California’s SB 53: The First Frontier AI Law, Explained
California Enacts First Frontier AI Law as New York Weighs Its Own On September 29, Governor Newsom (D) signed SB 53, the “Transparency in Frontier Artificial Intelligence Act (TFAIA),” authored by Sen. Scott Wiener (D). The law makes California the first state to enact a statute specifically targeting frontier artificial intelligence (AI) safety and transparency. […]
The State of State AI: Legislative Approaches to AI in 2025
State lawmakers accelerated their focus on AI regulation in 2025, proposing a vast array of new regulatory models. From chatbots and frontier models to healthcare, liability, and sandboxes, legislators examined nearly every aspect of AI as they sought to address its impact on their constituents. To help stakeholders understand this rapidly evolving environment, the Future […]
Call for Nominations: 16th Annual Privacy Papers for Policymakers Awards
The 16th Privacy Papers for Policymakers call for submissions is now open until October 30, 2025. FPF’s Privacy Papers for Policymakers Award recognizes leading privacy research and analytical scholarship relevant to policymakers in the U.S. and internationally. The award highlights important work that analyzes current and emerging privacy issues and proposes achievable short-term solutions or […]
“Personality vs. Personalization” in AI Systems: Responsible Design and Risk Management (Part 4)
This post is the fourth and final blog post in a series on personality versus personalization in AI systems. Read Part 1 (exploring concepts), Part 2 (concrete uses and risks), and Part 3 (intersection with U.S. law). Conversational AI technologies are hyper-personalizing. Across sectors, companies are focused on offering personalized experiences that are tailored to […]
“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 […]
“Personality vs. Personalization” in AI Systems: Specific Uses and Concrete Risks (Part 2)
This post is the second in a multi-part series on personality versus personalization in AI systems, providing an overview of these concepts and their use cases, concrete risks, legal considerations, and potential risk management for each category. The previous post provided an introduction to personality versus personalization. In AI governance and public policy, the many […]
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 […]
FPF at PDP Week 2025: Generative AI, Digital Trust, and the Future of Cross-Border Data Transfers in APAC
Authors: Darren Ang Wei Cheng and James Jerin Akash (FPF APAC Interns) From July 7 to 10, 2025, the Future of Privacy Forum (FPF)’s Asia-Pacific (APAC) office was actively engaged in Singapore’s Personal Data Protection Week 2025 (PDP Week) – a week of events hosted by the Personal Data Protection Commission of Singapore (PDPC) at […]