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[…] Establishment of a Foundation for Trustworthiness (AI Framework Act or simply, Act) introduces specific obligations for “high-impact” AI systems in critical sectors, including healthcare, energy, and public services, and mandatory labeling requirements for certain applications of generative AI. The Act also includes substantial public support for private sector AI development and innovation through its […]

[…] section on obtaining consent appears only to apply when an operator has actual knowledge that it is collecting personal information from a teen, rather than also for services directed at teens. Rather than prescribe specific methods for obtaining consent, Arkansas borrows from the COPPA Rule and allows for “any reasonable effort, taking into consideration […]

[…] aids investigations into rule violations; Provides administrative support to other bodies (Board, Advisory Forum, Scientific Panel); Consults and cooperates with stakeholders; Cooperates with other relevant DG and services of the Commission; Supports international cooperation. European AI Board : Ar t. 65 AIA – Composition: 1 representative per Member State, with the EDPS participating as […]

[…] aids investigations into rule violations; Provides administrative support to other bodies (Board, Advisory Forum, Scientific Panel); Consults and cooperates with stakeholders; Cooperates with other relevant DG and services of the Commission; Supports international cooperation. European AI Board : Ar t. 65 AIA – Composition: 1 representative per Member State, with the EDPS participating as […]

[…] (2) “human-out-the-loop” (when it is not practical to subject every algorithmic recommendation to a human review); or (3) “human- over-the-loop” (to allow humans to intervene when situations call for it). To assess which of these approaches are appropriate, the Model Framework recommends organizations consider a 2-by-2 matrix of probability and severity of risk. In […]

[…] (2) “human-out-the-loop” (when it is not practical to subject every algorithmic recommendation to a human review); or (3) “human- over-the-loop” (to allow humans to intervene when situations call for it). To assess which of these approaches are appropriate, the Model Framework recommends organizations consider a 2-by-2 matrix of probability and severity of risk. In […]

[…] (2) “human-out-the-loop” (when it is not practical to subject every algorithmic recommendation to a human review); or (3) “human- over-the-loop” (to allow humans to intervene when situations call for it). To assess which of these approaches are appropriate, the Model Framework recommends organizations consider a 2-by-2 matrix of probability and severity of risk. In […]

[…] Office of Japan released the “Social Principles of Human-Centric AI” (人間中心の AI 社会 原則) 157 on 29 March 2019. The Principles highlight the benefits of AI and call for transformation of the whole of Japanese society – including human resources, social systems, industrial structures, innovation, and governance – into an “AI Ready Society” that […]

[…] algorithm allowed for the creation of AI models that can be trained efficiently on massive amounts of data. Further, while much attention has been paid to so- called “general purpose” 9 generative AI models (such as OpenAI’s ChatGPT, Google’s Gemini, and Anthropic’s Claude), there are narrower, use-case specific models that are trained on highly […]

[…] workloads or the underlying system and platform.” Intel “Confidential Computing offers a hardware-based security solution des igned to help protect data in use via unique application-isolation technology called a Trusted Execution Environment (TEE).” Confidential Computing Consortium “Confidential Computing is the protection of data in use by performing computation in a hardware-based, attested Trusted Execution […]