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Protecting Privacy in an AI Era

Daniel Solove argues in the Wall Street Journal (alternate link) that giving people control of their personal data is not an effective way to regulate privacy in this era. Instead, we need to hold companies accountable for their actions,…

What happened

The latest analysis post sets out a development that is directly relevant to security operators. Daniel Solove argues in the Wall Street Journal (alternate link) that giving people control of their personal data is not an effective way to regulate privacy in this era.

Why it matters

This matters because AI-related risk increasingly shows up through deployment choices, interfaces, and governance gaps rather than model headlines alone. It is a direct signal about how compliance and policy expectations are being translated into implementation work.

Assessment

The strongest signal here is not just the headline event, but the wider pattern it points to. In practice, that means operators should read this as a broader signal over noise item rather than a narrow one-off.

  • Translate the development into specific ownership, policy, and evidence requirements instead of leaving it as background policy tracking
  • Monitor follow-on reporting or primary-source updates for scope expansion, implementation guidance, or stronger enforcement signals

Further reading