# Protecting Privacy in the AI Era Why corporate accountability for data matters - **Source:** [Schneier on Security](https://brifing.si/source/7aee9996-c7c0-47f7-89ec-66a1ed95f8cc) - **Published:** 2026-07-16 - **Topic:** [Data & AI](https://brifing.si/c/data-ai) - **Original article:** - **On Brifing:** https://brifing.si/s/f6ce250c-7bc8-42a0-a97a-252b185924d7 ## The Shortcoming of Traditional Approach Daniel Solove's WSJ article argues that giving individuals control over their personal data is an ineffective privacy solution today. He advocates for adopting a corporate accountability model similar to food and pharmaceutical industries. ## Mandatory Data Minimization The paper proposes regulations requiring companies to minimize data collection. This approach aims to reduce privacy risks by preventing unnecessary data gathering in the first place. ## Technological Design Liability Under the proposed model, companies would be legally responsible for harms caused by negligent technology designs. This creates a mechanism to encourage secure and ethical design practices. ## Algorithmic Harm Accountability The article advocates for corporate liability for harmful algorithms. This approach seeks to establish protective measures against potential risks posed by AI systems. ## Multi-Stakeholder Review Mechanism Among the proposed solutions is having technologies reviewed by multi-stakeholder groups. This aims to create a balanced oversight system incorporating diverse perspectives. ## A New Privacy Paradigm Solove's paper presents the shift from individual control to corporate accountability as a new privacy paradigm. This approach requires fundamental changes for effective protection in the digital age. ## Sources covering this story - https://www.schneier.com/blog/archives/2026/07/protecting-privacy-in-an-ai-era.html — --- _Summary written by Brifing from the original reporting. Copyright in the original article belongs to its publisher; read the full piece at the link above._