<ul><li>Generative AI poses real privacy risks, eroding privacy en masse and providing tools for bad actors.</li><li>The solution involves consumers demanding transparency and government regulation.</li><li>Mitigating privacy risks requires educating the public about data privacy and AI adoption.</li><li>Generative AI can include text, audio, and video content generation using large language models.</li><li>Training stages involve pre-training, supervised instruction fine-tuning, and reinforcement learning from human feedback.</li><li>Privacy risks of generative AI include data compromise, leaked personal information, and data misuse during interactions.</li><li>AI exacerbates surveillance, identification, aggregation, and exclusion risks in privacy.</li><li>Concrete AI examples show how user interactions with generative AI systems impact data privacy.</li><li>Steps like data minimization, transparency, and user consent are proposed to mitigate generative AI privacy risks.</li><li>The clear solution involves consumers becoming aware of data value and demanding data privacy, potentially reshaping the surveillance economy.</li></ul>

Is There a Clear Solution to the Privacy Risks Posed by Generative AI?

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