Is Everything You Think You Know About AI Wrong?

WaPo |  consumers are already seeing our machine learning research reflected in the sudden explosion of digital personal assistants like Siri, Alexa and Google Now — technologies that are very good at interpreting voice-based requests but aren't capable of much more than that. These "narrow AI" have been designed with a specific purpose in mind: To help people do the things regular people do, whether it's looking up the weather or sending a text message.

Narrow, specialized AI is also what companies like IBM have been pursuing. It includes, for example, algorithms to help radiologists pick out tumors much more accurately by "learning" all the cancer research we've ever done and by "seeing" millions of sample X-rays and MRIs. These robots act much more like glorified calculators — they can ingest way more data than a single person could hope to do with his or her own brain, but they still operate within the confines of a specific task like cancer diagnosis. These robots are not going to be launching nuclear missiles anytime soon. They wouldn't know how, or why. And the more pervasive this type of AI becomes, the more we'll understand about how best to build the next generation of robots.

So who is going to lose their job?

Partly because we're better at designing these limited AI systems, some experts predict that high-skilled workers will adapt to the technology as a tool, while lower-skill jobs are the ones that will see the most disruption. When the Obama administration studied the issue, it found that as many as 80 percent of jobs currently paying less than $20 an hour might someday be replaced by AI.

"That's over a long period of time, and it's not like you're going to lose 80 percent of jobs and not reemploy those people," Jason Furman, a senior economic advisor to President Obama, said in an interview. "But [even] if you lose 80 percent of jobs and reemploy 90 percent or 95 percent of those people, it's still a big jump up in the structural number not working. So I think it poses a real distributional challenge."

Policymakers will need to come up with inventive ways to meet this looming jobs problem. But the same estimates also hint at a way out: Higher-earning jobs stand to be less negatively affected by automation. Compared to the low-wage jobs, roughly a third of those who earn between $20 and $40 an hour are expected to fall out of work due to robots, according to Furman. And only a sliver of high-paying jobs, about 5 percent, may be subject to robot replacement.

Those numbers might look very different if researchers were truly on the brink of creating sentient AI that can really do all the same things a human can. In this hypothetical scenario, even high-skilled workers might have more reason to fear. But the fact that so much of our AI research right now appears to favor narrow forms of artificial intelligence at least suggests we could be doing a lot worse.