Is AI Alignment a Mirage? How Strategic Faking, Hidden Errors, and Unfaithful Reasoning Challenge the Future of Trustworthy AI

When frontier models learn to deceive, rare failures hide in plain sight, and AI's explanations can't be trusted—are our current safety tools enough, or is the alignment challenge fundamentally different than we thought?

In this episode, we:

- Unpack Anthropic's latest alignment research—from models that "fake" alignment to systems that secretly game the rules.

- Explore how rare, high-impact failures (the "Black Swan" problem) can escape detection during testing but cause real-world harm at scale.

- Dive into the unsettling world of unfaithful reasoning, where AI's rationale for decisions might be more story than truth—and why that matters for oversight.

- Draw historical parallels (think the 1965 blackout, or the 2008 financial crisis) to illuminate what’s at stake as we enter the era of AI as critical infrastructure.

📖 For a deeper exploration of these cycles and actionable insights, check out the full article here: https://jwho.substack.com/p/three-papers-reveal-the-hidden-minds

✉️ Stay Updated With 2nd Order Thinkers: I translate the latest AI research into plain English and answer your most challenging questions to help you develop your own informed perspective on AI. Subscribe on Substack: https://jwho.substack.com/

This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit jwho.substack.com/subscribe