John Collomosse presents Building Safe and Fair Generative AI upon the Three Pillars of Provenance

Provenance facts, such as who made an image and how, can provide valuable
context for users to make trust decisions about visual content. Emerging
standards and provenance enhancing tools promise to play an important role in
fighting fake news and the spread of misinformation. In this talk we contrast
three provenance enhancing technologies: metadata, fingerprinting and
watermarking, and discuss how we can build upon the complementary strengths of
these three pillars to provide robust trust signals to support stories told by
real and generative images. Beyond authenticity, we describe how provenance can
also underpin new models for value creation in the age of Generative AI. In
doing so we address other risks arising with generative AI such as ensuring
training consent, and the proper attribution of credit to creatives who
contribute their work to train generative models. We show that provenance may be
combined with distributed ledger technology (DLT) to develop novel solutions for
recognizing and rewarding creative endeavour in the age of generative AI.