Search results

[…] deploying high-impact AI systems.  Under Article 33, AI Business Operators providing AI products and services must “review in advance” (this presumably means before the relevant product or service is released into a live environment or goes to market) whether their AI systems is considered “high-impact AI.” Businesses may request confirmation from the MSIT on […]

[…] the data of all residents. Similar scope to federal COPPA – mostly: The law applies to “operators” defined as entities who operate or provide a website, online service, online application, or mobile application that is either “directed at” children or teens or when the service has actual knowledge that it is collecting personal information […]

[…] AI Systems Providers : High- Risk AI systems need to undergo a conformit y assessment (Ar t. 43) before being placed in the market or put into service (i.e. data quality, documentation and traceability, transparency, human oversight, accuracy, cybersecurity and robustness – Arts. 9-15); This assessment has to be repeated if the system or […]

[…] AI Systems Providers : High- Risk AI systems need to undergo a conformit y assessment (Ar t. 43) before being placed in the market or put into service (i.e. data quality, documentation and traceability, transparency, human oversight, accuracy, cybersecurity and robustness – Arts. 9-15); This assessment has to be repeated if the system or […]

[…] (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 […]