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People worry about the scenario in which AIs take over. I think something much more amusing, in a sense, will happen first. The AI will know what you intend, and it will be good at figuring out how to get there. I tell my car’s GPS I want to go to a particular destination. I don’t know where the heck I am, I just follow my GPS. My children like to remind me that once when I had a very early GPS—the kind that told you, “Turn this way, turn that way”—we ended up on one of the piers going out into Boston Harbor.

More to the point is that there will be an AI that knows your history, and knows that when you’re ordering dinner online you’ll probably want such-and-such, or when you email this person, you should talk to them about such-and-such. More and more, the AIs will suggest to us what we should do, and I suspect most of the time people will just go along with that. It’s good advice—better than what you would have figured out for yourself.

As far as the takeover scenario is concerned, you can do terrible things with technology and you can do good things with technology. Some people will try to do terrible things with technology, and some people will try to do good things with technology. One of the things I like about today’s technology is the equalization it has produced. I used to be proud that I had a better computer than anybody I knew; now we all have the same kind of computers. We have the same smartphones, and pretty much the same technology can be used by a decent fraction of the planet’s 7 billion people. It’s not the case that the king’s technology is different from everybody else’s. That’s an important advance.

The great frontier five hundred years ago was literacy. Today, it’s doing programming of some kind. Today’s programming will be obsolete in a not very long time. For example, people no longer learn assembly language, because computers are better at writing assembly language than humans are, and only a small set of people need to know the details of how language gets compiled into assembly language. A lot of what’s being done by armies of programmers today is similarly mundane. There’s no good reason for humans to be writing Java code or JavaScript code. We want to automate the programming process so that what’s important goes from what the human wants done to getting the machine, as automatically as possible, to do it. This will increase that equalization, which is something I’m interested in. In the past, if you wanted to write a serious piece of code, or program for something important and real, it was a lot of work. You had to know quite a bit about software engineering, you had to invest months of time in it, you had to hire programmers who knew this or you had to learn it yourself. It was a big investment.

That’s not true anymore. A one-line piece of code already does something interesting and useful. It allows a vast range of people who couldn’t make computers do things for them, make computers do things for them. Something I’d like to see is a lot of kids around the world learn the new capabilities of knowledge-based programming and then produce code that’s effectively as sophisticated as what anybody in the top ranks can produce. This is within reach. We’re at the point where anybody can learn to do knowledge-based programming, and, more important, learn to think computationally. The actual mechanics of programming are easy now. What’s difficult is imagining things in a computational way.

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