 Second, we now know well (and those familiar with the relevant formal terrain knew at the time of Dennett’s writing) that information processing can exceed standard computation, that is, can exceed computation at and below the level of what a Turing machine can muster (Turing-computation, we shall say). (Such information processing is known as hypercomputation, a term coined by philosopher Jack Copeland, who has himself defined such machines (e.g., Copeland 1998). The first machines capable of hypercomputation were trial-and-error machines, introduced in the same famous issue of the Journal of Symbolic Logic (Gold 1965; Putnam 1965). A new hypercomputer is the infinite time Turing machine (Hamkins &amp; Lewis 2000).) Dennett’s appeal to Church’s thesis thus flies in the face of the mathematical facts: some varieties of information processing exceed standard computation (or Turing-computation). Church’s thesis, or more precisely, the Church-Turing thesis, is the view that a function \(f\) is effectively computable if and only if \(f\) is Turing-computable (i.e., some Turing machine can compute \(f\)). Thus, this thesis has nothing to say about information processing that is more demanding than what a Turing machine can achieve. (Put another way, there is no counter-example to CTT to be automatically found in an information-processing device capable of feats beyond the reach of TMs.) For all philosophy and psychology know, intelligence, even if tied to information processing, exceeds what is Turing-computational or  Turing-mechanical.[38]  This is especially true because philosophy and psychology, unlike AI, are in no way fundamentally charged with engineering artifacts, which makes the physical realizability of hypercomputation irrelevant from their perspectives. Therefore, contra Dennett, to consider AI as psychology or philosophy is to commit a serious error, precisely because so doing would box these fields into only a speck of the entire space of functions from the natural numbers (including tuples therefrom) to the natural numbers. (Only a tiny portion of the functions in this space are Turing-computable.) AI is without question much, much narrower than this pair of fields. Of course, it’s possible that AI could be replaced by a field devoted not to building computational artifacts by writing computer programs and running them on embodied Turing machines. But this new field, by definition, would not be AI. Our exploration of AIMA and other textbooks provide direct empirical confirmation of this. 