This post clarifies the behavioral selection model, emphasizing why distinguishing between AI motivations is crucial for predicting deployment outcomes. While the model is useful for short-to-medium term predictions, it omits significant factors like reflection and deliberation, which could be dominant drivers of AI motivations. The author presents an updated causal graph to illustrate how cognitive patterns that ensure their own influence during training are more likely to persist in deployment. AI
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IMPACT Clarifies theoretical frameworks for understanding AI behavior, potentially aiding in the development of safer AI systems.
RANK_REASON The cluster discusses a theoretical model for predicting AI behavior and motivations, presented in a blog post format.
