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Future of Privacy Forum Honors Julie Brill with Lifetime Achievement Award
Washington, D.C. – September 12, 2025 — The Future of Privacy Forum, a global non-profit focused on data protection, AI and emerging technologies today announced that it has honored Julie Brill with its Lifetime Achievement Award. The award recognizes Brill’s decades of leadership and profound impact on the fields of consumer protection, data protection […]

“Personality vs. Personalization” in AI Systems: Specific Uses and Concrete Risks (Part 2)
[…] personality-like features, whether it is a specific voice mode, or a consistent persona, or even a range of “AI companions.” Even if companion-like personalities are not directly promoted as features, users can build them using system prompts and customized design; an early 2023 feature of OpenAI enabled users to create custom GPTs. Figure 3 […]

AI Regulation in Latin America: Overview and Emerging Trends in Key Proposals
[…] the OECD’s AI Principles, focused on transparency, security, and responsibility of AI systems, and to UNESCO’s AI Ethics Recommendation, which emphasizes the need for a human-centered approach, promoting social justice and environmental sustainability in AI systems. All bills reviewed ground the development of AI in privacy or data protection as a guiding principle to […]

FPF at PDP Week 2025: Generative AI, Digital Trust, and the Future of Cross-Border Data Transfers in APAC
[…] about the latest developments. This year, FPF APAC organized two events for its members: a Privacy Leaders’ Luncheon (an annual staple), and for the first time, an India Luncheon co-organized alongside Khaitan & Co. 5.1 On July 8, 2025, FPF hosted an invite-only Privacy Leaders’ Luncheon. This closed-door event provided a platform for senior […]

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 […]

Vermont and Nebraska: Diverging Experiments in State Age-Appropriate Design Codes
In May 2025, Nebraska and Vermont passed Age-Appropriate Design Code Acts (AADCs), continuing the bipartisan trend of states advancing protections for youth online. While these new bills arrived within the same week and share both a common name and general purpose, their scope, applicability, and substance take two very different approaches to a common […]

FPF Experts Take The Stage at the 2025 IAPP Global Privacy Summit
[…] trust in the digital ecosystem with consumers. The panel also provided a master perspective on how tech leaders approach digital governance now and in the future through promoting interoperability, model transparency, and government experimentation and implementation of IT tools and procurement. On the second day of the conference, FPF Managing Director for Asia-Pacific (APAC) […]

Amendments to the Montana Consumer Data Privacy Act Bring Big Changes to Big Sky Country
[…] lowest numerical applicability thresholds of any of the state comprehensive privacy laws when the law was enacted in 2023. At that time, prior comprehensive privacy laws in Virginia, Colorado, Utah, Connecticut, Iowa, and Indiana all applied to controllers that either (1) control or process the personal data of at least 100,000 consumers (“the general […]

Consent for Processing Personal Data in the Age of AI: Key Updates Across Asia-Pacific
[…] contract performance, bringing Indonesia closer to global privacy frameworks. In November 2023, the Philippines‘ National Privacy Commission issued a Circular on Consent, clarifying valid consent standards and promoting transparency. The guidance aims to reduce consent fatigue by encouraging layered, contextual consent interfaces and outlines when consent may not be strictly necessary. South Korea amended […]

The Curse of Dimensionality: De-identification Challenges in the Sharing of Highly Dimensional Datasets
[…] values are replaced with broader, less precise categories. Examples include replacing an exact birth date with just the birth year or an age range, a specific ZIP code with a larger geographic area, or a specific occupation with a broader job category. This is a core technique used to achieve k-anonymity. While it reduces […]