Christian Mammen, Managing Partner of Womble Bond Dickinson’s San Francisco office and Co-Founder of the firm’s Artificial Intelligence Practice, co-authored a new white paper, “Creativity, Artificial Intelligence, and the Requirement of Human Authors and Inventors in Copyright and Patent Law.” The white paper examines the nature and uniqueness of human creativity amid an emerging debate over whether IP laws must be updated to accommodate AI-generated outputs. It is available for download here.
Mammen, who was an Academic Visitor with the Oxford Faculty of Law and temporary fellow at University College, Oxford, during a sabbatical from the firm, convened a multidisciplinary group of professors and postgraduates to study a series of interrelated questions about AI, the creative process, and IP law’s requirements that authors and inventors be humans. Mammen is the lead author of the white paper, which was co-authored by Michael Collyer, Ron Dolin, Dev Gangjee, Tom Melham, Maggie Mustaklem, Pireeni Sundaralingam, and Vincent Wang-Maścianica. Additional information about them can be found at the end of this release.
The paper takes a multidisciplinary approach to the concept of creativity and argues that it includes external, subjective, and social context factors. Relatedly, the paper also examines IP law’s fundamental rationale: there is something special and important about human creativity. The authors consider how arguments for the IP protection of AI-generated artifacts do not fully address these creativity requirements. The paper primarily references U.S. law, with additional examples from the U.K. and EU.
“As the lines between human creative output and generative artificial intelligence blur, we are at a pivotal crossroads for intellectual property that question some of the law’s most essential assumptions,” said Mammen. “I’m grateful to have worked alongside such an impressive and cross-disciplinary group of intellectuals as we tackle these exciting questions and probe the nature of creativity itself.”
“As the lines between human creative output and generative artificial intelligence blur, we are at a pivotal crossroads for intellectual property that question some of the law’s most essential assumptions. I’m grateful to have worked alongside such an impressive and cross-disciplinary group of intellectuals as we tackle these exciting questions and probe the nature of creativity itself.”
After graduating from Cornell Law School, Mammen earned a doctorate in law from the University of Oxford. His D.Phil. dissertation was published in book form in 2002 with the title, “Using Legislative History in American Statutory Interpretation.” A recognized thought leader on IP issues, he has held visiting faculty positions at UC Law San Francisco (formerly UC Hastings College of the Law), UC Berkeley Law School, Stanford Law School, and the University of Oxford.
About the Co-Authors
Michael Collyer is a doctoral candidate at the University of Oxford and co-founder of the Oxford AI Network and Founders & Funders Foundation. He holds a bachelor’s in politics, psychology, law, and economics from the University of Amsterdam and a master’s in social science of the internet from the University of Oxford.
Dr. Ron Dolin has degrees in math, physics, law, and computer science and is a licensed attorney in California. He has taught about legal informatics at Stanford, Notre Dame, and Harvard law schools and is co-editor and co-author of the textbook Legal Informatics (Cambridge University Press, 2021).
Dr. Dev Gangjee is a professor of IP law at the Oxford Law Faculty. His research presently focuses on the adoption of machine learning technologies by Intellectual Property Offices around the world. He is also working on the legal regulation of data, which fuels machine learning.
Dr. Tom Melham FRSE FBCS CEng is a professor of computer science at the University of Oxford and a fellow of Balliol College. Melham’s research is focused on mathematical methods for assuring the quality and correctness of digital hardware and software systems. Alongside this, his research interests include AI and technology in legal services and the justice system, as well as testing and evaluating AI-based systems. He also works in computer-aided dispute resolution and was the lead technical co-author of a landmark LawtechUK study on online dispute resolution for SMEs. Melham serves on the Board of Trustees of the Alan Turing Institute, the UK’s national institute for AI and data science. He is a chartered engineer and a Fellow of the British Computer Society and the Royal Society of Edinburgh.
Maggie Mustaklem is a design lead and doctoral researcher focusing on the implications of AI in design. Her research project, Design Interrupted, centers on the “everyday AI” in platforms like Pinterest and Instagram (increasingly generative tools) designers and architects use to search for inspiration. She is interested in how these tools may be flattening what designers see for inspiration, influencing what they ultimately produce. Mustaklem holds a master’s in history of design from the Royal College of Art and Victoria & Albert Museum and a bachelor’s in psychology from the University of Michigan.
Pireeni Sundaralingam is a cognitive scientist trained at Oxford and MIT. She has held posts as Principal Advisor for Human Potential for the United Nations initiative UNLive and led research at Silicon Valley’s Center for Humane Technology. Her consulting firm, Neuro-Resilience Consulting, specializes in optimizing conditions for human innovation and decision-making. Sundaralingam is also an award-winning poet whose work has been translated into five languages and is currently College Poet Laureate and InterDisciplinary Catalyst at University College, University of Oxford.
Dr. Vincent Wang-Maścianica is a research scientist affiliated with the Compositional Intelligence branch of Quantinuum and the Human Centred AI Lab at St. Catherine's College, both in Oxford, where he was trained in mathematics and computer Science. Wang-Maścianica develops and works with high-level yet intuitively accessible visual reasoning languages for complex systems, including models of human cognition, natural language, and computation, both quantum and classical.