AI, Language, and the Uncanny Valley
We experience vertigo in the uncanny valley because we’ve spent hundreds of thousands of years fine-tuning our nervous systems to read and respond to the subtlest cues in real faces. We perceive when someone’s eyes squint into a smile, or how their face flushes from the cheeks to the forehead, and we also — at least subconsciously — perceive the absence of these organic barometers. Simulations make us feel like we’re engaged with the nonliving, and that’s creepy.
That's an excerpt from Douglass Rushkoff's book, Team Human, talking about how the uncanny valley is our best defense. The uncanny valley is that special place where computer simulations, particularly of humans, come close-but-not-quite-close enough and therefor trigger an ick reaction (like the almost-humans in Polar Express or creepy Princess Leia in Rogue One).
The quest for AI runs right through the uncanny valley, although sometimes the ick factor is less about uneasiness and more about cars that don't drive themselves where you want them to. The gap between what AI promises and what it can deliver is at least as large as an uncanny valley, though companies like Google are now trying to build a fluffy PR bridge over it (hence Google's directive that researchers "strike a positive tone" in their write-ups).
Since summer, journalists have been gushing glowingly over GPT-3, the newest level of AI powered language simulation (the New York Times has now gushed twice in six months). It was the late seventies when I heard a professor explain that the search for decent language synthesizing software and artificial intelligence were inexorably linked, and that seems to still be true.
It's important to understand what AI, or to call it by its current true name, machine learning, CONTINUE READING: CURMUDGUCATION: AI, Language, and the Uncanny Valley
