions on the use of data by AI systems. As opposed to copyright law, the Database Directive does not even contain an exception for text and data mining. In consequence, adding a broad research exemption to the Directive that also covers the use of data for the development, training, and testing of AI systems seems to be key. Importantly, such an exemption would not confer a standalone right of access to the data contained in a database. It would merely allow the use of data for research purposes if access to such data has already been granted, most often on a contractual basis and against remuneration.

European data protection laws, especially the GDPR, create significant obstacles to the use of data by AI systems, such as the principle of data minimization and purpose limitation, as well as the need to provide a legal basis for the processing of personal data. Footnote 48 Additional barriers stem from restrictive rules on the transfer of personal data to third countries and the increasingly impractical distinction between personal and non-personal data. While the GDPR contains provisions that potentially amount to a quite broad research exemption, Footnote 49 it remains unclear if and to what extent this exemption can be applied to privilege the processing of personal data for the development, training, and testing of AI. However, a suitable application of the research exemption can only be a first step. As outlined below, further research is needed to develop a suitable data usage framework. Footnote 50 In addition, clear and comprehensive data access and/or data use rights Footnote 51 should be established, regarding both personal and non-personal data, to facilitate the development, training, and testing of AI systems.

At the same time, protection carve-outs must not become a carte blanche for IPR infringement. Generative art (art with and through AI) is, for instance, a field in which legal rules need to carefully balance access to and protection of IPR-protected content. AI is a powerful tool for creating works such as films, music, or architectural designs. Such tools are already being offered to the general public for free. The conditions for use of such tools and their output (including sale as non-fungible tokens) vary greatly and can have important effects on the operating modes and business models of the artistic community. Some developers are not sufficiently aware of, or are not willing to abide by, copyright protection rules. Others miss out on advantageously structuring the use of their tools through contractual arrangements. Working, together with stakeholders, from this situation towards a more appropriate legal and factual framework for generative art constitutes a worthy task both for IP offices and for the general discourse on AI protection carve-outs.

3.3 Research Recommendations

3.3.1 new software protection regime, 3.3.1.1 recommendation.

Future research should develop a novel IP protection regime for software that could replace today’s two-tiered approach.

The current IP system does not provide a convincing protection regime for software. The interaction of its main instruments, copyright and patent protection, is far from ideal. The regime has evolved over time, driven by the approach to somehow incorporate software protection into the traditional IP system. However, software differs in important respects from both works of literature or art and from technical inventions. Fitting it into copyright and patent law thus necessitates many compromises. Software produced and employed by AI systems is a recent challenge of particular importance to today’s approach. Therefore, the development of AI systems makes it more urgent than ever to remedy the deficiencies of the current regime for software protection.

The dual system combining copyright and patent protection should be rethought and possibly replaced by a single IPR for software (including AI systems). Such a regime may combine a very limited sui generis protection (regarding both substance and duration) for unregistered software with a stronger protection for software registered in a software register. The granting of a strong IP right could come with (source code) disclosure requirements. Better tailored to promote innovation and to avoid overprotection, such a system may also allow for the closing of current protection loopholes, e.g. regarding complex, highly innovative modelling software.

Given the huge economic importance of software, the implementation of such far-reaching changes in its protection regime resembles open-heart surgery. These changes cannot be undertaken without thorough prior research and discussion. Such research must be interdisciplinary, involving not only legal scholars but also computer scientists and economists. All stakeholders’ (software developers, industry, IP offices, the open source community, and key user groups, etc.) views need to be collected and novel protection approaches need to be tested in a discourse with them.

Given the existing framework of IP treaties, a novel software protection regime could hardly replace the current system over night. But novel approaches could be introduced at a national and regional (e.g. EU) level alongside the existing regimes. If these approaches prove workable, they may well replace the current protection regimes de facto, namely if companies stop applying for software patents and enforcing copyrights. Traditional approaches for software protection may either continue to (formally) exist or be abandoned altogether at a later point in time.

3.3.1.2 Background

Software has always been a sort of outsider among the subject matters of the IP system. The protection regimes that are applied to computer programs were developed long before software even existed. As it seemed virtually impossible to create an entirely new IP right to capture software in the 1980s and 1990s, national lawmakers and international organisations had no choice but to accommodate software in the existing IP regime. The obvious choice was copyright as it came with a series of benefits, the most important ones arguably being that the existing international regime allowed for an almost worldwide protection without the need for application, examination, registration, and payment of fees. In addition, the inclusion of software in patent law was blocked (at least) for the member states of the European Patent Convention as Art. 52(2)(c) EPC states that programs for computers cannot be considered inventions. The “linguistic approach”, focussing on the expression of algorithms in the source code, permitted software to be treated similarly to works of literature and art, Footnote 52 thus allowing copyright protection. With partial amendments to copyright law, e.g. on decompilation Footnote 53 or shortened protection terms, Footnote 54 some steps were taken towards a software-specific protection regime, but without accomplishing this task.

Irrespective of this integration process, businesses also sought the benefits of patent protection for their software. In the US, such patents were granted on a relatively broad basis following a series of Supreme Court decisions in the 1970s and 1980s, culminating in Diamond v. Diehr in 1981, Footnote 55 and subsequent decisions by the Court of Appeal for the Federal Circuit. Footnote 56 Europe remained reluctant, given the provisions in the EPC that excluded patents for computer programs as such (Art. 52(2)(c) and (3) EPC). While patents were (and still are) unavailable for mere computer programs, they were eventually granted for so-called “computer-implemented inventions”. Footnote 57 Over time, the more permissive US and the more restrictive European approach have converged to a certain extent. Inter alia , the US system became more stringent, and moved much closer to the European approach, with the Supreme Court’s Alice decision. Footnote 58

As a result of these historical developments, software can be protected by both patents and copyrights in the major jurisdictions. While it is not uncommon for several IP rights to protect a given object – e.g. copyright, design, patent, and trade mark rights to protect the design of a car – it is quite unusual for a given subject matter category to be explicitly covered by more than one IP right. Not surprisingly, this two-tier system of protection leads to contradictory results. For instance, despite the expiry of patent protection after 20 years, previously patented software does not fall into the public domain but remains protected by copyright for a much longer period of time.

A major problem of the current software protection regime is the fact that neither copyright nor patent law are well suited for this subject matter. Software is different from both technical inventions and works of literature and art. IP protection granted to it should be keyed to these particularities. For example, many software products (e.g. operating systems) cannot be substituted by others because they have become de jure or de facto standards. Software products need to be integrated into a (usually pre-existing) framework of hardware and software, which requires interoperability that can only be ensured if application programming interfaces (API) are provided or – where necessary – lawfully developed through reverse engineering. In digital economies, software assumes a sort of infrastructure role for ever more products and services. Also, in view of these characteristics, the strong protection (duration, degree of exclusivity, etc.) granted by the combination of copyrights and patent rights seems problematic at least for certain types of software (e.g. update patches). Licensing transactions ensuring freedom to operate are hampered by difficulties in determining software ownership and by multi-owner IPR thickets. Fragmented statutory rules and market developments, such as the “open source” movement, have patched some of these issues. Others have led to highly complex and year-long proceedings before competition authorities. Footnote 59 A well-tailored protection framework, including built-in limitations that secure access rights where needed, promises many advantages over these makeshift approaches. It becomes all the more desirable with a view to AI systems consisting, in essential parts, of software and generating large-scale software output the protection status of which is far from evident. Footnote 60

While it seems that software developers and the industries producing and using software have learned to cope with the current software protection framework, important issues remain unresolved. Moreover, the mere fact that developers and the industry have learned to make the best of the current software protection regime in no way precludes that a much better system could be created, i.e. a system that leads to faster and cheaper innovation and raises fewer competition issues.

3.3.2 AI Inventorship and IPR Allocation Parameters

3.3.2.1 recommendation.

Future research should develop a comprehensive grid for the allocation of entitlements resulting from innovations generated by AI systems.

As a key consequence of loosening the ties between the generation of innovative output (by AI systems) and the ownership of resulting IPRs (by natural or legal persons), research must work out a more comprehensive grid for the sound allocation of IP entitlements resulting from innovations generated by AI systems. This concerns a broad range of IPRs (e.g. patents, utility patents, design rights, and new forms of software protection), as well as settings where complementary innovative activity is undertaken by AI systems and human individuals or teams.

3.3.2.2 Background

An appropriate allocation of AI output-related IPRs to natural or legal persons sets the conditions for achieving the IP system’s goals, particularly the incentivization of innovation and the fostering of IP transactions – licensing in particular, but for instance also the use of IP as collateral in M&A and venture capital transactions – which help to disperse and implement protected content. The conduct-steering effect of liability as well as clear responsibilities in the IP system’s self-protection through the enforcement of IPRs against infringing use are further allocation-related benefits. Allocating rights and responsibilities to AI systems themselves is not an option due to these systems’ lack of personality in the legal sense.

There is already some discussion about parameters for allocating IPRs resulting from AI innovation. Footnote 61 Among the main candidates are creatorship of or investment in the output-generating AI system, control over the system at the time of innovation, and responsibility for task and output selection (choice-making). Furthermore, some jurisdictions have adopted statutory rules that assign – be it for AI settings or at a more general level – initial IPR ownership to persons other than the factual inventor. Footnote 62 However, these allocation elements do not yet form a sufficiently comprehensive framework. The additional questions such a framework would have to answer are manifold. What, for instance, is the – possibly sector-specific – hierarchy or relative weight of several applicable allocation parameters? In case different persons fulfil different allocation criteria, does this always result in co-ownership Footnote 63 or do certain allocation parameters (sometimes) outweigh others? For settings in which co-ownership turns out to be the result, are IP law’s present rules on co-ownership appropriate, even though there are no non-economic inventor/author rights to be protected? Assuming that certain groups of (co-)rightholders yield to requests that they waive their position, e.g. for fear of otherwise losing downstream clients, Footnote 64 should the law accept such contractual arrangements?

Arranging the answers to such questions into a suitable allocation regime requires profound research. Such research needs to include legal, economic and technological aspects, including an incentives analysis ( cf . 3.3.3) for accommodating novel allocation approaches.

3.3.3 Revisit Incentivization Necessities and Ownership Approach

3.3.3.1 recommendation.

The IPR system must not mechanically extend its traditional incentivization rationale to innovative AI output. AI systems themselves do not require incentivization. Effective and efficient incentives for natural/legal persons to engage in the development and use of high-quality AI systems, as well as in the implementation of and transactions over their innovative output, need not necessarily parallel traditional IPR incentives for human innovativeness. Traditional notions of ownership may have to be rethought and protection may be oriented more towards securing monetary rewards and freedom to operate than towards non-economic ownership rights.

3.3.3.2 Background

Economists point out that incentivization of AI outputs as such may be unnecessary or even detrimental, whereas it may drive innovation and dissemination to incentivize the commercialization of such outputs (including transactions over them) and the development of AI systems that generate them. Footnote 65 In view of the potentially high innovative output of (future) AI systems, granting full-fledged IPRs to each such output may, in particular, generate overcompensation and excessive IPR thickets. Research, in which economics looms large, must therefore explore incentivization exigencies and dynamics in the AI innovation field. It is crucial to avoid the unwanted effects of over- or under-protection on dynamic efficiency. Such research must also explore whether, and in which ways, the growing relevance of AI systems and data change the role IPRs play for businesses, both in daily practice and at a strategic level. Footnote 66

3.3.4 Data Usage Framework

3.3.4.1 recommendation.

Future research should develop a legal framework focusing on access, sharing and usage of (personal and non-personal) data for the common good while providing a suitable protection of privacy and workable means to protect individuals against harm resulting from data processing.

Next step research should specify legal cornerstones for enhancing the access to, usage and sharing of (personal and non-personal) data for the development, training, and testing of AI systems. Topics include novel approaches to data (protection) law, common data spaces, data pools, interoperability requirements, technical standards regarding syntax and semantics of data, and the (non-)mandatory, sector-specific licensing of data portfolios to AI users/developers on a FRAND basis.

These approaches must apply both to personal and non-personal data since access to and use of both types of data are key conditions for the development, training, and testing of many AI systems. Further research is needed on whether and to what extent the usage of personal data by AI systems risks engendering an infringement of data protection laws or personality rights, such as the right to protection of privacy. A potential way forward could be an in-depth analysis of the scope of current research exemptions in data protection laws (particularly the GDPR) to assess if these exemptions can be applied broadly to cover the usage of personal data by AI systems. But research should also consider entirely novel approaches that go beyond the idea of an all-encompassing regulation of the processing of personal data (as in the GDPR) but rather provide a workable protection of privacy and means to protect individuals against harm resulting from the processing of personal data (e.g. manipulation and discrimination) while opening up the usage of personal data for the common good. Footnote 67

This research must include both an interdisciplinary and an intra-disciplinary component. Obviously, workable data transaction frameworks cannot be conceived without the input of computer and data scientists. But even from a purely legal perspective, there are manifold issues that need to be considered beyond IP and data law, such as contract, competition and procedural law. Equally, the analysis of pertinent business models promises to be very fruitful, including collaboration between holders of large data sets and controllers of powerful AI systems.

In addition to opening up access to and use of data, in-depth research is needed to clarify the legal consequences if an AI system has been developed, trained, or tested with data that have been accessed or used unlawfully. Should this “infect” the AI system in some way, even if the system does not contain the unlawfully used data? Should the consequences be the same regardless of whether the data were used for the development, the training, or the testing of an AI system? And, should it matter whether vast or small amounts of data have been used in an unlawful way – possibly even just a single data point?

3.3.4.2 Background

Data are a key resource for AI operations, especially for AI systems that are based on machine learning. But use of and access to data are often restricted for various reasons. While the use of non-personal data is much less regulated and thus largely permissible, European data protection laws, especially the GDPR, impose significant restrictions on the use of personal data, the most important ones being: The principle of data minimization which requires that the processing of personal data be adequate, relevant and limited to what is necessary in relation to the purposes for which the data are processed; Footnote 68 this principle may inhibit the use of personal data for the training, and testing of an AI system. The principle of purpose limitation according to which data may only be collected for specified, explicit and legitimate purposes and not further processed in a manner that is incompatible with those purposes; Footnote 69 often, personal data would be a great resource for the development and training of an AI system, but that system might have a purpose which is different from the purpose for which the data were collected, e.g. geo-localization data collected by telecom service providers that could be used to train an AI system that helps to fight traffic jams and to balance public transportation occupancy. A major barrier for the use of personal data by AI systems is that some data protection laws, namely the GDPR, require a basis for the lawfulness of any processing of personal data, the most important ones being the data subject’s consent, Footnote 70 an overriding legitimate interest of the controller, Footnote 71 the need to process personal data for the performance of a contract to which the data subject is a party Footnote 72 or the need to process data for compliance with a legal obligation. Footnote 73 Although the range of possible reasons for the lawfulness of processing is quite broad, such a basis will often be lacking for the use of personal data for the development, training, and testing of AI systems.

Restrictions on access to data are another severe impediment. Companies are increasingly aware that they possess vast amounts of data that can be used in a productive way, e.g. for the training and testing of AI systems. This potential is tapped in a growing number of cases, either in house by the data holding company or through data transactions. In many other settings, though, data access and use fail. Some lawmakers, especially the EU, are enacting certain rules which aim at fostering data exchange and usage. For instance, the Open Data Directive Footnote 74 requires public sector bodies and public undertakings to make data available, including publicly funded, high-value research data. The Data Governance Act Footnote 75 should allow for the re-use of certain public sector data that cannot be made available as open data, e.g. health data. The Draft Data Act Footnote 76 will allow users of IoT devices to gain access to data generated by these devices and to share such data with third parties, thus mitigating their exclusive harvesting by initial data collectors and holders. In addition, the act will include means for public sector bodies to access and use, in exceptional circumstances, data held by the private sector. The Digital Markets Act Footnote 77 obliges gatekeepers to provide data access and portability in various ways. However, research will have to investigate whether these measures and their impact on business models generate sufficient data access for the development, training, and testing of AI.

3.3.5 Use of AI Tools by IP Offices

3.3.5.1 recommendation.

IP offices should strive to exploit the capacity of AI systems in their own operations. This may include the determination of whether an application fulfils the respective protectability requirements (e.g. novelty and inventive step). As a sound medium-term prospect, AI tools will not replace humans in the examination of IPR applications but will become one element of an interactive approach in which human and AI skills are combined to complement each other.

AI tools could help to establish more coherent decision-making within and across IP offices. At the same time, the digitization and automation of IP office processes must maintain, or should even improve, the procedural protection for applicants and further parties to their procedures. As part of such protection, IP offices should strive to render their AI tools transparent and explainable, to the extent possible and reasonable. This could include the establishment of a freely available AI tools database that enables applicants and their agents to improve the quality of their IP filing and IP management and even pre-test the chances of success of their applications.

IP offices should, among themselves, pursue an approach of transparency, insight-sharing and cooperation, which does not exclude friendly competition for benchmark solutions. WIPO may pioneer such an approach.

3.3.5.2 Background

AI can be a tool, and not only a subject, for the work of IP offices. In fact, a number of AI pertinent projects are already run by offices such as Singapore’s IPOS, UKIPO, IPI, WIPO, and EPO. Footnote 78 Much more would be possible, however, and IP offices should engage in intense, cooperative research and discussion on how to implement the above recommendation. More generally, AI has much potential to optimize administrative processes. By reaping this potential, IP office processes could become blueprints for other branches of public administration. Research topics include the identification of suitable AI application fields, e.g. automatic patent/design classification, harmonization of lists of goods and services, computer vision treatment of pictures and similar items in IPR applications, natural language processing of application content, machine translation of applications and prior art searches, and tailor-made AI systems, e.g. adversarial networks, for protectability assessments. In addition, hands-on concepts for integrating AI skills into the PHOSITA standard and similar tests could be developed and data pools for training IP office AI systems could be established, including data-sharing between offices/jurisdictions and the usability of other government agencies’ data. In its network of IP office representatives, the AI/IP Research Project has detected much interest in these topics and enthusiasm to pursue them cooperatively. The Project aims at becoming a catalyst for such cooperation.

The Zurich AI/IP Group fully recognizes that the interplay between AI and IP involves many further aspects. At this stage, the Policy and Research Recommendations cannot specifically address all of them. This section presents a – very much non-exhaustive – list of additional AI/IP topics, which may also become a focus of the Group’s future work.

Patterns of AI innovativeness and creativeness How do AI systems actually go about innovating and creating, both in the field of technical inventions and in areas such as “generative art”, today and in the foreseeable future? This topic is highly interdisciplinary, likely even driven by non-legal, technical/IT disciplines.

Liability regime for IPR/data law infringements by AI systems For instance, the ramifications of the black-box nature of AI systems; ways to increase predictability of use of IPR-protected content by AI systems; ways to build IP law compliance into AI systems; consequences of AI systems processing data the use of which is (partially) unlawful, e.g. lack of a basis for the lawfulness of processing; partial switch to a liability rule regime instead of injunctions; parameters for allocating liability to be in sync with entitlement allocation rules; and the need for mandatory precautions (insurance, reserves, etc.) by small providers of AI systems.

Consistency of the broader legal framework for AI Lawmakers around the globe are working on solutions to address the challenges caused by the use of AI systems in general, beyond the aspect of AI and IP. Important proposals, such as the EU Commission’s draft AI Act, do not specifically address IP issues. AI-related changes to the IP system must aim at consistency with general AI regulation and potential sector-specific AI regulations. Documentation, notification, and disclosure obligations on AI system users present an example for an area where AI/IP considerations and general AI regulation may overlap.

Both institution and Office anonymized for the purposes of this submission.

We are fully aware that there are important differences between the systems we lump together under the term “artificial intelligence” and that there is an ongoing debate on how the term can be defined from the perspective of the law. We thank the reader for bearing with the generalizations made in this Project, permitting a more concise Recommendations document.

See , for instance, European Commission’s High-Level Expert Group on AI (2018); OECD High-Level General Definition of AI Systems, https://oecd.ai/en/wonk/a-first-look-at-the-oecds-framework-for-the-classification-of-ai-systems-for-policymakers ; Chen et al. ( 2017 ); Krafft et al. ( 2020 ), p. 73 et seq .; Schuett ( 2021 ), p. 3 et seq .; Ongsulee ( 2017 ); Van Roy et al. ( 2019 ), p. 5 et seq .; Klinger et al. ( 2018 ), p. 4. Insights on the state of AI/IP affairs gained so far by the Project are canvassed, in greater detail, in Picht et al. ( 2023 ).

So far, the AI/IP discussion shows a certain, understandable focus on patent law. However, a conceptual, holistic policy project on AI/IP, such as the Project described here, must not overlook the important issues and developments in other areas of IP law, especially copyright and trade secrets law.

To the extent these workshops were conducted online, recordings are available at https://www.cipco.uzh.ch/de/veranstaltungen/IP-KI (all web sources last accessed 16 February 2023).

For an account of important findings thus gained, see Picht et al. ( 2023 ).

In particular Abraham Bernstein (University of Zurich), Alberto Russo (EUIPO), Alessandro Curioni (IBM), Alexander Klenner-Bajaja (EPO), Alicia Daly (WIPO), Anaic Cordoba (Swiss IPI), Angel Aledo Lopez (EPO), Beat Weibel (Siemens), Begonia Gonzalez Otero (Max Planck Institute for Innovation and Competition), representatives of the Intellectual Property Office of Singapore, Craig MacMillan (Canadian IPO), Daryl Lim (Penn State University), Emily Miceli (UKIPO), Felix Addor (Swiss IPI), Fernando Peregrino Torregrosa (EUIPO), Gaetan de Rassenfosse (EPFL), Hansueli Stamm (Swiss IPI), Heli Pihlajamaa (EPO), Ian Grimstead (UKIPO), Joseph Walton (UKIPO), Juan Bernabe-Moreno (IBM), Kate Gaudry (Kilpatrick Townsend), Martin Bader (University of St Gallen), Michael May (Siemens), Michael Schröder (ERNI AG), Naomi Häfner (University of St Gallen), Nicki Curtis (UKIPO), Peter R. Thomsen (Novartis), Pierre Olivier (UKIPO), Ryan Abbott (University of Surrey, DABUS Project), Sabrina Konrad (Swiss IPI), Samir Ghamir-Doudane (INPI), Sita Mazumder (Lucerne University of Applied Sciences and Arts), Ulrike Till (WIPO) and Yann Ménière (EPO, MINES ParisTech).

Person having ordinary skills in the art (“ Durchschnittsfachmann ”).

See , for instance, Bonadio et al. ( 2021 ), pp. 48–66; Konertz and Schönhof ( 2018 ), pp. 379–412; Shemtov ( 2019 ).

For an overview of the litigation and discussion, see Picht, Brunner and Schmid ( 2023 ); for continuous updates on the DABUS applications and litigations, see also https://artificialinventor.com/patent-applications/ .

Boards of Appeal of the European Patent Office, J 0008/20 – 3.1.01 and J 0009/20 – 3.1.01, 4.3.7; Federal Patent Court, 11 W (pat) 5/21, II.2.c.

Abbott ( 2016 ), pp. 1079, 1125; Ménière and Pihlajamaa ( 2019 ), p. 334; Bonadio et al. ( 2021 ), p. 54; Fabris ( 2020 ), p. 691 et seq .; Fraser ( 2016 ), p. 321; Käde ( 2021 ), p. 558; Lim ( 2018 ), p. 863; sceptical regarding an impact of AI on the PHOSITA tests, Burk ( 2021 ), p. 308 and Simon ( 2013 ), p. 377.

ECJ decision of 13 November 2018, Levola Hengelo BV/Smilde Foods BV , C-310/17, para. 37; ECJ decision of 4 October 2011, Football Association Premier League , C-403/08 and C-429/08, para. 159; ECJ decision of 16 July 2009, Infopaq International , C-5/08, para. 39.

Senftleben and Buijtelaar ( 2020 ), p. 7; de Cock Buning ( 2016 ), p. 314; Bullinger ( 2022 ), para. 15; Loewenheim and Pfeifer ( 2020 ), para. 2  et seq .

Egloff ( 2020 ), para. 2; Hug ( 2012 ), para. 3  et seq .

Swiss Federal Supreme Court, BGE 142 III 387, para. 3.1.; von Büren and Meer ( 2014 ), para. 178.

For European law, see : Sec. 7 of the German Copyright Act; Art. L111-1 of the French Intellectual Property Code (IPC); Sec. 10(1) of the Austrian Copyright Act. For Swiss law: Art. 6 Copyright Act.

For European law, see : Sec. 13 of the German Copyright Act; Art. L121-1 of the French Intellectual Property Code (IPC); Sec. 20(1) of the Austrian Copyright Act; Art. 8 of the Italian Copyright Statute. For Swiss law: Art. 9 Copyright Act.

For European law, see : Sec. 12(1) of the German Copyright Act; Art. L121-2 of the French Intellectual Property Code (IPC); Art. 12 of the Italian Copyright Statute. For Swiss law: Art. 9(2) Copyright Act.

For European law, see : Art. L121-1 of the French Intellectual Property Code (IPC); Sec. 21(1) of the Austrian Copyright Act; see also Sec. 23 of the German Copyright Act; Art. 18 of the Italian Copyright Statute. For Swiss law: Art. 11(1) Copyright Act.

For European law, see : Sec. 14 of the German Copyright Act; Art. L121-1 of the French Intellectual Property Code (IPC); Sec. 21(3) of the Austrian Copyright Act; Art. 25 of the Italian Copyright Statute. For Swiss law: Art. 11(2) Copyright Act.

Art. 7(1) Berne Convention for the Protection of Literary and Artistic Works (as amended on 28 September 1979).

E.g ., UK ( cf . Sec. 9(3), Sec. 12(7) and the definition of “computer-generated” in Sec. 178 CDPA, although some exceptions apply, cf . Sec. 79(2)(c) and Sec. 81(2) CDPA); Ireland ( cf . Sec. 21(f), Sec. 30, and the definition of “computer-generated” in Sec. 2(1) of the Copyright and Related Works Act); Hong Kong ( cf . Sec. 11(3), Sec. 17(6) and the definition of “computer-generated” in Sec. 198 of the Copyright Ordinance, although some exceptions apply, cf . Sec. 91(2)(c) and Sec. 93(2) of the Copyright Ordinance).

Note that this may be different if AI systems are used to produce inventions. Cf . Senftleben and Buijtelaar ( 2020 ), pp. 18–20, 23, who recommend to instead adopt a neighbouring rights approach.

Cf . Sec. 4(3) of the German Unfair Competition Act; Sec. 1(1)(1) of the Austrian Unfair Competition Act; regarding Scandinavian countries, Viken Monica (2020), passim .

Senftleben and Buijtelaar ( 2020 ), passim ; Dornis ( 2020 ), p. 44 et seq .

See Sect. 3.2.2 .

Staehelin ( 2006 ), p. 18 et seq .; Andermatt ( 2008 ), p. 285; Fabian ( 2019 ), p. 283 et seq .

See , for Germany, BGH, Ia ZR 110/64 – Spanplatten ; BGH, X ZR 54/67 – Wildverbissverhinderung ; Busse and Keukenschrijver ( 2016 ), Sec. 6, note 17 et seq .; Mellulis ( 2015 ), Sec. 6, note 35; on German patent law before 1936, which allowed for corporate patents, Schmidt ( 2009 ), p. 234 et seq . For Switzerland, Botschaft , BBl 1967 II, p. 364; BGer 4A_78/2014; BPatGer O2012_001; Brehmi ( 2012 ), Art. 3, note 5 et seq .; Zuberbühler ( 2012 ). For the UK, Rhone-Poulenc Rorer International Holdings Inc v. Yeda Research & Development Co Ltd [2007] UKHL 43. For the US, Murphy ( 2012 ).

Cf ., for instance, BGH, GRUR 1966, 558, 559 et seq .

Against corporate patent ownership in AI settings, Ann ( 2022 ), Sec. 1, note 25 et seq .; Sec. 19, notes 17–35.

Senftleben and Buijtelaar ( 2020 ), pp. 3, 19; Ramalho ( 2017 ), p. 16; Papastefanou ( 2020 ), p. 295; Lauber-Rönsberg and Hetmank ( 2019 ), p. 647. For parallel reflections in patent law, see Konertz and Schönhof ( 2018 ), p. 411; AIPPI German Delegation 2019, https://aippi.soutron.net/Portal/Default/en-GB/RecordView/Index/254 , p. 18 et seq .

Abbott ( 2016 ), pp. 1079, 1125; Lim ( 2018 ), p. 863 et seq .; dissenting view, Bonadio et al. ( 2021 ), p. 66, advocating a different regime for AI-generated inventions and human inventions, rather than denying AI-generated inventions patent protection altogether.

In general on them, Heller ( 2013 ).

See , for instance, Derclaye and Husovec ( 2022 ), pp. 3–5; EU Commission Staff Working Document, Evaluation of Directive 96/9/EC on the legal protection of databases of 25 April 2018, p. 46; Hoeren ( 2016 ), p. 787.

Hoeren ( 2016 ), p. 790  et seq ., with further references.

Broughton Micova et al. ( 2019 ), p. 242; Geiger et al. ( 2017 ), p. 209  et seq .; Hugenholtz and Quintais ( 2019 ), p. 1010  et seq .

See , for instance, Merges ( 1994 ).

Cf . Sect. 3.3.3 .

“Personal data means any information relating to an identified or identifiable natural person (‘data subject’); an identifiable natural person is one who can be identified, directly or indirectly, in particular by reference to an identifier such as a name, an identification number, location data, an online identifier or to one or more factors specific to the physical, physiological, genetic, mental, economic, cultural or social identity of that natural person” (Art. 4(1) GDPR).

Cf . also Picht et al. ( 2023 ).

In recent case law, the ECJ may have (unintentionally) opened a backdoor to research use of databases by stating that “the main criterion for balancing the legitimate interests at stake must be the potential risk to the substantial investment of the maker of the database concerned, namely the risk that that investment may not be redeemed” (ECJ decision of 3 June 2021, CV-Online Latvia v. Melons , C-762/19, para. 44). According to the Court, the sui generis right in databases is only infringed in case of “a risk to the possibility of redeeming that investment through the normal operation of the database in question” (para. 47, emphasis added), which could be interpreted as a research exemption.

Namely, Art. 5(1)(b) GDPR and Art. 89 GDPR.

Cf ., for instance, the Compas system used in the US to generate predictions about recidivism risks of a person accused of a crime, which was found to predict higher risks for black defendants (Liptak ( 2017 )). In the Netherlands, a court halted the use of an automated system to find welfare fraud, finding that the system disproportionately targeted poorer people (Henley and Booth ( 2020 )).

In fact, neither the provisions nor the recitals of the more recent regulations, such as the GDPR and the DSM Directive, even mention AI.

Arts. 3 and 4 Directive (EU) 2019/790 of the European Parliament and of the Council of 17 April 2019 on copyright and related rights in the Digital Single Market and amending Directives 96/9/EC and 2001/29/EC.

Geiger, Frosio and Bulayenko ( 2018 ), p. 10.

See Sect. 3.3.4.2 .

Art. 5(1)(b) GDPR and Art. 89 GDPR.

See , for instance, Art. 4 WIPO Copyright Treaty; Art. 1 Directive 2009/24/EC of the European Parliament and of the Council of 23 April 2009 on the legal protection of computer programs (EU Software Directive); Sec. 2(1)(1) German Copyright Act; Sec. 3(1)(b) UK Copyright, Designs and Patents Act; Art. 2(3) Swiss Copyright Act.

E.g . Art. 6 Directive 2009/24/EC of the European Parliament and of the Council of 23 April 2009 on the legal protection of computer programs (EU Software Directive); Sec. 69e German Copyright Act; Art. L122-6-1 (IV) French Intellectual Property Code (IPC); Sec. 50B UK Copyright, Designs and Patents Act; Art. 21 Swiss Copyright Act.

E.g . Art. 29(2)(a) Swiss Copyright Act.

US Supreme Court decision of 3 March 1981, Diamond v. Diehr , 450 U.S. 175 (1981).

Cf . in detail, D ragoni ( 2021 ).

On the concept and requirements, see EPO Examination Guidelines, Sec. G-II, 3.3 et seq ., G-VII, 5.4.

US Supreme Court decision of 19 June 2014, Alice Corp. v. CLS Bank International , 573 U.S. 208 (2014).

For example: ongoing proceedings regarding Apple Pay by the European Commission (EC press release of 2 May 2022, Antitrust: Commission sends Statement of Objections to Apple over practices regarding Apple Pay, https://ec.europa.eu/commission/presscorner/detail/en/ip_22_2764 (accessed 20 September 2022)); proceedings regarding Google’s search engine by the European Commission between 2010 and 2017 (EC press release of 27 June 2017, Antitrust: Commission fines Google €2.42 billion for abusing dominance as search engine by giving illegal advantage to own comparison shopping service – Factsheet, https://ec.europa.eu/commission/presscorner/detail/en/MEMO_17_1785 (accessed 20 September 2022)); proceedings regarding Microsoft’s Internet Explorer by the European Commission between 2007 and 2013 (BBC News, Microsoft fined by European Commission over web browser, 6 March 2013, https://www.bbc.com/news/technology-21684329 ); United States of America v. Microsoft Corporation , with subsequent settlement between Microsoft and the DOJ in late 2001 (implications discussed by Weinstein ( 2002 )).

On the unavailability of copyright protection for AI-generated works, see Sect. 3.1.2 .

Konertz and Schönhof ( 2018 ), pp. 379, 412; Hugenholtz and Quintais ( 2019 ), pp. 1190, 1208.

On examples, such as the works made for hire doctrine (not AI-specific) or the UK and Irish legislation on ownership of AI-generated works (AI-specific), see Picht, Brunner and Schmid ( 2023 ).

Cf . for instance, on co-authorship of groups of choice-makers, Hugenholtz and Quintais ( 2019 ), pp. 1190, 1208 et seq .; AIPPI German Delegation, pp. 7, 12.

Cf . Hugenholtz and Quintais ( 2019 ), pp. 1190, 1209.

See , for instance, Rassenfosse et al. ( 2023 ).

For some initial research on this, see Picht et al. ( 2023 ). See further Furman and Seamans ( 2018 ).

For an analysis of the fundamental flaws of current European data protection laws and potential ways forward, see Thouvenin ( 2023 ); Thouvenin ( 2021 ); Thouvenin ( 2019 ).

Art. 5(1)(c) GDPR.

Art. 5(1)(b) GDPR.

Art. 6(1)(a) GDPR.

Art. 6(1)(f) GDPR.

Art. 6(1)(b) GDPR.

Art. 6(1)(c) GDPR.

Directive 2019/1024 of the European Parliament and of the Council of 20 June 2019 on open data and the re-use of public sector information.

Cf . Proposal for a Regulation of the European Parliament and of the Council on European data governance (Data Governance Act) of 25 November 2020.

Cf . Proposal for a Regulation of the European Parliament and of the Council on harmonised rules on fair access to and use of data (Data Act) of 23 February 2022.

Cf . Proposal for a Regulation of the European Parliament and of the Council on contestable and fair markets in the digital sector (Digital Markets Act) of 15 December 2020.

For an overview, see Picht et al. ( 2023 ).

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Florent Thouvenin is Chair for Information and Communications Law, University of Zurich, Switzerland; Chair of the Executive Board of the Center for Information Technology, Society, and Law (ITSL), Zurich, Switzerland; Director of the Digital Society Initiative (DSI), University of Zurich, Switzerland.

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Picht, P.G., Thouvenin, F. AI and IP: Theory to Policy and Back Again – Policy and Research Recommendations at the Intersection of Artificial Intelligence and Intellectual Property. IIC 54 , 916–940 (2023). https://doi.org/10.1007/s40319-023-01344-5

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Copyright Dissertation Topics

Copyright Dissertation Topics – Copyright law is a dynamic field that plays a vital role in protecting intellectual property rights. For students pursuing a dissertation in copyright law or related disciplines, selecting an engaging and relevant topic is crucial. This article presents 20 copyright dissertation topics that can serve as a starting point for in-depth research. These topics cover various aspects of copyright law, including international perspectives, emerging technologies, and societal impacts. Each topic offers an opportunity to contribute to the existing body of knowledge in this field and address contemporary issues in copyright law.

Sure! Here are 20 Copyright dissertation topics:

• The Impact of Digital Piracy on the Music Industry: A Comparative Study of Legal Measures and their Effectiveness.
• Copyright and Artificial Intelligence: Challenges and Opportunities in the Age of Machine Learning.
• Copyright Protection for Virtual Reality Content: Balancing Creativity and Consumer Access.
• The Role of Fair Use in Copyright Law: An Analysis of Recent Legal Cases and Implications for Creative Industries.
• Copyright Infringement in the Digital Age: Evaluating the Effectiveness of Digital Rights Management (DRM) Technologies.
• The Copyright Implications of 3D Printing: Examining the Balance between Innovation and Protection.
• The Role of Copyright in Protecting Traditional Cultural Expressions: A Comparative Study.
• Copyright and Educational Institutions: Analyzing the Challenges and Opportunities for Digital Learning.
• Copyright and User-Generated Content: Balancing the Rights of Creators and Consumers in Online Platforms.
• Copyright and Artificial Intelligence Music Composition: Evaluating the Legal and Ethical Dimensions.
• Copyright and Open Access: Exploring the Impacts of Open Licensing Models on Scholarly Communication.
• Copyright and Social Media: Analyzing the Legal Issues Surrounding the Use of Copyrighted Content on Platforms like Instagram and YouTube.
• Copyright Infringement in the Film Industry: Investigating the Role of Digital Streaming Platforms.
• Copyright and Cultural Heritage Institutions: Examining the Challenges and Solutions in Digitizing and Preserving Copyrighted Works.
• Copyright and Video Game Development: Analyzing the Legal Framework for Protecting Game Elements.
• Copyright and Text and Data Mining: Assessing the Legal Implications for Researchers and Data Analysts.
• Copyright and the Publishing Industry: Examining the Impact of E-books and Self-Publishing on Copyright Law.
• Copyright and the Film Industry: Investigating the Legal Challenges in the Production and Distribution of Films.
• Copyright and Artificial Intelligence Image Recognition: Evaluating the Copyright Implications for Image Databases.
• Copyright and Streaming Services: Analyzing the Legal and Economic Aspects of Licensing Content for Online Platforms.

Remember to choose a topic that aligns with your interests and the availability of research materials. Good luck with your dissertation!

Conclusion:

These 20 copyright dissertation topics offer diverse avenues for exploring contemporary issues in copyright law. By addressing challenges posed by digital technologies, artificial intelligence, cultural heritage preservation, fair use in new media, and open access publishing, these topics contribute to the understanding and development of copyright law in an ever-changing landscape. Researchers can choose a topic that aligns with their interests and embark on an in-depth analysis of the chosen area, shedding light on the complexities and potential solutions within copyright law.

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LLM Intellectual Property Rights

LL.M. (Intellectual Property Rights) Objectives " Knowledge is Power " – the adage is more relevant today than at any other time in the past; and it will be still more relevant in the years to come as we move more and more towards knowledge-based economy. It is but natural that in this new scenario, Intellectual Property Rights should occupy the central stage in the economic development. A renewed awakening of the role of intellectual property in the countries of the various regions of the world has led more recently to the adoption or revision of national legislation on Intellectual Property Rights (IPR) as well as to the establishment or modernization of Government structures that administer such legislation. The changing legal regime of IPR has become one of the crucial issues in the contemporary relations among nations. Central to such a concern has been the level of protection sought/contested on the rights at international and transnational level. The issues of IPR have acquired compelling width in the wake of IPRs agreement, with the WTO at its centre and monitored by WIPO. The New IPR regime that has come into being seems to have a vital linkage with the revolution in New Generic Technologies (NGT), Information and Communication Technology (ICT) and Biotechnology in particular. The present program has been designed keeping in view the above opportunities and challenges to give in-depth knowledge of IPR to the students pursuing LL.M. two year program. A part from the IPR the course has also taken care of the basic fundamentals of Law other than IPR to understand the legal system and its administration not only at the national but also international level. To make the LL.M. program research oriented entire Semester IV has been devoted to towards practical oriented understanding of Law in general and IPR Law in particular. The present program will cater the needs of the various stack holders of IPR such as Lawyers, Judges and Industry.

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The Supreme Court of India (the Supreme Court) not only declares law while answering the question(s) before it but also declares, and makes and unmakes law. The question(s) of law or fact, or mixed question of law and fact, answered by the Supreme Court becomes binding by virtue of Article 141 of the Constitution of India. By answering such questions, the Court also irons out the creases of law by interpreting-constructing the statutory texts. This article covers the reportable intellectual property (IP) decisions of the Supreme Court delivered in the year 2023. The reportable decisions of the Supreme Court have been taken from Judgement Information System (JUDIS) and Supreme Court Cases.

Journal of Intellectual Property Rights

This Paper seeks to review the articles published in the Journal of Intellectual Property Rights (hereinafter, JIPR) in the third decade of the twenty-first century from Volume 25 (1) (2020) to Volume 28 (5) (2023). In this decade, five new series on different themes of intellectual property rights (hereinafter, IPRs) were started by JIPR which include ‘IP & Taxation Policy’, ‘Theoretical Underpinnings of IP Laws’, ‘Standard Essential Patents’, ‘IP Laws Declared by the Supreme Court’, and ‘JIPR in IPR Research’. In this decade, a total of 139 articles were published covering different areas of IPRs. The articles published in this decade constitute 14.52 (point five two) percent of the total articles published in JIPR till Volume 28 (5) (2023). In terms of percentage of the articles published in each decade, this decade with 14.52 (point five two) percent comes fourth after the decades 2010–2014 with 26.22 percent, 2005–2009 with 22.98 percent, and 2015–2019 with 15.04 percent. This is the sixth paper on the theme ‘JIPR in IPR Research’ and proceeds with the same argument and method as developed and adopted in the First Paper and the sequel papers published under the theme.

Abhirup Chakraborty

A series of short notes on "Intellectual Property Rights & Laws" which is useful for any competitive exam on IPR. A set of five notes are there, out of which this one is the third note.

A series of short notes on "Intellectual Property Rights & Laws" which is useful for any competitive exam on IPR. A set of five notes are there, out of which this one is the first note.

Walter Scholger

Oliviero Magagnini

The object of this thesis is legal; it deals with law, with two sets of laws in particular. And law has always evolved over time, trying to adapt to the changing circumstances of society. The tension between competition and intellectual property (IP) law is definitely not the oldest example, but it is a good one. Concepts such as economic efficiency have developed since the beginning of the 20th century, and competition and IP law— and thus their ongoing conflict— have been influenced by scientific and social changes.

This paper seeks to review the articles published in the Journal of Intellectual Property Rights (JIPR) in the last decade of the twentieth century from Volume 1(1) (1996) to Volume 4(6) (1999). There are seven intellectual property (IP) statutes in force in India. When JIPR published its first Volume in the year 1996, only two IP statutes, legislated and enacted in post-independent India, were in force, namely: (i) The Copyright Act, 1957; and (ii) The Patents Act, 1970 — enacted after 10 years and 23 years respectively after the independence of the country. Nevertheless, the Imperial Act on designs was also in force by the virtue of Article 372 of the Constitution of India, until the Indian Parliament enacted a separate statute on designs. Two statutes were enacted in 1999 and the other three statutes were enacted in the first decade of the 21st century but some of them took a time of almost a decade to come into force. For convenience, the papers published in JIPR have been reviewed year-wise. Paper attempts to identify the: (i) total number of issues published; (ii) total number of articles published; (iii) total number of contributions made by the Indian and foreign scholars; (iv) total number of sole and joint publications; (v) publishing style of JIPR; and (vi) area of IP covered in the publications. JIPR since its inception has aimed to fill void in the IP literature in general and the Indian IP literature in particular. Paper develops an argument that JIPR has significantly contributed in the dissemination of IP information and knowledge, and also in creating IP knowledge and awareness by publishing quality research articles on an open access platform.

Sakshi poddar

Rita Matulionyte

The report compares applicable law rules to intellectual property (IP) disputes as proposed in the recent international projects (ALI, CLIP, Transparency, Kopila and Joint Japanese-Korean proposals). Namely, it identifies the differences among proposals, reveals the underlying reasons of differing rules, looks at how particular issues have been until now solved at international and national levels, and finally, overviews the main arguments for and against particular solutions suggested in the proposals. This report was presented in the 1st meeting of the Committee on Intellectual Property and Private International Law of the International Law Association (15-17 March 2012, Lisbon) and is expected to contribute to the merge of current international proposals into a single international initiative.

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