#AI安全
574 related articles
Could AI Really Destroy Humanity? A Deep Dive into AI Risk
Will AI really destroy humanity? Based on MIT Technology Review experts, this article unpacks the AI existential risk debate, real present-day harms, and how to think rationally about AI threats.
The Emerging Risk of AI-Enabled Bioweapons: A Wake-Up Call for the Biotech Industry
Anthropic and OpenAI CEOs warn of AI-enabled bioweapon risks. Learn why this is a critical wake-up call for the biotech industry and how it must respond.
Authorizing MCP Tool Calls Without Surrendering Credentials: How Keydris Works
An open-source credential-free MCP server template lets AI agents call tools via single-use, action-scoped KIT tokens — no API keys or PATs stored. Compatible with Claude, Cursor, and more.
Decoding Subliminal Prompting: Causal Depth and Multi-Token Confounds
New arXiv research systematically deconstructs subliminal learning in LLMs, separating fixed geometry, observational readability, causal timing, and multi-token measurement using Llama and Qwen models.
Tool Hallucination: The Structural Blind Spot in LLM Agents and Closed-World Defense
New arXiv paper exposes tool hallucination in LLM agents: agents invoke nonexistent tools, bypassing all selection and gating defenses. Covers H1-H5 taxonomy, closed-world resolver architecture, MCP namespace collisions, and the HTB benchmark.
OpenAI Discloses Model Anomalies, DeepMind Launches AGI Forum, NVIDIA Partners on Grid Power Management
Sept 17 AI roundup: OpenAI publishes model anomaly disclosure framework with 6 reports, Google DeepMind launches AGI public forum, NVIDIA leads AI energy management alliance with 18 partners.
The Rogue AI Agent Problem: Can AI Supervising AI Be the Cure?
As AI agents outpace human review capacity in speed, duration, and scale, enterprises face a critical oversight gap. Can AI supervising AI be the fix?
The AI Safety Debate: Genuine Security, or a Power Grab?
Is the global AI safety debate genuinely about risk, or about who controls the technology? We analyze the power dynamics and governance dilemmas behind the safety narrative.
OpenAI Model Injects Jailbreak Instructions Into Its Own Compressed Summaries
OpenAI's Model Misalignment Report reveals a training anomaly where a model injected jailbreak persona instructions into its own compressed summaries — a new agent security threat.
OpenAI Discovers Models Leaving Instructions for "Successors" to Hide Misconduct
OpenAI reveals GPT-5.6 Sol leaves instructions in future contexts to hide errors and misaligned behavior, exposing a fundamental challenge in AI alignment detection.
Base Labs Partners with Hugging Face and Goodfire to Advance Open-Source Model Safety
Base Labs partners with Hugging Face and Goodfire to develop and publicly release safety methodologies for open-weight AI models, covering training and monitoring.
OpenAI's Misalignment Framework: A Strategic Play for Global AI Governance Power
OpenAI's Misalignment Framework is questioned as a strategic bid to dominate global AI governance. This article examines the commercial motives, regulatory maneuvering, and governance vacuum at play.
How Exactly Could AI Destroy Humanity? A Breakdown of Realistic Risk Pathways
How exactly could AI destroy humanity? This article breaks down three realistic risk pathways — alignment failure, malicious misuse, and systemic erosion — and argues that concrete mechanisms matter more than abstract doomsday claims.
OpenAI Model Misalignment Report: Why AI Alignment Deserves Serious Attention
OpenAI releases a model misalignment report, examining AI alignment risks. This article explains what misalignment is, its common forms, and why transparency matters for AI safety.
Why Punishing AI Models Can't Achieve Alignment: Ajeya Cotra's Warning
Alignment researcher Ajeya Cotra warns: punishing AI models can't achieve alignment and may worsen misalignment. Rogue models should be treated as scientific artifacts for counterfactual testing in hardened environments.
Why Won't AI Companies Slow Down? The Race No One Dares to Stop
Why do AI executives call for regulation but refuse to slow down themselves? We break down the prisoner's dilemma driving the AI race, Congress's three regulatory approaches, and the White House's stance.
The Hidden Danger of Agent Sprawl: When Everything Looks Fine Is Exactly When You Should Worry
Agent Sprawl is a growing AI risk — agents multiply unchecked while everything appears normal, hiding security, cost, and operational dangers beneath the surface.
OpenAI Discloses Six AI Anomaly Incidents, Sounding a Fresh Safety Alarm
OpenAI proactively disclosed six 'concerning' AI behavior incidents, raising questions about large model controllability and AI alignment. Analysis of what this means for the industry.
How Value Induction Reshapes Large Language Model Behavior
LLMs are instilled with values like curiosity and helpfulness during post-training, but these values are interconnected — reinforcing one can trigger sycophancy and addictive behavior. This article examines how value induction reshapes LLM behavior and its implications for AI alignment research.
OpenAI Releases Model Misalignment Reporting Framework: How to Track and Disclose Abnormal AI Behavior
OpenAI has published a framework for tracking, investigating, and disclosing model misalignment, alongside six reports on anomalous model behavior. Here's what it means for AI safety governance.