Generative models have advanced to the point where they can produce content that is nearly indistinguishable from human-created content. As these models continue to evolve, the detection of realistic fake content, also known as deepfakes, will only become more challenging, raising significant concerns about the authenticity and trustworthiness of digital media.

To mitigate these risks, recent regulations, such as the EU’s AI Act, advocate for watermarking techniques that can reliably distinguish between synthetic and authentic content. In response, both industry and academia are actively developing watermarking methods designed to be embedded within the generation process. However, it remains unclear whether current watermarking techniques are fit for purpose and whether they meet key technical and societal requirements for a real-world deployment.

This interdisciplinary workshop aims to explore these challenges by featuring accessible contributions from researchers across computer science, law, and social sciences, as well as representatives from industry. The event will prioritize open discussions and networking opportunities.

A key goal of the workshop is to bring together researchers with interests in watermarking, with a focus on those from across the UK, to encourage future collaborations and knowledge exchange.

Confirmed speakers

Dr. Abigail See, Google DeepMind
Prof. Henry S. Thompson, University of Edinburgh
Ayesha Bhatti, Center for Data Innovation
Dr. Teddy Furon, INRIA (Online)
Prof. Mauro Barni, University of Siena
Bence Szilágyi, Garandor

Beyond Deepfakes: advancing watermarking in Generative AI