Current privacy consent mechanisms often let users down: cookie banners violate informed consent requirements, privacy policies are still difficult to understand, and transparency alone does not guarantee the protection of personal data. In other words, privacy controls are often not user-friendly, let alone felt as mechanisms for empowerment. As AI processes more and more personal data and plays an increasingly important role in society, these challenges are becoming more acute. Emerging systems based on large-scale data and machine learning complicate the boundaries of user control and consent; invisible inferences, decisions delegated to AI agents, and opaque personalisation create new challenges. While prior HCI research has examined the usability of consent and explored ways to improve it, the community still lacks a systematic exploration of consent in the age of AI. Therefore, this workshop brings together experts from AI, HCI, privacy, social sciences, policy, and law fields, to imagine how consent and control must evolve beyond ``scroll-and-click'' towards richer, contextual, and adaptive mechanisms reflecting human capabilities and values. It re-imagines consent and user control in the AI era, distinguishing between explicit decisions and the broader ways in which people can influence how their data is used. Using the Futures Design Toolkit~fuel4design₂021, participants will develop future personas and create design provocations through prototyping. We are seeking position papers that address: novel consent mechanisms, the privacy impact of AI, privacy decision delegation models, and new interaction modalities for user consent and control. We will produce design artefacts and research directions for privacy control tools that are more effective, usable, and accessible than existing mechanisms.
Seymour et al. (Mon,) studied this question.