2019 was a great year for seeing what AI could do. Waymo deployed self-driving taxis to actual paying customers in Arizona. Bots from OpenAI and DeepMind beat the top professionals in two major esports games. A deep-learning algorithm performed as well as doctors—and sometimes better—at spotting lung cancer tumors in medical imaging.
But as for what AI should do, 2019 was terrible. Amazon’s facial recognition software? Racist, according to MIT researchers, who reported that the tech giant’s algorithms misidentify nearly a third of dark-skinned women’s faces (while demonstrating near-perfect accuracy for light-skinned men’s). Emotion detection, used by companies such as WeSee and HireVue to perform threat assessments and screen job applicants? Hogwash, says the Association for Psychological Science. Even the wonky field of natural language processing took a hit, when a state-of-the-art system called GPT-2—capable of generating hundreds of words of convincing text after only a few phrases of prompting—was deemed too risky to release by its own creators, OpenAI, which feared it could be used “maliciously” to propagate fake news, hate speech, or worse.
2019, in other words, was the year that two things became unavoidably clear about the rocket ship of innovation called artificial intelligence. One: It’s accelerating faster than most of us expected. Two: It’s got some serious screws loose.
That’s a scary realization to have, given that we’re collectively strapped into this rocket instead of watching it from a safe distance. But AI’s anxiety-inducing progress has an upside: For perhaps the first time, the unintended consequences of a disruptive technology are visible in the moment, instead of years or even decades later. And that means that while we may be moving too quickly for comfort, we can actually grab the throttle—and steer.
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