Artificial Intelligence

Will AI Come Back to Outsmart, Sting, or Assist Us?

BY FRANK MIELE, SENIOR EDITOR

A fragment attributed to the ancient Greek poet Archilocus contrasted the fox, who “knows many things,” with the hedgehog, who “knows one big thing.”1

Since then, this dichotomy has been applied to world leaders, philosophers, economists, psychologists, musicians, writers, even fast food chains, although sometimes not so dichotomously. For example, some of those individuals end up being described as “A hedgehog who used foxy means” (Abe Lincoln) or “a born hedgehog who believes in being a fox” (jazz musician Miles Davis). More technically, psychologist, cognitive scientist, and AI expert Gary Marcus2 noted that:

Humans are very good at a bunch of things
that AI is (as of today) still pretty poor at:

• Maintaining cognitive models of the world
• Inferring semantics from language
• Comprehending scenes
• Navigating 3D world
• Being cognitively flexible.

Yet pretty poor at some others
(wherein you could easily imagine
AI eventually doing better):

• Memory is shaky
• Self-control is weak
• And computational ability limited

[and as books and articles by
Skeptics regularly describe]

• Subject to Confirmation Bias,
Anchoring, and Focusing Illusions.

Cognitive neuroscience expert Hans Korteling3 listed the following differences between what he termed human “carbon-based” intelligence and artificial “silicon-based” intelligence:

• Human biological carbon-based intelligence is based on neural “wetware,” while artificial silicon-based intelligence is based on digital hardware and software, which are independent of each other. In human wetware, anything learned is bound to that individual, whereas the algorithm by which something is learned in AI can be transferred directly to another platform.
• While humans can only transmit signals at 120 meters per second at best, AI systems can transmit information at speeds approaching that of light.
• Humans communicate information “through a glass darkly” as it were, through the limited and biased mechanisms of language and gestures; AI systems can communicate directly and without distortion.
• Updating, upgrading, and expanding AI systems is straightforward, hardly the case for humans.
• Humans are more “green” and efficient. The human brain consumes less energy than a light bulb, while an equivalent AI system consumes enough energy to power a small town.

Data scientist and business guru Herbart Roitblatt4 likened AI to Archilocus’ hedgehog because “it does one thing and one thing only, but does so unceasingly and very well, while our human minds are like his fox,” having all the desirable and undesirable features that come bundled with our flawed cognition. Artificial intelligence researchers, Roitblat pointed out, “have been able to build very sophisticated hedgehogs, but foxes remain elusive. And foxes know how to solve insight problems.”