Or a corollary to the title: Why a computer will never function intelligently.

Mihai Nadin wrote a brilliant paper titled: Machine intelligence: a chimera.
It can be accessed and read here on Springer.
Nadin, M. AI & Soc (2019) 34: 215. https://doi.org/10.1007/s00146-018-0842-8

Abstract

The notion of computation has changed the world more than any previous expressions of knowledge. However, as know-how in its particular algorithmic embodiment, computation is closed to meaning. Therefore, computer-based data processing can only mimic life’s creative aspects, without being creative itself. AI’s current record of accomplishments shows that it automates tasks associated with intelligence, without being intelligent itself. Mistaking the abstract (computation) for the concrete (computer) has led to the religion of “everything is an output of computation”—even the humankind that conceived the computer. The hypostatized role of computers explains the increased dependence on them. The convergence machine called deep learning is only the most recent form through which the deterministic theology of the machine claims more than what it actually is: extremely effective data processing. A proper understanding of complexity, as well as the need to distinguish between the reactive nature of the artificial and the anticipatory nature of the living are suggested as practical responses to the challenges posed by machine theology.

Several quotes from his paper:

If nothing else can be derived from these accepted discoveries, one statement stands out: human beings, in their quest for understanding the world, constitute themselves through their activities, testimony of their abilities. They prove theorems, but not in a mechanical (i.e., machine-based) manner. Moreover, they are not subject to the infinite loop of the halting problem: that is, can a computer recognize when the program’s task is finished (or will it continue to process indefinitely)? The human being—and for that matter any form of life, independent of the activity through which it expresses itself—would halt. In other words, it understands whatever is performed and stops, either when it cannot achieve what it wants or after achieving it. Based on these two observations, one can infer: (1) contrary to statements made since Dartmouth, human beings are not reducible to algorithmic machines; and (2) a science of the human being transcends the algorithmic description.

For suggesting that computers, in whichever form, could not do something—whatever that might be—Dreyfus and Weizenbaum and many others were treated like intellectual Luddites. For ascertaining that the brain is not a computer and intelligence is more than solving problems based on rules, such authors were ridiculed by colleagues enjoying positions of authority. The fact that none of them realized what Turing, Church, and especially Gödel established: there are tasks for which the algorithmic, at least in its current expression, is not adequate. In the spirit in which determinism was hypostatized and became the religion of science, some of Dreyfus’s and Weizenbaum’s colleagues effectively deified the Turing machine. The various commandments attributed to the deity by the humans who constructed it (in search of answers to questions for which no better answers could be given at the time) formalize this religion. Churches promote such commandments as divine. In a strange parallel development, Descartes’s views, proclaimed but never proven, gave rise to the theology of reductionism and determinism embodied in the machine, and now extended to one particular type: the Turing machine. There is historic precedent to this: the hypostatized brain as made of clay infused with spirit; the brain as a hydraulic machine (the humors, fluids running though the machine); the mechanical automata model (more like a clock); Hobbes’s mechanical motion brain; Helmholtz’s “neural network,” pretty much like the telegraph; the brain as a quantum computer. It never ends (Zarkadakis 2015). The obsession with reducing the brain to the machine-du-jour is as understandable as it is infantile.

The model that AI adopted and which Dreyfus analyzed was proven wrong by those studying physiology and the motoric system, the brain, and everything else embodied in the living (human, plant, animal).

In a short article (1887a, b), Peirce makes reference to Gulliver’s Voyage to Laputa.

In the “Voyage to Laputa” there is a description of a machine for evolving science automatically. “By this contrivance, the most ignorant person, at a reasonable charge, and with little bodily labor, might write books in philosophy, poetry, politics, laws, mathematics, and theology, without the least assistance from genius or study”