Google is placing a lot of importance on engaging with governments across the world, even amid tensions around artificial intelligence, privacy and fake news, according to one of the company’s top engineers.
Alphabet’s top computer scientists, told CNBC’s Josh Lipton on Tuesday.
“Obviously tech companies have a lot of expertise in this space. We can offer advice and our views of where the technology is going what impact that might have in the broader society. And I think you want governments to be thinking carefully about what the implications of these technologies will be five, 10 years down the road. That seems like a helpful dialogue to have.”
Meanwhile, in Washington, Donald Trump’s administration has been planning a summit on artificial intelligence with representatives from Google, plus Amazon, Facebook, Intel and 34 other major U.S. companies, according to The Washington Post.
Dean is a company veteran, joining the company when it had 25 employees in 1999. He’s led Google Brain since 2012, where he researches artificial intelligence. Google’s top brass, including Sundar Pichai and Sergey Brin, have long maintained that artificial intelligence is the future of the company.
But critics of artificial intelligence have also warned that it has the ability to take workers’ jobs. Dean counters that Google actually aims to make humans more productive and improve their experiences with technology.
“We want to make users more productive and a lot of time is spent in email writing things that are relatively straightforward. A really smart person looking over your shoulder would probably be able to guess about what you’re going to write in the next sentence. We want to make the system able to do this for you,” Dean said.
There are a lot of positive ways that regulators and technologists can work together, Dean said, particularly in the healthcare field which can “benefit everyone in the world.”
Google’s technologies are discovering new types of things that doctors didn’t even realize were present in visual data, such as getting clues about heart health from retinal scans instead of blood draws, Dean said.
“The healthcare space is a very complicated one for a variety of reasons: It’s much more regulated than some other kinds of industries, for good reason,” Dean said.
“You want to deploy these sorts of systems in a safe and methodical manner. But I think it’s also important also to get these benefits out as soon as regulatorily possible. It is still pretty early. I think the fact that machine learning is really starting to work on practical problems is a relatively recent phenomenon and I think we’ll see more and more of this in healthcare and other industries.”