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.
Privacy
11posts
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.
The Laptop Rule and the White-Collar Delusion
The laptop class may be more exposed to AI than it admits, because text-heavy office work is exactly where models thrive.
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.
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.
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.
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.
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.
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.
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.