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[…] the means to reasonably identify the individuals: if they do not process personal data, the GDPR does not apply.  On the other hand, pseudonymization is not a free pass. A dataset may still qualify as personal data: (1) if the recipient has reasonable means to re-identify the individual; (2) for the controller who holds […]

[…] Senior Director of U.S. Legislation, Future of Privacy Forum AUTHORS Thanks to Bridget Egan for her research contributions. ACKNOWLEDGEMENTS All FPF materials that are released publicly are free to share and adapt with appropriate attribution. Learn more . 3 Table 1. Legislative Outcomes for State AI Bills Overview of the 210 industry-focused AI bills […]

[…] Senior Director of U.S. Legislation, Future of Privacy Forum AUTHORS Thanks to Bridget Egan for her research contributions. ACKNOWLEDGEMENTS All FPF materials that are released publicly are free to share and adapt with appropriate attribution. Learn more . The Future of Privacy Forum’s (FPF) report, The State of State AI: Legislative Approaches to AI […]

[…] including subscription-based and enterprise pricing models. As personalized AI systems increasingly replace, or are integrated into, online search, they will impact online content that has largely been free and ad-supported since the early Internet. However, it is not clear that personalized AI systems can, or should, adopt compensation strategies that follow the same historical […]

[…] of their risk classification. For AI systems in general, Brazil’s proposal includes:  The right to prior information about an interaction with an AI system, in an accessible, free of charge, and understandable format.  The right to privacy and the protection of personal data, following the Lei Geral de Proteção de Dados Pessoais (LGPD) and […]

[…] will companies work through and implement an analysis of “necessary,” “reasonably necessary,” or “strictly necessary?” 2. Is data collection “necessary” in ad-driven business models where content is free in exchange for advertising? Is there a distinction between the “necessity” of data for ad measurement or attribution and data collected for first-party or cross-context behavioral […]

[…] us as we discuss the current environment and help us map unanswered questions and areas of concern. 5–8 KEY DISCUSSION QUESTIONS Regulators world-wide are erecting barriers to free data flows based on data privacy, national security/law enforcement and economic sovereignty. These rules impact how companies structure cloud infrastructure and vendor contracts, conduct cybersecurity monitoring […]

[…] Article 1 of the LGPD identifies the objective of the law as ensuring the processing of personal data protects the fundamental rights of freedom, privacy, and the free development of personality.3 At the same time, Article 2 of the LGPD recognizes data protection is “grounded” on economic and technological development and innovation.  The study […]

[…] alignment between data protection regulators, with the G7 Data Protection Authorities and Privacy Commissioners’ Summit in Tokyo. This resulted in a communiqué outlining their focus on Data Free Flow with Trust (DFFT), emerging technologies, and enforcement cooperation. FPF’s Global team circled the globe, hosting and speaking at leading events this year, including the Global […]

[…] high utility loss for QIs) Masking Obscure parts of data values (e.g., XXXX) Obscure direct identifiers Simple; Preserves format Limited privacy protection; Can reduce utility; Hard for free text Low (Insufficient for QIs in queries) Generalization Replace specific values with broader categories Reduce identifiability via QIs Basis for k-anonymity Significant utility loss, especially in […]