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3 posts

• Emergent Capabilities as Security Risks: What AI Systems Can Do That Nobody Planned For

  LLMs spontaneously develop capabilities not explicitly trained—and this creates unpredictable security properties that defenders can't anticipate from static model cards or one-time capability evals.

  Jun 28, 2026 capability-evaluation threat-modeling model-cards emergent-behavior ai-governance

• AI-Mediated Communication Can Steer Collective Opinion

  When AI edits your posts before you share them, it introduces directional biases that compound through social networks — and a new study quantifies both the bias and the amplification effect.

  Jun 21, 2026 opinion-dynamics llm-bias social-networks ai-governance platform-design

• SQLite AGENTS.md: No Agentic Code Accepted

  D. Richard Hipp's three-sentence policy in SQLite's AGENTS.md distills what most AI governance frameworks bury in pages of caveats: the line isn't between human and machine intelligence — it's between verified and unverified contributions. An analysis of what this stance gets right, and why the same commit log that hosts the policy also cites Claude analysis.

  Jun 20, 2026 secure-development agentic-ai responsible-ai ai-governance supply-chain