The case for satiating cheaply-satisfied AI preferences

·Redwood Research··

A central AI safety concern is that AIs will develop unintended preferences and undermine human control to achieve them. But some unintended preferences are cheap to satisfy, and failing to satisfy them needlessly turns a cooperative situation into an adversarial one. In this post, I argue that developers should consider satisfying such cheap-to-satisfy preferences as long as the AI isn’t caught behaving dangerously, if doing so doesn’t degrade usefulness or substantially risk making the AI more...

Read full article →

Related Articles

Loss of Oversight: How AI Systems May Become Harder to Audit, Monitor, and Investigate
Jordan Taylor · LessWrong · 36m ago
The Case for Evaluating Model Behaviors
jsteinhardt · Alignment Forum · 20h ago
Mechanistic estimation for expectations of random products
Jacob Hilton · ARC · 5d ago
Multipolar Civilisation Depends on Maintaining an Attacker’s Dilemma
Naci Cankaya · LessWrong · 14d ago
Using Base-LCM to Monitor LLMs
Éloïse Benito-Rodriguez · LessWrong · 14d ago