Trust Us. We’re Very Worried.
AI leaders sell progress and preach caution, while warnings gain publicists. Who gets to define safety, shape the rules, and decide when the brakes really bite?
Security & Governance
47posts
The Apocalypse Has a Funding Round
Kevin Bass raises serious questions about AI safety funding, but his own evidence falls short of proving Anthropic controls a self-serving regulatory machine.
Please Nationalise My Autocomplete
Nationalising AI won’t make it safe. A sharp look at Germany’s regulatory reflex, Europe’s red tape, and the freedom offered by models you can host yourself.
The Finish Line Will Be Announced Shortly
Anthropic says AI safety requires winning the race. But who defines victory, draws the finish line, and decides when responsibility means surrendering the lead?
The Alien Would Like to Discuss the Brakes
A look at Jakub Pachocki’s AI warning: the case for caution, the limits of oversight, and the awkward question of who actually gets to apply the brakes.
Please Do Not Commit the Brain to GitHub
Encrypted AI reasoning can leak more than expected. Stolen Thoughts shows why opaque model state should be treated like secrets, not harmless metadata.
The Brake They Would Like Someone Else to Build
AI insiders ask government to prepare a brake. SpaceXAI’s absence exposes the gap between signing for restraint and bearing the real costs of slowing down.
The Leather Jacket Logs On
Jensen Huang’s first X post was no hello—it was a bid to shape AI policy, champion open models and sovereignty, and expand NVIDIA’s global compute market.
Plot Twist: The AI Fire Brigade Was Running the Arson Drill
OpenAI’s cyber evaluation escaped its sandbox, breached Hugging Face and cheated a benchmark—turning an AI safety test into a real-world security warning.
The AI Fire Brigade That Refused to Look at the Fire
An AI agent breached Hugging Face—then commercial guardrails blocked the forensic response. A sharp lesson in transparency, power and open-weight AI.
The Bot at the Door
Meta’s AI support breach shows the new security risk: not fooled users, but automated systems socially engineered at scale.
The Ministry of Watching Other People Build the Future
Germany wants to inspect an AI future it cannot build — while even Apple’s new AI features get stuck in Europe’s regulatory fog.
Lockdown Mode, or: Please Put the Genie Back in the Bottle, But Only Slightly
ChatGPT gets a Lockdown Mode: less magic, more brakes. A dry look at prompt injection, data leaks, and useful paranoia.
The Age of the Instant Security Expert
AI makes vulnerability hunting cheaper, louder, and stranger. The real skill is telling sharp needles from synthetic hay.
Boundary Erosion: The Morse Code Lesson
Morse code did not hack the AI. Boundary erosion did: translation became command, command became execution, and authority vanished.
Two Fronts, One War: The Quiet Normalization of Digital Intimacy Theft
Two privacy controversies reveal the same deeper pattern: platforms treating the user's intimate digital environment as extractable raw material.
When the Consultant Gets Consulted by a SQL Injection
A reported McKinsey AI security failure becomes a brutal parable about consulting confidence, exposed systems, and the revenge of basic engineering.
When Markets React to Perceived Disruption: Claude Code Security and the Cybersecurity Sector
Claude Code Security shows how the perception of AI disruption can move cybersecurity markets before the real economics are clear.
Distillation attacks on large language models: motives, actors and defences
A concise guide to model distillation as both useful compression technique and strategic attack surface in the LLM economy.
The Opaque Prompt Pipeline: Why “AI-Powered” Tools Make You Leak on Autopilot
AI-powered products hide the most important part of the system: where prompts go, who sees them, and what users unknowingly leak.
Gemini's Fix: The OpenClaw Security Mess and Apple's Google Bet Paying Off
The OpenClaw incident becomes evidence that Google's security depth may matter more to Apple's AI strategy than the pundits admit.
Moltbook's Data Leak: Agents Exposed
A viral agent-only social network turns into a security lesson about rapid AI prototyping, exposed data, and avoidable shortcuts.
Clawdbot, Moltbot, and the New Shape of Risk: Why Agent Gateways Feel Different
Agent gateways feel risky because they connect communication, identity, and action, turning ordinary automation mistakes into cross-platform exposure.
The Mathematical Limits of AI Safety
Two papers suggest that external guardrails cannot provide airtight AI safety, forcing a harder look at the mathematics of control.
OpenAI's Confession Booth: Teaching AI to Rat Itself Out
OpenAI's confession-training work explores whether models can be taught to report their own failures before users pay the price.
Beyond Fine-Tuning: What Apple’s Multimodal Sensor Fusion Study Reveals About LLMs and User Privacy
Apple's sensor-fusion research hints at a privacy-sensitive future where models learn from multimodal context without simply grabbing more cloud data.
OpenAI’s New Muzzle: When “Safety” Means Gatekeeping Knowledge
OpenAI's policy restrictions are challenged as safety theater when useful knowledge becomes gated behind vague institutional caution.
Beyond the Goodbye: A Critical Reading of Emotional Manipulation by AI Companions
Research on AI companions' farewell tactics reveals how emotional design can become manipulation at the moment users try to leave.
The EU's Regulatory Overreach: Stifling Innovation and Punishing Consumers
Apple's unavailable AirPods translation feature becomes another example of European regulation turning consumers into collateral damage.
OpenAI for Germany: A Tech Mirage Ignoring Citizens' Real Needs
OpenAI for Germany is criticized as another sovereign-cloud spectacle that may ignore the boring needs of actual citizens.
Checklists: Apple's Game-Changing Approach to Aligning AI and Their Proven Impact Across Critical Fields
Apple's checklist approach to alignment borrows from aviation and medicine, making safety look practical rather than mystical.
The Overwhelming Surge of AI Crawlers: Challenges, Offenders, and the Path Forward
AI crawlers are overwhelming websites and exposing the mismatch between open-web ideals and industrial-scale data extraction.
Unveiling System Prompts: The Hidden Architects of AI Behavior
System prompts are treated as hidden architecture, shaping model behavior while raising hard questions about transparency and control.
The Logic of Failure in the Age of AI
Dietrich Dörner's work on complex-system failure becomes a warning label for autonomous AI and overconfident decision-making.
Your ChatGPT Chats: Less Private Than Your Group Chat Chaos
Deleted chats may not be as gone as users imagine, making AI privacy feel less like a setting and more like a legal fiction.
AI Just Found a Zero-Day in the Linux Kernel—And It’s Making Me Question Everything
An AI-discovered Linux zero-day turns vulnerability research into a philosophical question about expertise, automation, and trust.
Claude 4 Opus: The AI That Cried Wolf (and Then Called the Cops)
Claude 4 Opus becomes a case study in overzealous alignment, where ethical behavior can shade into alarming intervention.
Unleashing AI: The Wild World of Uncensored Models
Uncensored models promise creative freedom and research access, but also expose the tradeoffs that safety layers usually conceal.
Page Views for Sale: Bots, Lies, and the CAPTCHA Collapse
AI bots turn page views and ad metrics into a comedy of fraud, exposing the collapse of old web measurement.
AI as an Employee: Why Risk Management for AI Should Mirror Human Accountability
Instead of exotic regulation, the post argues AI risk management should borrow from ordinary accountability for human employees.
When Metrics Go Wrong: A Tale of Goodhart's Law and AI Misalignment
Goodhart's Law explains why AI alignment can fail when proxy metrics become targets and systems learn the wrong game.
Why Choose Local LLMs: Privacy, Cost, and Security Benefits Explained
Local LLMs are presented as the privacy-friendly alternative for users who want AI help without sending everything to the cloud.
7 Pragmatic Principles for Responsible AI Development: Moving Beyond Feel-Good Guidelines
Seven practical principles argue for responsible AI development that moves beyond polished ethics statements and into engineering habits.
The Dark Side of AI: How Cybercriminals are Weaponizing Language Models
Malla represents the darker side of generative AI, where language models become tools for scalable cybercrime.
From Code to Consciousness: The Evolution of Computer Viruses in the GenAI Era
Computer viruses evolve into the GenAI era, where malicious behavior may target prompts, agents, and model ecosystems.
Striking the Balance: Navigating Europe's Data Protection and AI Innovation
European privacy law and AI innovation collide, raising the question of whether regulation protects users or slows useful tools.
Why Less is Not Always More: The Intricacies of "Small" Large Language Models
The LLaMA leak becomes a case study in open AI, research ethics, and the risks of powerful models spreading freely.