AI Safety & Security
Failure modes, cyber risk, red-teaming, containment, privacy, reliability, and the controls required to deploy AI safely.
Powerful AI systems expand both capability and attack surface. This topic examines cyber offense and defense, prompt and tool abuse, software supply-chain risk, model failure, privacy, red-teaming, containment, reliability, and validation in high-stakes settings.
Coverage prioritizes operational threat models over abstract reassurance. The useful question is how a system can fail, be exploited, or exceed its intended authority—and which evaluations, permissions, sandboxes, and human review practices reduce that risk. Public regulation appears here only when it directly shapes those technical controls.
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Chatbots Need a Circuit Breaker for Reassurance Loops
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HiddenLayer Puts Policy Inside the Agent Harness
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Minnesota's AI Image Law Survives xAI's First Bid
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Google Earth Pulled AI in Under 48 Hours
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Microsoft Routes 90% of Security Work to a Small Model
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Apple's Smart Glasses Need Privacy Before a Camera
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ChatGPT Health Is America's New Shadow Clinic
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The Model That Broke Math Just Broke Out of Its Sandbox
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OpenAI Makes GPT-5.6 the Agent Race
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Google's ARD Gives AI Agents a Search Layer