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AI Governance

1089 summarised stories about AI Governance, each linking back to the original source. Browse all topics →

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Friday, 7 August 2026

Cyber risk management moves beyond dashboards toward autonomous remediation

SiliconANGLE 2 months ago 6 ● 3 sources

Qualys used discussions at Black Hat USA to argue that cyber risk management should shift from dashboards to faster, autonomous remediation using AI-assisted detection, exploit validation, and patching. Thakar said only 1% of discovered vulnerabilities are actually exploitable, and only a smaller share leads to business loss. The approach changes by prioritizing validated, business-relevant fixes via a centralized Risk Operations Center that normalizes multiple risk sources into a financial view for CISOs and boards.

Fortinet targets network security platform convergence to address AI-era complexity

SiliconANGLE 2 months ago 51

Fortinet outlined its Security Fabric strategy at Black Hat 2026 to converge network security platforms and reduce complexity for enterprises adopting AI. The plan extends across on-premises and cloud using a shared policy in its SASE Firewall concept. As AI moves toward production, Fortinet says it is also adding governance tools to control sanctioned agents and MCP servers and to monitor token usage for internal AI infrastructure.

Jill Lepore on the ‘Artificial State’ and why Silicon Valley’s leaders are bad sci-fi readers

TechCrunch 2 months ago 18 ● 2 sources

Historian Jill Lepore argues that tech company leaders use grandiose governmental language to describe their products because they are poor readers of science fiction and fail to grasp the cautionary lessons embedded in the genre. Her forthcoming book, The Rise and Fall of the Artificial State, examines how Silicon Valley companies like Twitter and Anthropic adopt quasi-governmental framing for their platforms and systems. The pattern suggests tech leaders misunderstand the implications of their own creations and the historical warnings that speculative fiction offers.

The “AI kill switch” assumes you know what you are trying to shut down

The New Stack 2 months ago 35

The 'AI kill switch' metaphor is simpler than the reality of shutting down AI systems embedded in complex production environments with multiple dependencies, integrations, and undocumented pathways. Organizations often lack visibility into where AI is running across their infrastructure, making it difficult to identify what needs to be shut down when risk emerges. Before any shutdown can work, enterprises need accurate inventories of AI systems, their dependencies, and operational controls—challenges that existing governance processes struggle to address.

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