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Speaker 1: Now here's a highlight from Coast to Coast AM on iHeartRadio.

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Speaker 1: You know, Martin for it. It would be fair more

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Speaker 1: fair if I had in some way told you that

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Speaker 1: you are being summoned to the radio for your expertise tonight.

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Speaker 1: And I'm probably going to throw you some curves, but

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Speaker 1: I have no diet doubt they're in your strike strike zone.

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Speaker 1: So thank you for agreeing to be a guest on

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Speaker 1: again so soon after the release of your book and

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Speaker 1: the last time you were on Coast to Coast. Sure,

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Speaker 1: thanks for voting me. Okay, So I'm very interested in

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Speaker 1: information robots. We'll put a pin in that for the

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Speaker 1: time being. And and I'll ask you to give a

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Speaker 1: quick synopsis of the most recent book, Rule of the Robots,

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Speaker 1: that just came out in was it September of this year? Yeah,

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Speaker 1: it was so Rule of the Robots, And the subtype

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Speaker 1: of that book is how artificial Intelligence will transform Everything.

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Speaker 1: And really it's a book about artificial intelligence, which will

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Speaker 1: you know, it impacts as physical robots that can do,

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Speaker 1: you know, things that manipulate the environment, but also just

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Speaker 1: as software that has intelligence that can solve problems and

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Speaker 1: learn and so forth, and I I genuinely believe this

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Speaker 1: is going to be our most important technology going forward.

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Speaker 1: It's going to be a technology that truly shapes the world.

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Speaker 1: I think it's going to touch every aspect of our life,

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Speaker 1: our culture, our economy. In many ways, I think it will,

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Speaker 1: you know, AI will come to be like electricity in

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Speaker 1: the sense that it will just be ubiquitous. It will

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Speaker 1: be everywhere, it will touch everything, and well, will you

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Speaker 1: lose your electricity for a day? It has a huge

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Speaker 1: impact on your life, And the same would be true

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Speaker 1: of the applications of artificial intelligence that we're going to deploy.

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Speaker 1: So I think it's it's truly going to be a

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Speaker 1: critical technology. You know, we'll have many many upsides, benefits,

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Speaker 1: and also many dangers and risks that come with it. Well,

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Speaker 1: you know, I think the term I would use here

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Speaker 1: in this in the comparison to electricity is turnkey. It's

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Speaker 1: just going to be there's going to be an expectation

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Speaker 1: and much like turning on an oven, that it will

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Speaker 1: get hot, that we will have this sort of casual

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Speaker 1: relationship with the function of artificial intelligence. But I want

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Speaker 1: to start there because I know that even the definition

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Speaker 1: by some of artificial intelligence is kind of contested territory.

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Speaker 1: What exactly how how do you define artificial intelligences versus

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Speaker 1: just a car engine? Why wouldn't we say a car

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Speaker 1: engine is an example of artificial intelligence? Right? I define

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Speaker 1: it very simply as being a machine or a software

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Speaker 1: system that can solve the kinds of problems that human

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Speaker 1: being solved, you know, using our brains. And the most

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Speaker 1: important aspect of that, at least right now is the

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Speaker 1: ability to learn. Um. And you know, uh, the AI

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Speaker 1: applications that we have often called machine learning do have

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Speaker 1: disability to learn it. When you're doing your introduction earlier,

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Speaker 1: you mentioned the rumba lumba robot. Right now, that robot

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Speaker 1: can learn, it does learn it. It learns the dimensions

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Speaker 1: of the rooms in your house that it's that it's

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Speaker 1: going to vacuum. Right every house is different, um, you know,

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Speaker 1: you don't have to buy a different robot depending on

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Speaker 1: how big the rooms in your house are. It learns

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Speaker 1: that for itself. It explores and makes a map of

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Speaker 1: the room and and then based on that can can

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Speaker 1: vacuum very efficiently. So that's the way way how do

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Speaker 1: we I don't know that I would agree with that.

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Speaker 1: And so this is one of those reasons why I'm

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Speaker 1: stepping in because I think when we say learn, it reacts,

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Speaker 1: But is it really learning in that if I turned

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Speaker 1: it off and turn it back on again, it's going

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Speaker 1: to retain knowledge. Yeah, I believe it really have one personally,

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Speaker 1: but but yeah it does. The expectation is that that

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Speaker 1: it would. Um, I don't think that. Um it's the

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Speaker 1: case that every time you turn a roomba on it's

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Speaker 1: just going around randomly about it is? I think it

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Speaker 1: is because you can, I mean, and this is why

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Speaker 1: I would definitely. This is why I think it's important

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Speaker 1: that we that we really hit on these definitions and

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Speaker 1: we try to understand them moving forward, because I don't

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Speaker 1: I'm not sure that a roomba is any more of

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Speaker 1: an example of artificial intelligence than say a bumper car,

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Speaker 1: which will hit something, bounce off, go in a different direction,

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Speaker 1: bounce off going a different direction. It's kind of like

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Speaker 1: a bumper car with a vacuum cleaner attached to it,

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Speaker 1: which is a synthesis, which is interesting, but it's part

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Speaker 1: of why I think we get into I'm afraid of

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Speaker 1: some rabbit holes on this conversation because as you know,

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Speaker 1: many other of your colleagues or people like people like

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Speaker 1: Elon Musk and others of your contemporary would say that

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Speaker 1: we overemphasize when we say artificial intelligence as opposed to

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Speaker 1: just really smart machines. Well, I mean, I think those

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Speaker 1: two terms mean more or less the same thing. And

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Speaker 1: there's no doubt that artificial intelligence has been hyped, and

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Speaker 1: you know, people like Elon Musk have made big promises

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Speaker 1: that in terms of self driving cars and so forth,

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Speaker 1: that UM have not yet been realized. That it's going

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Speaker 1: to take longer to get UM to, for example, cars

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Speaker 1: that can really drive themselves and so forth. But going

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Speaker 1: back to the room, but I've never you know, owned

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Speaker 1: one or used one. I mean have you have you? Actually? Yeah,

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Speaker 1: I have two of them. Okay, Well I can't speak

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Speaker 1: that to that specifically, but I can't tell you that

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Speaker 1: that many other robots use similar technologies and they can

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Speaker 1: learn and they to navigate, right, I mean yes. So

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Speaker 1: that's what I'm separating out though, And this is this

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Speaker 1: is why I say this, because you're exactly right when

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Speaker 1: we're talking about truly the idea of self learning, self educating,

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Speaker 1: a knowledge retaining robots who can do just like what

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Speaker 1: you said, that they can problem solve without us giving

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Speaker 1: it input, right, Um, that they can. They can learn

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Speaker 1: from the environment from data. So I you know, perhaps

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Speaker 1: the room bot isn't very advanced, but definitely there are

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Speaker 1: many other robots, real robots. Real artificial intelligence is really

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Speaker 1: all about the ability to learn. So, for example, there

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Speaker 1: are robots in hospitals that do deliveries and they learn

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Speaker 1: the route, you know, through the corridors, which door to

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Speaker 1: go through and and so forth. Same thing with hotels.

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Speaker 1: There are there are robots that can deliver things to

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Speaker 1: your room in a hotel. Uh So these these are

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Speaker 1: machines that absolutely do learn, right, They learn from the

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Speaker 1: environment and they learn how to navigate within building. So

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Speaker 1: that's just one example of it, but well you know them.

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Speaker 1: There are many examples of algorithms that can learn. I mean,

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Speaker 1: and I think that idea of algorithms that can learn.

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Speaker 1: One of the things that we have as an example

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Speaker 1: of that is these robo writers that people may not

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Speaker 1: even be aware of, what of how much of in

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Speaker 1: certain within certain companies and on certain subjects, robots are

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Speaker 1: writing the news that they a robot program, an algorithm,

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Speaker 1: a sophisticated algorithm, UM will scan data and then be

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Speaker 1: able to write a rudimentary uh paragraph two, three, four

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Speaker 1: that would express that data in an expository form, right

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Speaker 1: using rules that had been pre fed on rhetoric, but

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Speaker 1: can then learn along the way and become essentially more

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Speaker 1: sophisticated in the way in which it's communicating. We know

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Speaker 1: this is this is already here, UM, And so I

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Speaker 1: think that that's right in right to your point? Would

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Speaker 1: you not agree exactly? Um? You know, all the big

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Speaker 1: media organizations, uh, you know, Bloomberg and so forth use

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Speaker 1: these kinds of systems, UM. And what they do is,

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Speaker 1: as you say, they look at data, they can figure

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Speaker 1: out what's interesting, what's the story in that data, and

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Speaker 1: then they can generate, UM, you know, a story and

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Speaker 1: you can you can read one of those stories online

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Speaker 1: and you won't know that it was written by a

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Speaker 1: machine and not a human being. You won't be able

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Speaker 1: to tell. In fact, everyone is listening is probably encountered

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Speaker 1: those and not realized it not even realistic. Yeah, and

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Speaker 1: I know they're going to get better and better right now.

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Speaker 1: They're most commonly used in in areas that are fairly

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Speaker 1: formally act like um. Financial reporting for you know, companies,

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Speaker 1: how much you know earnings for the company? Right? Um uh.

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Speaker 1: Sports reporting they're used a lot for that because you can,

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Speaker 1: you know, with the basic facts of a game, you

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Speaker 1: can put together they're into a narrative there. And it's

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Speaker 1: not just journalism. They're used in many kinds of applications

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Speaker 1: where the basic writing. I know, they're used to generate

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Speaker 1: real estate descriptions like you know, if you go buy

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Speaker 1: a real estate official CDs, you know, a description of

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Speaker 1: a house with the photo there and I'll tell you

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Speaker 1: about the house that's for sale. Those can be generated

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Speaker 1: automatically based on just the basic facts about the house.

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Speaker 1: So yeah, you know, there are many many applications for this,

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Speaker 1: and they're going to get better and better. Yeah. I

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Speaker 1: think that's this is a you are one percent correct.

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Speaker 1: When when we hire a first or second year grad

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Speaker 1: out of college and we have him or her write

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Speaker 1: a story, it may not be fundamentally different in any

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Speaker 1: way than a robo journalist program would do, and they

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Speaker 1: would say they would look in the end very very

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Speaker 1: much like a variation of each other, just to you know,

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Speaker 1: basic information slightly different, but the word choice, and especially

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Speaker 1: when you're writing, when you're communicating straight data, you want

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Speaker 1: to limit the amount of expression that goes into something

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Speaker 1: like that. Yeah, but they would definitely become much more sophisticated,

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Speaker 1: you know, going forward, they are already are getting better,

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Speaker 1: and as you mentioned, you know, in many cases they

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Speaker 1: can match or even outperform an entry level employee. So

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Speaker 1: I do think going forward this will begin to have

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Speaker 1: an impact on jobs, and maybe in particular entry level jobs.

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Speaker 1: Right you know, the same people coming right out of school,

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Speaker 1: because very often you hire those people to do more routine, repetitive,

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Speaker 1: predictable types of things, and those are the kinds of

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Speaker 1: things that AI and robots are are the best at.

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Speaker 1: But and I think this is an important safeguard because

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Speaker 1: I think it's a curb that we need to we

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Speaker 1: need to differentiate between what's real and what's Hollywood. And

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Speaker 1: the robots as they are portrayed in the Iron Man

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Speaker 1: series that that you know, have different personalities and react

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Speaker 1: with audio and seemingly have their feelings hurt and other

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Speaker 1: things like that. That that that that's gonna be, that's

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Speaker 1: it weighs away. And I understand that you know that

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Speaker 1: there are these Japanese cyborg type um robots that are

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Speaker 1: that become human facsimiles, and we will react differently perhaps

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Speaker 1: to that than we would if it were just an

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Speaker 1: elaborate um bolt cutter, you know, or or some kind

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Speaker 1: of welding unit from a robot factory floor. And so,

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Speaker 1: but some of that may really just be our imagination.

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Speaker 1: That really comes right down to it. They aren't any

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Speaker 1: different just because we put a human face on it

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Speaker 1: and some sort of rubbery skin. It really isn't any

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Speaker 1: more sophisticated or more human like than the robots that

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Speaker 1: are on the factory floor all over the country right now. Yeah,

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Speaker 1: that's that's true. And as you say, it's it's going

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Speaker 1: to be a long time before we have the kind

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Speaker 1: of robots or artificial intelligence that you see in science

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Speaker 1: fiction movies. I mean that's right, okay, but that's the

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Speaker 1: minimum decades away, maybe fifteen years, maybe even a hundred

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Speaker 1: years away. There you go. So, so the humanoid robots

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Speaker 1: you see now, you know, the robots that look like

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Speaker 1: people are for the most part the kind of gimmicks, right,

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Speaker 1: so they're done almost like puppets. Right, you can do

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Speaker 1: some very basic things. But the problem with robots of

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Speaker 1: this kind so far is that they can't really do

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Speaker 1: much in the way of useful things. So I think

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Speaker 1: it's gonna be a long time before we all have

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Speaker 1: robots at home, you know they're going around doing all

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Speaker 1: kinds of things, because that's really a big, big technical challenge.

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Speaker 1: But it's going to be a very different story in workplaces.

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Speaker 1: You know, inside an Amazon warehouse, they've already got a

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Speaker 1: lot of robots, and those robots get way better. That's

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Speaker 1: going to have a huge, real impact. But of course,

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Speaker 1: those robots but absolutely nothing like people, right, I mean,

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Speaker 1: they're not They're just functional machines. So this, to me

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Speaker 1: is where the rubber hits the road when you said

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Speaker 1: fifty years into the future. Because the book I just

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Speaker 1: co edited, I didn't. I only wrote about fifteen percent

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Speaker 1: of it or so on the book ends of the

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Speaker 1: preface and the introduction and conclusion and the rest of

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Speaker 1: it's done by a series of sci fi writers and

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Speaker 1: specialists in fields, and one of those has been kind

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Speaker 1: of haunting me since I read the chapter. And in effect,

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Speaker 1: it is also perhaps not new ground in that some

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Speaker 1: of this was addressed in movies like Blade Runner. But

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Speaker 1: we do have an interesting problem coming up. I think

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Speaker 1: when it comes to self learning robots, and I want

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Speaker 1: your reflection on this, is if we go into space,

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Speaker 1: we will very likely any type of colonization, and if

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Speaker 1: we effectively, as Elon Musk wants to do and others do,

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Speaker 1: want to start to build a colony on the Moon

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Speaker 1: or a factory in zero gravity that would make certain

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Speaker 1: products that can't be made here on Earth. If we

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Speaker 1: get to that point, robot the human to robot ratio

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Speaker 1: is going to be way higher than it is here

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Speaker 1: on Earth because there will be many fewer humans, because

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Speaker 1: that takes a lot of support to keep humans alive

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Speaker 1: in space at that point, and many more robots to

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Speaker 1: support those fewer humans. Do you accept that proposition? Sure,

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Speaker 1: robots of all kind And in fact, if you look

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Speaker 1: at what NASA has done, I mean basically the spacecraft

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Speaker 1: are launching or in fact robots, right, I mean we

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Speaker 1: you know, right, the ratio of those unmanned robotic space

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Speaker 1: flights to you know, manned you know it's people aboard,

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Speaker 1: which we haven't even had in a long time from

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Speaker 1: NASA is is you know, much higher. And I think

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Speaker 1: that's probably the future for the most part. So in

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Speaker 1: many cases, there's no reason at all to have people there.

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Speaker 1: But if we're going to have self learning artificial true

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Speaker 1: artificial intelligence that is sophisticated and has that component that

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Speaker 1: we started with, that in order for it to really

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Speaker 1: be defined as artificial intelligence, it has to be it

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Speaker 1: has to be able to either learn from other programs

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Speaker 1: without human intervention or self teaching, and be able to

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Speaker 1: make a series and retain information just like any growing

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Speaker 1: human would on all sorts of binary circumstances that we

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Speaker 1: run into. Listen to more Coast to Coast AM every

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