In an era increasingly dominated by artificial intelligence, the conventional wisdom surrounding data privacy is undergoing a critical re-evaluation. **Daniel Solove**, a prominent privacy scholar, recently articulated in the *Wall Street Journal* that the prevailing strategy of granting individuals direct control over their personal data is no longer an effective mechanism for privacy regulation. ### The Limitations of Individual Data Control **Solove** argues that the complexity and pervasiveness of AI systems make it impractical for individuals to meaningfully manage their data. The sheer volume and intricate flow of information render individual consent and control insufficient to safeguard privacy effectively. ### A Call for Corporate Accountability Instead of focusing solely on individual control, **Solove** advocates for a paradigm shift: holding companies directly accountable for their data practices. This approach draws parallels with highly regulated industries, such as food and drug manufacturing, where companies bear significant responsibility for product safety and ethical conduct. ### Proposed Regulatory Measures To achieve this enhanced corporate accountability, **Solove** outlines several key measures: * **Rigorous Data Minimization:** Companies should be legally obligated to collect and retain only the data absolutely necessary for their services. * **Fiduciary Duties:** Organizations handling personal data should be bound by fiduciary duties, requiring them to act in the best interests of the individuals whose data they possess. * **Liability for Negligent/Reckless Design:** Companies should face legal consequences for technological designs that negligently or recklessly compromise privacy. * **Liability for Harmful Algorithms:** Algorithms that cause demonstrable harm to individuals should also incur corporate liability. * **Multi-Stakeholder Review:** Technologies, particularly those involving AI, should undergo comprehensive review by a diverse group of stakeholders, including experts, regulators, and civil society representatives. This proactive, accountability-centric framework is presented as a far more potent defense against privacy infringements in the rapidly evolving AI landscape. The full academic paper supporting these arguments is available [here](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6985419).