What happens when artists, lawyers, technologists, and academics sit down to talk about artificial intelligence? On 23rd May 2025, we found out.
The hybrid workshop I organised—Bridging the Knowledge Gap: Exchange and Transfer in the Creative Industry—was funded by the internal University pump priming fund and hosted at Coventry University. It brought together a multidisciplinary mix of voices to explore how AI is reshaping creative industries, and what that means for law, ethics, and artistic practice.
This wasn’t just another AI event. It was a space for nuance, for disagreement, and for asking difficult questions. The kind that don’t have easy answers.
Who’s in the room matters
Participants included academics, students, industry professionals, and legal experts. Some were deeply embedded in AI development; others were navigating its implications for copyright, patent, data governance, or creative expression. The diversity of perspectives was intentional. If we’re going to talk about knowledge exchange, we need to be clear about whose knowledge we’re exchanging—and why.
The workshop unfolded across three thematic sessions, each designed to surface tensions and opportunities at the intersection of AI and creativity.
Session 1: AI and creative work
Led by Professor Eleonora Belfiore (Theme Lead on Space, Place and the Creative Economy at the Centre for Creative Economies in Coventry University), this session asked: what does creativity look like when machines are part of the process?
Dr. Xin Chen (Associate Professor of Computer Science at the University of Nottingham) in his presentation Demystifying AI: How Machines Learn, Create, and Influence demystified large language models (LLMs), explaining how systems like ChatGPT process data, undergo training, and are deployed in real-world applications. He demonstrated how different AI models can produce varied responses to the same prompt, highlighting the importance of data quality and the influence of engineers during the training process. His examples were practical, but the implications were philosophical. What happens when bias or opacity creeps into the machine’s output?
Mrs. Petra Molnar (Founder of AI Cinelab) followed with her presentation Empowering Creativity through AI: Bridging Gaps and Redefining Access. She showcased tools like Freepik, ElevenLabs, and CapCut—platforms that democratise creative production. But she also raised concerns: are we trading originality for accessibility? And what does “authorship” mean in an AI-assisted world? Her presentation sparked a lively discussion on how AI can be adopted ethically and inclusively, ensuring that creativity remains a human-centred endeavour.
Mx. Kayla-Megan Burns (Founder of Podplistic) concluded the session by exploring the dual futures that lie ahead for the creative industry in the face of AI. In Burns’ presentation AI in Music: Navigating the Crossroads of Creation and Exploitation, the future of creativity, they argued, depends on the policy decisions we make today. Regulation isn’t just a technical issue—it’s a cultural one.
Session 2: Legal frameworks and AI data governance
This session, which I chaired, turned the spotlight on law and regulation.
Dr. Luke McDonagh (Associate Professor of Law at the London School of Economics and Political Science) explored the feasibility of transferring technology through copyright and trade secrets in his presentation Training Data, Technology Transfer, Trade Secrets and AI. His analysis was clear: innovation and protection are in tension, and the law is still catching up.
Professor Enrico Bonadio from City, University of London dissected the UK government’s proposal to expand the Text and Data Mining (TDM) exception in his presentation The UK Government's Proposal on a New AI-Focused Text and Data Mining Exception. The idea? Allow AI developers to mine lawfully accessed works, unless rights holders opt out. The backlash? Creators worry they’ll lose control over how their work is used. The opt-out system, Bonadio noted, may be more symbolic than practical.
Session 3: Intellectual property strategies in the AI era
Led by Dr. Nadia Naim (Associate Dean for International – Law and Social Sciences at Aston University), this session tackled the legal nuts and bolts of protecting AI-related innovations.
Patent attorneys Dr. Tim Gilbert and Michael Loadman (Swindell & Pearson Ltd) walked us through the risks and opportunities in their presentations Protecting Intellectual Property Related to AI and Large Language Models: Risks and IP Issues. From data leakage to institutional IP policies, their message was clear: legal strategy must evolve alongside technology.
Reflections: Beyond the black box
Special guests Professor James Brusey (Professor of Computer Science at Coventry University and newly appointed Innovate UK Bridge AI Independent Scientific Advisor at The Alan Turing Institute) and Mr. Andrea Sarnataro (Senior AI Creative & Art Director) shared valuable insights on the future of AI in creative industries. Their insights underscored a recurring theme: interdisciplinary collaboration isn’t optional—it’s essential.
Throughout the day, participants wrestled with questions that resist simple answers:
- How can creative professionals be supported in using AI to augment their work rather than compete with it?
- What legal training and skills are needed to protect original works in the AI era?
- What policy frameworks should governments adopt to guide ethical AI development?
- How should laws evolve to address the challenges posed by frontier technologies?
These aren’t just academic questions. They’re practical, political, and deeply human.
Final thought
AI may be the ultimate black box, but knowledge exchange doesn’t have to be. By creating spaces for dialogue—across disciplines, professions, and perspectives—we can begin to bridge the gaps that matter most.
