Protecting Privacy in an AI Era
Privacy scholar Daniel Solove argues in the Wall Street Journal that individual consent and data control are inadequate frameworks for regulating privacy in the AI era. He calls instead for structural accountability measures — including data minimization requirements, fiduciary duties, and liability for harmful algorithmic design — modeled on how regulators oversee food and drug companies.
Why this matters: The notice-and-consent model puts the burden on you. Read the terms, click accept, live with the consequences. Solove's argument is that this was always a fiction, and AI makes it a worse one. You cannot meaningfully consent to how a model trained on your data might affect you years from now. The food and drug comparison is useful: we do not ask people to evaluate drug safety themselves. We hold manufacturers liable and make them prove products are safe before release. That same logic applied to AI would mean companies bear the cost of harm, not the people caught in it.
Who should care: AI governance · Lawyers · Administrators · Compliance · General readers · Policy · Privacy officers
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