I am going to write the same warning I have written to rationalist friends in relation to the Great Filter Hypothesis and almost everything on Overcoming Bias: BEWARE OF MODELS WITH NO CAUSAL COMPONENTS! I repeat: BEWARE NONCAUSAL MODELS!!! In fact, beware of nonconstructive mental models as well, while we're at it! Beware classical logic, for it is nonconstructive! Beware noncausal statistics, for it is noncausal and nonconstructive! All these models, when they contain true information, and accurately move that information from belief to belief in strict accordance with the actual laws of statistical inference, still often fail at containing coherent propositions to which belief-values are being assigned, and at corresponding to the real world.

Can you explain this part more?