The behavioral selection model distinguishes between identical AI behaviors driven by different underlying motivations. This distinction determines whether a model remains stable or fails during deployment. The author notes that while the model predicts short-term motivations, it ignores critical long-term dynamics. Practitioners must disambiguate these drivers to ensure reliable alignment.