Measuring Reward-Seeking by Instilling Contrastive Beliefs

·LessWrong··

This is an unofficial automated linkpost. Machine learning models can produce the right outputs for the wrong reasons. Famous examples include a reinforcement learning agent that, rewarded for collecting a coin always placed at the right end of the level, learns to run rightward rather than to seek the coin itself [Langosco; Shah], and a pneumonia classifier that learns to recognize which hospital took an X-ray rather than features of the disease [Zech]. The trained behavior looks correct on the...

Read full article →

Related Articles

Why are European countries moving their gold out of North America?
ranit · Hacker News · 17h ago
Hackers Had a Live Feed of Every ID Verification Company Scanned for over a Year
beardyw · Hacker News · 1d ago
Artificial Analysis Intelligence Index v4.2
nojs · Hacker News · 23h ago
Solving the Jane Street reverse engineering challenge
anitil · Hacker News · 1d ago
Which tools do Claude, Codex and Cursor choose? We measured 17k runs to find out
screm · Hacker News · 2d ago