Think economics of ecologies. Coherence in terms of the average mutual information of the paths of trophic I/O provides a measure of relative ecological effectiveness (absent prediction or agency.) Map this onto the information I/O of a self-organizing hierarchical Bayesian causal model (with, for example, four major strata for human-level environmental complexity) and you should expect predictive capability within a particular domain, effective in principle, in relation to the coherence of the hierarchical model over its context.
As to comparative evaluation of the intelligence of such models without actually running them, I suspect this is similar to trying to compare the intelligence of phenotypical organisms by comparing the algorithmic complexity of their DNA.
My (not so “fake”) hint:
Think economics of ecologies. Coherence in terms of the average mutual information of the paths of trophic I/O provides a measure of relative ecological effectiveness (absent prediction or agency.) Map this onto the information I/O of a self-organizing hierarchical Bayesian causal model (with, for example, four major strata for human-level environmental complexity) and you should expect predictive capability within a particular domain, effective in principle, in relation to the coherence of the hierarchical model over its context.
As to comparative evaluation of the intelligence of such models without actually running them, I suspect this is similar to trying to compare the intelligence of phenotypical organisms by comparing the algorithmic complexity of their DNA.