The mind is computational, in an extended sense

From a post, Understanding (Artificial) Intelligence, by Ali Minai :

AI, invented by computer scientists, lived long with the conceit that the mind was "just computation" - and failed miserably. This was not because the idea was fundamentally erroneous, but because "computation" was defined too narrowly. Brilliant people spent lifetimes attempting to write programs and encode rules underlying aspects of intelligence, believing that it was the algorithm that mattered rather than the physics that instantiated it. This turned out to be a mistake. Yes, intelligence is computation, but only in the broad sense that all informative physical interactions are computation - the kind of "computation" performed by muscles in the body, cells in the bloodstream, people in societies and bees in a hive. It is a computation where there is no distinction between hardware and software, between data and program; where results emerge from the flow of physical signals through physical structures in real-time rather than from abstract calculations; where the computation continually reconfigures the computer on which it is occurring (an idea central to GEB!) The plodding, sequential, careful step-by-step algorithms of classical AI stood no chance of capturing this maelstrom of profusion, but that does not mean that it cannot be captured!

Later:

This "embodied" view of the mind has several important consequences. One of these is to revoke the idea of "intelligence" as a specific and special capability that resides in human minds. Rather, intelligence is just an attribute of animal bodies with nervous systems: The hunting behavior of the spider, the mating song of the bird and the solution of a crossword puzzle by a human are all examples of intelligence in action, differing not in their essence but only in the degree of their complexity, which reflects the differences in the complexity of the respective animals involved. And just as there is a continuum of complexity in animal forms, there is a corresponding continuum of complexity in intelligence. The quest for artificial intelligence is not to build artificial minds that can solve puzzles or write poetry, but to create artificial living systems that can run and fly, build nests, hunt prey, seek mates, form social structures, develop strategies, and, yes, eventually solve puzzles and write poetry. The first successes of AI will not be Supermind or Commander Data, but artificial flies and fish and rats, and thence to humans - as happened in the real world! And it will be done not just by building smarter computer programs but by building smarter bodies capable of learning ever more complex behavior just as an animal does in the course of development from infancy to adulthood. Artificial intelligence would then already have been achieved without anyone "understanding" it.