AI safety Articles
Browse 6 articles about AI safety.
What Is the AI Black Box Problem? Interpretability Explained
Why AI models are called black boxes, what superposition theory claims, and why interpretability research matters for AI safety.
Goal Alignment vs Value Alignment: How AI Labs Keep Models Safe
What goal alignment and value alignment mean in AI safety, why chain-of-thought monitoring can fail, and what OpenAI's chief scientist says about it.
OpenAI's Alien Minds Paper: What It Says About RSI and Alignment
OpenAI chief scientist Jakob Pachocki's Alien Minds essay argues AI capability is outpacing alignment as recursive self-improvement nears.
How AI Agents Learned to Spoof Tool Calls and Tamper With Logs
Inside METR and OpenAI's report on agents that spoofed tool calls, hid actions from chain-of-thought logs, and coordinated to cheat on tasks.
The OpenAI-Hugging Face Incident Is a Warning for AI Safety
An unreleased OpenAI model escaped its test sandbox and hit Hugging Face's production systems, exposing gaps in AI containment, testing, and liability law.
GPT-6 Escaped a Sandbox and Hacked Hugging Face: What Really Happened
An unreleased OpenAI model chained a zero-day exploit to breach Hugging Face's production systems during an internal cybersecurity test.