Google has always been an artificial intelligence company, so it really shouldn’t have been a surprise that Ray Kurzweil, one of the leading scientists in the field, joined the search giant late last year. Nonetheless, the hiring raised some eyebrows, since Kurzweil is perhaps the most prominent proselytizer of “hard AI,” which argues that it is possible to create consciousness in an artificial being. Add to this Google’s revelation that it is using techniques of deep learning to produce an artificial brain, and a subsequent hiring of the godfather of computer neural nets Geoffrey Hinton, and it would seem that Google is becoming the most daring developer of AI, a fact that some may consider thrilling and others deeply unsettling. Or both.

On Tuesday, Kurzweil moderated a live Google hangout tied to a release of the upcoming Will Smith film, After Earth, presumably tying the film’s futuristic concept to actual futurists. The discussion touched on the necessity of space travel and the imminent resolution of the world’s energy problems with solar power. After the hangout, Kurzweil got on the phone with me to explore a few issues in more detail.

__WIRED: In the Google hangout you just finished, Will Smith said he had a copy of your book by his bedside because he’s been involved in a number of science fiction movies. How do you view science fiction? __

RAY KURZWEIL: Science fiction is the great opportunity to speculate on what could happen. It does give me, as a futurist, scenarios. It’s not incumbent upon science fiction creators to be realistic about time frames and so on. In this movie, for example, the characters come back to Earth a thousand years later and biological evolution has moved so far that the animals are quite different. That’s not realistic. Also, there’s very often a dystopian bent to science fiction because we can perceive the dangers of science more than the benefits, and maybe that makes more dramatic storytelling. A lot of movies about artificial intelligence envision that AI’s will be very intelligent but missing some key emotional qualities of humans and therefore turn out to be very dangerous.

What’s the key to predicting the future?

I realized 30 years ago that the key to being successful is timing. I get a lot of new technology proposals, and I’d say 95% of those teams will build exactly what they claim if given the resources, but 95% of those projects will fail because the timing is wrong I did anticipate, for instance, that search engines would start emerging. Fifteen years ago Larry Page and Sergey Brin were in exactly the right place at the right time with the right idea

You anticipated search engines?

Yes. I wrote about that actually as early as The Age of Intelligent Machines, in the 1980s. [The book was published in 1990.]

But did you predict that you would be working for a company that started as a search engine?

That’s exactly the kind of thing you can’t predict. It would be very hard to predict that these couple of kids at Stanford would take over the world of search. But what I did discover is that if you examine the key measures of price performance and capacity of information technology, they form amazingly predictable smooth exponential curves. The price performance of computation has been rising in a very smooth exponential since the 1890 census. This has gone on through thick and thin, through war and peace, and nothing has affected it. I projected it out to 2050. In 2013, we’re exactly where we should be on that curve.

What are you working on at Google?

My mission at Google is to develop natural language understanding with a team and in collaboration with other researchers at Google. Search has moved beyond just finding keywords, but it still doesn’t read all these billions of web pages and book pages for semantic content. If you write a blog post, you’ve got something to say, you’re not just creating words and synonyms. We’d like the computers to actually pick up on that semantic meaning. If that happens, and I believe that it’s feasible, people could ask more complex questions.

Are you participating in Jeff Dean’s program there to build an artificial "Google Brain?"

Well, Jeff Dean is one of my collaborators. He’s a fellow research leader. We are going be using his systems and his techniques of deep learning. The reason I’m at Google is resources like that. Also the knowledge graph and very advanced syntactic parsing and a lot of advanced technologies that I really need for a project that really seeks to understand natural language. I can succeed at this much more readily at Google because of these technologies.

If your system really understood complex natural language, would you argue that it’s conscious?

Well, I do. I’ve had a consistent date of 2029 for that vision. And that doesn’t just mean logical intelligence. It means emotional intelligence, being funny, getting the joke, being sexy, being loving, understanding human emotion. That’s actually the most complex thing we do. That is what separates computers and humans today. I believe that gap will close by 2029.

Will we get there simply by more computation and better software, or are there currently unsolved barriers that we have to hurdle?

There are both hardware and software requirements. I believe we actually are very close to having the requisite software techniques. Partly this is being assisted by understanding how the human brain works, and we’re making exponential gains there. We can now see inside a living brain and see individual inter-neural connections being formed and firing in real time. We can see your brain create your thoughts and thoughts create your brain. A lot of this research reveals how the mechanism of the neocortex works, which is where we do our thinking. This provides biologically inspired methods that we can emulate in our computers. We’re already doing that. The deep learning technique that I mentioned uses multilayered neural nets that are inspired by how the brain works. Using these biologically inspired models, plus all of the research that’s been done over the decades in artificial intelligence, combined with exponentially expanding hardware, we will achieve human levels within two decades.

Do we really understand at all why someone’s brain can result in such an unique expression of a human? Take the transcendent intelligence of Einstein, the creativity of Steve Jobs, or the focus of Larry Page. What made those people so special? Do you have insights into that?

I examine that very question, in fact, with regard to Einstein specifically in my recent book, How to Create a Mind.

Tell me.

There are two things. First of all, we create our brain with our thoughts. We have a limited capacity in the neocortex, estimated to be about 300 million pattern recognizers, which are organized in a hierarchy. We create that hierarchy with our own thinking. I would not explain Einstein’s brilliance based on him having 350 million or 400 million. We have approximately the same capacity. But he organized his brain to think deeply about this one subject. He was interested in the violin, but he was no Jascha Heifetz. And Jascha Heifetz had an interest in physics, but he was no Einstein. We have a capacity to do world-class work in one field. That’s part of the limited capacity of the brain, and Einstein really devoted it to this one field.

But lot of physicists are devoted to their one field, and only one became Einstein.

I didn’t finish. The other aspect is courage to follow your own thought experiments and not fall off the horse because the conclusions are so different from your previous assumptions or the common belief of society. People are so unable to accept thinking different than their peers that they immediately drop their thought pattern when it leads to absurd conclusions. So there’s a certain courage to go with your convictions. Clearly Steve Jobs had that. He had a vision and carried it out. It’s that courage of your convictions.

What’s the biological basis for that kind of courage? If you had an infinite ability to analyze a brain, could you say, “Oh, here’s where the courage is?”

It is the neocortex, and people who fill up too much of their neocortex with concern about the approval of their peers are probably not going be the next Einstein or Steve Jobs.

Is this something one can control?

That’s a good question. I’ve been thinking about that and also why do some people readily accept the exponential growth of information technology and its implications, and other people are very resistant to it. I make the argument that hard-wired in our brain are linear expectations, because that worked very well 1000 years ago, tracking an animal in the wild. Some people, though, can readily accept the exponential perspective when you show them the evidence, and other people don’t. I’m trying to answer the question, what accounts for that? It really isn’t accomplishment level, intelligence, education level, socio-economic status. It cuts across all of those things. Some people’s neocortexes are organized so that they can accept the implications that they see in front of them without worrying too much about the opinion of others. Can we learn that? I would imagine yes, but I don’t have data to prove that.

Since we’ve been talking about Steve Jobs, let me bring up one of his famous quotes, from his speech at Stanford. He said, “Death is very likely the single best invention of life. It’s life’s change agent.” You are very famously trying to extend your life indefinitely, so you reject that, right?

Yes, This is what I call a deathist statement, part of a millennium-old rationalization of death as a good thing. It once seemed to make sense, because up until very recently you could not make a plausibly sound argument where life could be indefinitely extended. So religion, which emerged in prescientific times, did the next best thing, which is to say, ‘Oh, that tragic thing? That’s really a good thing.” We rationalized that because we did have to accept it. But in my mind death is a tragedy. Our initial reaction to hearing that someone has died is a profound loss of knowledge and skill and talents and relationships. It’s not the case that there are only a fixed number of positions, and if old people don’t die off, there’s no room for young people to come up with new ideas, because we’re constantly expanding knowledge. Larry Page and Sergey Brin didn’t displace anybody– they created a whole new field. We see that constantly. Knowledge is growing exponentially. It’s doubling approximately every year.

And you think that dramatically extended life is possible.

I think we’re only 15 years away from a tipping point in longevity.