Scott explains why he's not interested in participating in the current wave of God debates on Substack, arguing that religious explanations fall into the same category as conspiracy theories by invoking "powerful hidden entities" to explain anomalies. Longer summary

Scott discusses his lack of interest in the resurgent religion debates on Substack, comparing religious explanations to a hypothetical theory that aliens caused Napoleon's rise. He argues that God explanations suffer from the same overfitting problem as conspiracy theories—they invoke powerful hidden entities to explain specific outcomes while being unfalsifiable. The post critiques the "divine simplicity" argument that God is simple because He is "mind without limits," showing this is a sleight-of-hand that confuses removing limits with reducing complexity. Scott also challenges computational dualism, arguing that computation clearly happens in the physical brain based on extensive evidence from neuroscience, which undermines the claim that "mind" exists on an exotic substrate that could support infinite capabilities. Shorter summary

Scott Alexander examines the 'canalization' theory in computational psychiatry and its refinement through deep learning concepts in the Deep CANAL model. Longer summary

Scott Alexander discusses a new paradigm in computational psychiatry called 'canalization', which models mental processes as an energy landscape with valleys representing attractors or persistent beliefs/behaviors. He then explores a follow-up paper that applies concepts from deep learning to refine this theory, introducing the Deep CANAL model. This model attempts to explain various mental disorders by mapping them onto different types of computational issues in artificial neural networks, such as overfitting/underfitting and the stability/plasticity dilemma. Scott expresses both interest and skepticism about this approach, noting its potential insights but also its limitations and potential contradictions with other theories. Shorter summary