In this webinar, we bring together experts and practitioners to explore a more responsible data model for AI chatbots. We’ll consider early evidence from platform interventions and what information is needed to inform effective oversight and design.
Drawing on lessons from the social media era, our panellists will discuss how mechanisms for transparency, data portability, and researcher access could be built into consumer chatbots from the start, rather than retrofitted after the damage is done.
As conversational AI systems are increasingly incorporated into more of our interactions on the Web, we have an opportunity to ask whether chatbots must follow the same path as past platforms – or whether deliberate choices about data architectures, data ethics and user rights could set a different precedent from the outset.
The harms we have witnessed as a result of social media platforms did not arise solely from the technologies themselves. Rather, these platforms were shaped by intentional design decisions, data practices, and a lack of transparency that left users, researchers, and regulators largely in the dark.
Chair: Dr June Brawner, Head of Research, the ODI