The above-mentioned researchers are skeptical in different ways. Andrew Ng thinks that human-level AI is ridiculously far away, and that trying to predict the future more than 5 years out is useless. Yann LeCun and Yoshua Bengio believe that advanced AI is far from imminent, but approve of people thinking about long-term AI safety.

Okay, but surely it’s still important to think now about the eventual consequences of AI. - Absolutely. We ought to be talking about these things.

+1 To go even further, I would add that it's unproductive to think of these researchers as being on anyone's "side". These are smart, nuanced people and rounding their comments down to a specific agenda is a recipe for misunderstanding.

Yoshua Bengio on AI progress, hype and risks

by V_V 1 min read30th Jan 20168 comments



Yoshua Bengio, one the world's leading expert on machine learning, and neural networks in particular, explains his view on these issues in an interview. Relevant quotes:

There are people who are grossly overestimating the progress that has been made. There are many, many years of small progress behind a lot of these things, including mundane things like more data and computer power. The hype isn’t about whether the stuff we’re doing is useful or not—it is. But people underestimate how much more science needs to be done. And it’s difficult to separate the hype from the reality because we are seeing these great things and also, to the naked eye, they look magical

[ Recursive self-improvement ] It’s not how AI is built these days. Machine learning means you have a painstaking, slow process of acquiring information through millions of examples. A machine improves itself, yes, but very, very slowly, and in very specialized ways. And the kind of algorithms we play with are not at all like little virus things that are self-programming. That’s not what we’re doing.

Right now, the way we’re teaching machines to be intelligent is that we have to tell the computer what is an image, even at the pixel level. For autonomous driving, humans label huge numbers of images of cars to show which parts are pedestrians or roads. It’s not at all how humans learn, and it’s not how animals learn. We’re missing something big. This is one of the main things we’re doing in my lab, but there are no short-term applications—it’s probably not going to be useful to build a product tomorrow.

We ought to be talking about these things [ AI risks ]. The thing I’m more worried about, in a foreseeable future, is not computers taking over the world. I’m more worried about misuse of AI. Things like bad military uses, manipulating people through really smart advertising; also, the social impact, like many people losing their jobs. Society needs to get together and come up with a collective response, and not leave it to the law of the jungle to sort things out.

I think it's fair to say that Bengio has joined the ranks of AI researchers like his colleagues Andrew Ng and Yann LeCun who publicly express skepticism towards imminent human-extinction-level AI.