What are the elements, operations, overlaps, constraints, limitations, and differences between the “artificial” cognition done by machines and the “natural” cognition performed by humans?

As Professor Turner argues, AI seems to have evident advantages: the systems are tireless, unneedy (well, except for huge amounts of energy resources), seemingly immortal (but maybe not quite?) and seemingly reliably replicable across countless instances. They seem nearly infallible in memory retention, capable of training each other, and can certainly handle and analyze vast datasets that the world’s entire research community could not encounter in a lifetime, much less study and analyze. AI procedures can operate computationally in ways that are alien to human cognition, using methods of problem-solving – or at least of calculation – that a human being cannot.

On the other hand, he can remind us, all human beings can act creatively in everyday situations, adapting and innovating in ways that AI cannot so far mimic, and such creativity rather than being remarkable is part of normal human performance. I would add that there are elements of judgment that cannot be reduced to calculation; that trying to resolve value conflicts based on some sort of calculation does not sound at all like a good idea; and that the processes of induction from comparing things might be mimicked through AI but I have no idea how one would judge the effectiveness of such “reasoning.” The bottom line, as Professor Turner e-mailed me, is that “artificial and natural intelligence should both be used for what they are good for; they do have some intersection;” but they remain quite different.

Please join us as Professor Turner launches a discussion of present realities and future opportunities in areas such as decision-making, multimodal communication, linguistics, reasoning, complex problem-solving, law, medicine, biology, and education.

Best wishes for safety and security for you and yours,