Tim Hwang, Google's Global Public Policy Lead on AI, discusses European regulatory frameworks governing machine learning.
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Hwang: AutoML could eliminate the need for machine learning specialists
“This emerging research right now, which is using machine learning to train machine learning systems, raises, like, this meta level, where, like, right now there's a lot of handwork that goes into building a model so it learns the right representations, but, li…”
Opinion
Hwang: Open publishing should be the default standard in AI research
“I'm very pro open publishing. Like, I think, like, it should be the default, and it's like, I'm still disputing situations where I'm like, you shouldn't publish on this stuff. Just because like, I think it is actually to the benefit of everybody to know what t…”
Insight
Hwang: The assumption that all automatable tasks will be automated is false
“Everybody always assumes that like, okay, if it can be automated, it definitely will be automated, right? But that's like a fallacy, because in certain cases, like, you may really worry about the security of your systems, right?”
Insight
Hwang: The AI competitive moat is shifting from data to interface design
“The amount of data you need to pull off certain types of machine learning applications is going down over time. And what that tells me is that there might not be necessarily a first-mover advantage in this space, where you may actually have collected a bunch o…”
Insight
Hwang: The public sees non-ML robots as AI, ignoring newsfeeds
“The newsfeed assuredly is AI, right? Like, it uses machine learning. It uses the latest machine learning to do what it does. We don't really think about it as AI, right? Whereas, like, the car is, like I mean, I think a lot of robots kind of fall into this cat…”
Insight
Hwang: US AI regulation is domain-specific while Europe uses broad horizontal rules
“I would say in general, I think the US moves on a very case-by-case basis. So the regulatory mode is basically to say, look, in medical, that seems to be a situation where, like, there's, like, particularly high risks. And like, we want to create a bunch of re…”