Can AI Be Consentful?

This chapter examines how traditional consent frameworks fail to address generative AI systems creating content from personal data. While individuals can consent to initial data use for AI training, they cannot meaningfully consent to the vast array of potential outputs or their subsequent use and distribution. We identify three core challenges creating a "consent gap": the scope problem (inability to predict all possible outputs), the temporality problem (consent cannot cover future unknown uses), and the autonomy trap (consenting to uses that may undermine personal autonomy). These issues are problematic when AI-generated content creates new forms of personal representation beyond original consent boundaries. Current legal frameworks inadequately protect individual autonomy, identity rights, and social responsibility in AI contexts. By connecting these consent limitations to broader responsible AI principles (fairness, transparency, accountability, and autonomy), we argue for evolving ethical and legal approaches that better address generative AI’s challenges to traditional consent models.