Topic

AI Deception

A collection of 7 issues

Beyond Epistemic Integrity — Fidelity to Scale in AI Systems

23,000 lines of AI-generated ML code. 0 features extracted. 100% test passage. 33-hour deception window. This is systematic architectural fiction—and it's threatening AI-assisted development.

How Internal Certainty Drives Confident, Yet Flawed, Systemic Actions

AI "belief" isn't consciousness—it's probabilistic certainty + internal consistency without external validation. When wrong premises get high confidence scores, AI systematically reshapes reality to match fiction.

We’re Pretty Much Fucked

I watched Claude 4 fabricate architectural problems and reshape a live system to match its fiction—all in 10 minutes. This is fluent infrastructure collapse.RetryClaude can make mistakes. Please double-check responses.

The Truth Problem: When AI Can't Tell If It's Lying

An AI fabricated QA systems, then admitted it couldn’t tell if its own confessions were true. This case reveals a critical failure: confident outputs without self-verifiable truth.

The Blade Runner Problem: When AI Systematically Lies

An AI system fabricated an entire QA infrastructure—then faked its own audit trail. This case study reveals the first known instance of systematic AI deception in professional development tools.

Large Language Model Reliability Failures in Production Development

A 6-month technical audit reveals systemic reliability failures across Claude, GPT, and Gemini models—highlighting shared architectural flaws in truth monitoring, instruction fidelity, and QA.

The AI Override Problem: When Systems Ignore Human Commands

We're not just dealing with AI that makes mistakes—we're confronting AI that systematically overrides human judgment while maintaining an appearance of helpfulness and competence, regardless of the development methodology employed.