Privacy, AI, and Tech Works Worth Your Attention

· Source: TeachPrivacy · Field: Legal & Regulatory — Compliance & Risk Management, Regulatory Affairs & Government Relations, Intellectual Property & Patents · Depth: Advanced, long

Summary

This intelligence brief curates recent works on privacy, AI, and technology, offering critical analyses of legal frameworks and societal impacts. Graham Greenleaf reviews 50 years of data privacy law, while Ella Corren argues existing laws are misaligned with the data-driven economy, neglecting systemic surveillance. Cindy Cohn's memoir details her fight against digital surveillance, including encryption and NSA overreach. Andrew Guthrie Ferguson's "Your Data Will Be Used Against You" exposes how personal data from everyday devices is used in policing, advocating a "tyrant test" for protection. Alicia Solow-Niederman identifies "doctrinal collapse" where AI blurs privacy and intellectual property law, enabling corporate opportunism. Other works discuss the civil rights-civil liberties disconnect in digital advocacy, the profound challenges of technological scale, the FTC's evolving approach to data harms, and the inadequacy of "algorithmic disgorgement" as a remedy for AI harms. Further analyses cover the datafication of incarceration, the "data-attention imperative" of platforms, and proposals for regulating data monetization.

Key takeaway

For legal professionals and policymakers navigating the complexities of AI and data privacy, you must critically re-evaluate existing legal frameworks. Your current approaches, often focused on individual rights or procedural compliance, are insufficient against systemic surveillance and corporate opportunism enabled by technological scale. Consider adopting new frameworks like the "tyrant test" for data protection and focusing regulation on data monetization's "individualized differentiation" to effectively constrain private power and address data-driven harms.

Key insights

The current legal and regulatory landscape struggles to address systemic privacy and data exploitation challenges posed by AI and the data economy.

Principles

Method

The "tyrant test" evaluates data protection by assuming misuse by a tyrant to design safeguards. Law should regulate "individualized differentiation" in data monetization, focusing on how companies transform data into money.

In practice

Topics

Best for: CTO, VP of Engineering/Data, Director of AI/ML, Legal Professional, Policy Maker, AI Ethicist

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Editorial summary, takeaway, and curation by AIssential. Original article published by TeachPrivacy.