It’s well known that all “artificial intelligence” systems are sharply limited in their domain. IBM’s chess playing Deep Blue doesn’t drive a car. But what happens when the domain itself begins a tectonic shift?
[Changing patterns of web searches] have also affected artificial intelligence, causing hiccups for the algorithms that run behind the scenes in inventory management, fraud detection, marketing, and more. Machine-learning models trained on normal human behavior are now finding that normal has changed, and some are no longer working as they should.
How bad the situation is depends on whom you talk to. According to Pactera Edge, a global AI consultancy, “automation is in tailspin.” Others say they are keeping a cautious eye on automated systems that are just about holding up, stepping in with a manual correction when needed.
What’s clear is that the pandemic has revealed how intertwined our lives are with AI, exposing a delicate codependence in which changes to our behavior change how AI works, and changes to how AI works change our behavior. This is also a reminder that human involvement in automated systems remains key. “You can never sit and forget when you’re in such extraordinary circumstances,” says [Rael Cline, CEO of algorithmic advertising consultancy Nozzle]. [MIT Technology Review]
I wonder which of the AI developers are trying to train their systems to predict such shifts, based on human-centered news sources, for purposes of training their systems to shift on the predicted path of change.
That would be another step along the path to self-agency, don’t you think?
In the meantime, I’m feeling just a bit like an insect under a microscope.
