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Five Big Questions (and Zero Predictions) for the U.S. Privacy and AI Landscape in 2026
Introduction For better or worse, the U.S. is heading into 2026 under a familiar backdrop: no comprehensive federal privacy law, plenty of federal rumblings, and state legislators showing no signs of slowing down. What has changed is just how intertwined privacy, youth, and AI policy debates have become, whether the issue is sensitive data, data-driven […]
FPF Holiday Gift Guide for AI-Enabled, Privacy-Forward AgeTech
On Cyber Monday, giving supportive technology to an older loved one or caregiver is a great option. Finding the perfect holiday gift for an older adult who values their independence can be a challenge. This year, it might be worth exploring the exciting world of AI-enabled AgeTech. It’s not only gadgets; it’s also about giving […]
“Personality vs. Personalization” in AI Systems: Intersection with Evolving U.S. Law (Part 3)
This post is the third in a series on personality versus personality in AI systems. Read Part 1 (exploring concepts) and Part 2 (concrete uses and risks). Conversational AI technologies are hyper-personalizing. Across sectors, companies are focused on offering personalized experiences that are tailored to users’ preferences, behaviors, and virtual and physical environments. These […]
A Price to Pay: U.S. Lawmaker Efforts to Regulate Algorithmic and Data-Driven Pricing
“Algorithmic pricing,” “surveillance pricing,” “dynamic pricing”: in states across the U.S., lawmakers are introducing legislation to regulate a range of practices that use large amounts of data and algorithms to routinely inform decisions about the prices and products offered to consumers. These bills—targeting what this analysis collectively calls “data-driven pricing”—follow the Federal Trade Commission (FTC)’s […]
Tech to Support Older Adults and Caregivers: Five Privacy Questions for Age Tech
Introduction As the U.S. population ages, technologies that can help support older adults are becoming increasingly important. These tools, often called “AgeTech”, exist at the intersection of health data, consumer technology, caregiving relationships, and increasingly, artificial intelligence, and are drawing significant investment. Hundreds of well funded start-ups have launched. Many are of major interest to […]
Meet Bianca-Ioana Marcu, FPF Europe Managing Director
FPF is pleased to welcome our colleague Bianca-Ioana Marcu to her new role as Managing Director of FPF Europe. With extensive experience in privacy and data protection, she takes on this responsibility at a pivotal moment for digital regulation in Europe. In this blog, we will explore her perspectives on the evolving privacy landscape, her […]
FPF Unveils Paper on State Data Minimization Trends
Today, the Future of Privacy Forum (FPF) published a new paper—Data Minimization’s Substantive Turn: Key Questions & Operational Challenges Posed by New State Privacy Legislation. Data minimization is a bedrock principle of privacy and data protection law, with origins in the Fair Information Practice Principles (FIPPs) and the Privacy Act of 1974. At a high […]
FPF Experts Take The Stage at the 2025 IAPP Global Privacy Summit
[…] European Parliament, co-Rapporteur of the AI Act), John Edwards (Information Commissioner, U.K. Information Commissioner’s Office), and Louisa Specht-Riemenschneider (Federal Commissioner for Data Protection and Freedom of Information, Germany), on Cross-regulatory Cooperation Between Digital Regulators. Their panel began by painting a detailed portrait of how the proliferation of digital regulations has created a necessity for […]
DBJ_Weld_Re-Identification
[…] we should actively prohibit re-identification, and require those with access to de-identified data to guard and use it appropriately. HHS Office of Civil Rights (OCR) regulators have promised to provide new guidance in the near future for the de-identification of health data in response to a Congressional mandate to do so. HHS OCR regulators […]
The Curse of Dimensionality: De-identification Challenges in the Sharing of Highly Dimensional Datasets
[…] and privacy budget management. Errors in implementation, such as underestimating sensitivity or mismanaging the privacy budget across multiple queries (due to composition rules), can silently undermine the promised privacy guarantees. Defining the “privacy unit” (e.g., user, query, session) appropriately is critical; misclassification can lead to unintended disclosures. Auditing DP implementations for correctness is also […]