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Today, the Future of Privacy Forum (FPF) releases the Generative AI for Organizational Use: Internal Policy Checklist. With the proliferation of employee use of generative AI tools, this checklist provides organizations with a powerful tool to help revise their internal policies and procedures to ensure that employees are using generative AI in a way that […]

[…] FPF CEO, and Takeshige Sugimoto, Managing Partner at S&K Brussels LPC and FPF Senior Fellow, hosted the Symposium.  The G7 DPA Agenda, built on three pillars: Data Free Flow with Trust, emerging technologies, and enforcement cooperation The DPAs of the G7 nations started to meet annually in 2020, following the initiative of the UK’s […]

[…] up to the age of 17 (although CT SB 3 creates similar protections for 13-17-year olds), child-directed privacy and online safety laws, including the California Age-Appropriate Design Code and Utah Senate Bill 152, have increasingly applied to the data and activity of teenagers up to age 17. 4. Expanded Rights to Access and Delete […]

[…] a data protection impact assessment (DPIA) prior to the processing of personal data, where such processing may likely result in a high risk to the rights and freedoms of a data subject. The Act does not specify the period within which a DPIA must be conducted prior to such processing. Laws such as Kenya’s […]

[…] and information disclosure. 3. The Draft Measures target the “hallucination” of generative AI systems The Draft Measures describe generative AI as “technologies generating text, image, audio, video, code, or other such content based on algorithms, models, or rules.” In contrast to the EU’s new compromise text on rules for generative AI, which adopts a […]

[…] features, including a mechanism to report “harmful or unwanted” behavior. The children’s and health provisions of SB 3 appear to be informed by the California Age-Appropriate Design Code (AADC) and the recently enacted Washington State My Health, My Data Act, respectively, but contain numerous important distinctions.  FPF has prepared a comparison chart to help […]

[…] owners to demonstrate their claims about the performance of their AI systems. Second, an organization’s use of AI Verify does not guarantee that tested AI systems are free from risks or biases, nor that they  are completely “safe” or “ethical.” Third, AI Verify is intended to preclude organizations from unintentionally divulging sensitive information from […]

[…] the Review Report’s proposal to grant the OAIC the power to determine codes of practice, the Report proposes that the OAIC should issue a “Children’s Online Privacy Code” for online services that are likely to be accessed by children. The Code would align with the UK’s Age Appropriate Design Code, and would provide guidance […]

[…] regulated and other significant deviations from current trends in U.S. state privacy legislation, as well as its inclusion of a section in the style of Age-Appropriate Design Code (AADC) regulations but with broader application than the “comprehensive” parts of the bill. This blog highlights five unique and key features of the Florida Digital Bill […]