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Future of Privacy Forum – New Jersey Rulemaking Comments
[…] urp ose s. ( D ) The phra se “s e lls or lic e nse s” does no t in clu d e: ( i) a one -tim e or occa sio nal sa le of asse ts of a busin e ss a s part of a tr a n sfe r […]

“Personality vs. Personalization” in AI Systems: Specific Uses and Concrete Risks (Part 2)
[…] qualities (e.g., emotional intelligence and empathy) can reduce users’ concerns about privacy infringements. The anthropomorphisation these characteristics engender in users may lead them to develop parasocial relationships— one-way relationships because chatbots cannot have emotional attachments with the user—that make them more willing to disclose data about themselves to the system. Impersonation of real people: […]

Vice President of U.S. Policy
[…] FPF Conduct, oversee, or contribute to new research Internal Coordination, Operations, and Support (app. 20% of time) Ensure members of the U.S. Policy Team are coordinating with one another and other teams Ensure that FPF communications, events, and operations experts are informed of and, as relevant, including in planning for upcoming projects Attend and […]

“Personality vs. Personalization” in AI Systems: An Introduction (Part 1)
[…] to respond — like “you’re my running coach, give me a daily running plan and be positive, upbeat and motivating.” Gemini will take those instructions and, with one click, enhance them to create a Gem that meets your specific needs.” “Get more done with Gemini: Try 1.5 Pro and more intelligent features,” May 14, […]

AI Regulation in Latin America: Overview and Emerging Trends in Key Proposals
[…] overview of the most relevant bills in the selected jurisdictions and identify emerging trends and divergences in the region. Accordingly, this analysis was based on at least one active proposal from each country that either (i) targets AI regulation in general, instead of providing technology-specific or sector-specific regulation; (ii) has similar provisions and scope […]

Event Report – FPF July 2025 Roundtable
[…] a in in g data se t, fr o m whic h th e und esir a b le data has been re m ove d . One is su e w it h exa ct unle arn in g is th e co st: re tr a in in g a mod el […]

A Price to Pay: U.S. Lawmaker Efforts to Regulate Algorithmic and Data-Driven Pricing
[…] AI used to make “consequential decisions,” including educational opportunities, employment, finance or lending, healthcare, housing, insurance, and other critical services. The use of a pricing algorithm in one of these contexts may therefore trigger the requirements of certain AI regulations. For example, the Colorado AI Act defines “consequential decision” to mean “a decision that […]

The “Neural Data” Goldilocks Problem: Defining “Neural Data” in U.S. State Privacy Laws
[…] apply when neural data is collected or processed for making inferences. Montana Montana SB 163 takes a slightly different approach than the other laws in two ways: one, it applies to “neurotechnology data,” an even broader category of data that includes the measurement of neural activity; and two, it amends Montana’s Genetic Information Privacy […]

FPF at PDP Week 2025: Generative AI, Digital Trust, and the Future of Cross-Border Data Transfers in APAC
[…] impact AI governance and how data protection regulators in Japan, South Korea, and Hong Kong (among others) have provided guidance on this. Josh’s presentation was followed by one from Darshini Ramiah, Senior Manager of AI Governance and Safety at IMDA. Darshini provided an overview of Singapore’s approach to AI governance, which is built on […]

Balancing Innovation and Oversight: Regulatory Sandboxes as a Tool for AI Governance
[…] setting while managing potential risks. The concept of a regulatory sandbox was first introduced in the financial technology (fintech) sector, with the United Kingdom launching the first one in 2015. Since then, the concept has gained global traction, especially in sectors with rapid technological advancement, such as healthcare. According to a 2025 report by […]