
#76 – Joe Carlsmith on Scheming AI
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Exploring Simplicity and Scheming in AI Models
The chapter delves into the complex concept of simplicity in AI models, discussing simplicity in relation to encoding, optimization, and inductive biases. It touches on the debate between simplicity and counting arguments, examining the role of biases like simplicity bias in preventing overfitting. The dialogue also explores the implications of scheming AI models, comparing cognitive efforts, risks, and benefits associated with deception in AI.
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