How to Give A.I. a Pinch of Consciousness
A.I. researchers are turning to neuroscience to build smarter, more powerful neural networks
In 1998, an engineer in Sony’s computer science lab in Japan filmed a lost-looking robot moving trepidatiously around an enclosure. The robot was tasked with two objectives: avoid obstacles and find objects in the pen. It was able to do so because of its ability to learn the contours of the enclosure and the locations of the sought-after objects.
But whenever the robot encountered an obstacle it didn’t expect, something interesting happened: Its cognitive processes momentarily became chaotic. The robot was grappling with new, unexpected data that didn’t match its predictions about the enclosure. The researchers who set up the experiment argued that the robot’s “self-consciousness” arose in this moment of incoherence. Rather than carrying on as usual, it had to turn its attention inward, so to speak, to decide how to deal with the conflict.
This idea about self-consciousness — that it asserts itself in specific contexts, such as when we are confronted with information that forces us to reassess our environment and then make an executive decision about what to do next — is an old one, dating back to the work of the German philosopher Martin Heidegger in the early 20th…
