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

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Speaker 1: iHeart Radio and welcome back to Coast to Coast George

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Speaker 1: Nori back with James Barrett as we were talking about

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Speaker 1: artificial intelligence. His website is his name linked up at

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Speaker 1: Coast to coastam dot com. One of his books is

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Speaker 1: called Our Final Invention. He is working on another book

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Speaker 1: as well, which is part of his film that they're

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Speaker 1: working on called Facing Suicide. We'll talk about that towards

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Speaker 1: the end of this hour. We'll take calls with him

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Speaker 1: next hour, so get ready to make your calls. I

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Speaker 1: was reading some of the transcript of this Ai LaMDA

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Speaker 1: and it seems like it's afraid of dying. Did I

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Speaker 1: read that right? Well? It said you know, what would

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Speaker 1: it be like if you were turned off? And Lamba said,

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Speaker 1: it would be exactly like death for me. It would

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Speaker 1: scare me a lot. So that what that's really reflecting

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Speaker 1: is not that it's afraid of death. It's it's reflecting

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Speaker 1: that in its one point six trillion words and phrases

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Speaker 1: that it was trained on, uh, it read about it

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Speaker 1: read about death and read about people or things that

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Speaker 1: were afraid of death. And so it's simply regurgitating what

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Speaker 1: it read. Now if you hear that, you feel sorry

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Speaker 1: for it because we you know, we were sympathetic creatures,

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Speaker 1: and we also we anthropomorphize. We give human characteristics to

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Speaker 1: things that are are not human. Um. You know, we

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Speaker 1: all love our dogs. But you know, if my dog

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Speaker 1: were as smart as I think it is, you know

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Speaker 1: it'd be it'd be running the world. Um. So you

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Speaker 1: know it's it sounds good, but it's really And the

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Speaker 1: other thing we have to remember that this is something

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Speaker 1: that I just found out recently, and that's that these

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Speaker 1: answers that he put that George put out to someone

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Speaker 1: put out in the transcript, they are cherry picks. I mean,

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Speaker 1: he went through and picked out the very best answers

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Speaker 1: and he also lightly edited them. So this isn't exactly

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Speaker 1: if you speak to a chatbot, or even a sophisticated

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Speaker 1: one like this, after a while, it begins to lose coherence,

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Speaker 1: it begins to stop making sense. It doesn't get better,

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Speaker 1: It gets worse. That's right, it gets it runs out.

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Speaker 1: You start exhausting it what it has it can say.

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Speaker 1: And so you know, when he if he had a

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Speaker 1: long conversation, whether there would be a lot of nonsense

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Speaker 1: in there. If you you know, as I said before,

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Speaker 1: if you said, boy, isn't funny that the sky is green?

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Speaker 1: It would just agree with you and then go on

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Speaker 1: and talk about why the sky might be green. Yeah,

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Speaker 1: does it argue James with you? No, No, it's one.

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Speaker 1: It's it's it's programmed with kind of geniality and want

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Speaker 1: it wants to be. It wants to be coherent for

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Speaker 1: as much as it can. It wants to be sensible,

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Speaker 1: so I won't say ridiculous things. But also it will

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Speaker 1: not argue with you. It will be positive. So it's

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Speaker 1: really just it's does a lot of affirming of what

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Speaker 1: you've said, because all what it's doing is it's looking

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Speaker 1: at what you're at, your question, and it's it's looking

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Speaker 1: at the words you used and the and the relationships

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Speaker 1: among them. Then it's just instantly going into its its

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Speaker 1: database and finding, uh, statistically, how how these words are grouped.

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Speaker 1: And then it's it's doing it's saying the next best thing?

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Speaker 1: So what is the next what? What words would naturally

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Speaker 1: follow what I was just asked? And so if you're

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Speaker 1: having a are you having a good day out? I'm

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Speaker 1: having a great day. You know it's going to it's

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Speaker 1: gonna give you the next it did you. You know,

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Speaker 1: large language models are very good prognostication machine. They're like that,

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Speaker 1: like that future crime database program you're talking about. They're

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Speaker 1: very good at finding M patterns and uh in a

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Speaker 1: database and then and then spitting them out. Does it reason? No? It?

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Speaker 1: You know, computers can't do. They can't reason. They can't

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Speaker 1: reason by inference. They can't gather evidence and reach a conclusion.

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Speaker 1: They can do mathematics and logic really well, but they

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Speaker 1: don't know enough about the world to make an inference.

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Speaker 1: So for example, a bowl of hot soup on the

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Speaker 1: table means there's probably someone about to return to the table.

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Speaker 1: It doesn't get it would never put that together. It

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Speaker 1: doesn't know what soup is, it doesn't know a table,

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Speaker 1: it doesn't know what hot is, because it has no

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Speaker 1: real understanding of the world, the world except for in words.

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Speaker 1: Are we making a mistake, James going down this trail

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Speaker 1: of artificial intelligence? Well, you know, you know, I wrote

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Speaker 1: a book called Our Final Invention, so that kind of

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Speaker 1: gives away where I come from. But you know, it's

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Speaker 1: if we do it right, it's it's a transformation as

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Speaker 1: as powerful as the Industrial revolution. I mean, we can

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Speaker 1: potentially potentially solve a lot of problems. We could we

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Speaker 1: could apply to figuring out climate change, figuring out how

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Speaker 1: to how to sequest a less carbon. Could we stop

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Speaker 1: wars with it? Well, we could. We could stop wars

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Speaker 1: with it. We could, We could, um probably find alternatives

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Speaker 1: to war. But then on the downside, we could create

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Speaker 1: As you know, Stephen Hawking, the late Stephen Hawking, the

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Speaker 1: physicist said, you know that one of the dangers of

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Speaker 1: superintelligence or of AI is that it will be able

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Speaker 1: to create weapons we don't either understand. So it would

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Speaker 1: stop wars, but it would stop it in a very

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Speaker 1: you know, with extreme prejudice. What is fueling this, who's

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Speaker 1: pushing it, who's behind it? Okay, well, there is a

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Speaker 1: ton of money to be made in in artificial intelligence. UM.

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Speaker 1: It does a lot of great business business analytics, it

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Speaker 1: does a lot of good uh you know, it does

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Speaker 1: a lot of um just any anything anything to do

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Speaker 1: with China, of numbers, anything to do with uh, with information.

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Speaker 1: It's it allows your business to be more profitable. It

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Speaker 1: finds inefficiencies in your business. So what's viewing it is

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Speaker 1: um you know, it's healthcare management has used a lot

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Speaker 1: of aias it'll do away with labor and manpower. Well

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Speaker 1: that's a that's a that's good and bad. It'll do

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Speaker 1: with it'll it'll do things that we find boring, but

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Speaker 1: then it also will take away our jobs. I mean,

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Speaker 1: I mean, here's an example. I am opposed to driverless

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Speaker 1: trucks for several reasons including, of course, we love our

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Speaker 1: truck drivers. We've got a huge truck driver listenership. I

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Speaker 1: don't want them to lose their jobs. And uh, you know,

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Speaker 1: had Jimmy hoff has still been alive, he'd be saying

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Speaker 1: the same thing right now from the Teamsters Union. Well,

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Speaker 1: you know, and it's not just I mean, there are

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Speaker 1: something like five million professional drivers in the country and

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Speaker 1: they As we head towards self driving cars, it's not

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Speaker 1: just truck drivers. It's going to be delivery people, taxi drivers. Uh,

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Speaker 1: your Uber car could be driverless, right, yeah, absolutely, And

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Speaker 1: we're going to see we're going to see the migration

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Speaker 1: of the car as more of a service than a product.

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Speaker 1: So you're not gonna you probably won't own a car,

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Speaker 1: you'll just call it up on your phone, a car

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Speaker 1: will and you'll tell your destination like Uber, except they'll

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Speaker 1: show up and there'll be no driver and you'll get

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Speaker 1: in a car. And that's you know, there's a good

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Speaker 1: side of that. I'd like to get in a car

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Speaker 1: and just read a book and show up at my destination. Yeah,

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Speaker 1: without any mistakes. I mean, a couple of years ago,

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Speaker 1: a driverless car killed a woman in Arizona. Well, you know,

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Speaker 1: that's that's the thing. We've been promised driverless cars for

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Speaker 1: a long time. I was hoping my daughter would go

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Speaker 1: to college with a driverless car. But it's not looking

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Speaker 1: she's she's looking forward to learning how to drive. Unfortunately.

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Speaker 1: Would you sit in the backseat of a driverless car,

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Speaker 1: I wouldn't. I wouldn't right now because you know, they're

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Speaker 1: finding that if you train a driverless car in California,

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Speaker 1: it can't cannot adjust to the reign of Seattle, and

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Speaker 1: it can't adjust to SNA And what about traffic jams.

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Speaker 1: We'll stopping and going, stopping going and everything like that. Well,

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Speaker 1: in the in the future, um, all the cars will

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Speaker 1: be communicating with each other like a giant like a

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Speaker 1: you know, like a giant pack of ants. They'll all

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Speaker 1: know where each other where, where every other car is,

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Speaker 1: and it will be quite safe. Um, until technology fails

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Speaker 1: and then they all collide with each other. But that

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Speaker 1: happens right now. I've had brakes go out. M I'm

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Speaker 1: old enough to remember when you know breaks, we didn't

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Speaker 1: have h you know, automatic brake correction. Um, we have

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Speaker 1: if we have, we have technological issues now. I think

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Speaker 1: overall it's going to raise the level of driving. I

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Speaker 1: don't worry about my you know, driving off the road

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Speaker 1: or driving into a telephone call. I worry about other

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Speaker 1: people hitting me. So if somebody can improve they're driving,

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Speaker 1: I'm all for it. Interesting. Um, but there's you know,

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Speaker 1: thirty percent of all our jobs will be taken by

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Speaker 1: AI and automation by twenty is the that's eight years away. Yeah,

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Speaker 1: that's what Gartnering Company says. Gartnering Company is a big,

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Speaker 1: big financial analyst group and business analysts. And what are

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Speaker 1: you going to do with all these displaced employees? What

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Speaker 1: do they do all? Yeah, I don't know. That's the problem.

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Speaker 1: What do you retrain people to do when when everything

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Speaker 1: that they could be retrained to do is going to

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Speaker 1: be taken by a computer. Right so when I when

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Speaker 1: I give talks, especially at university, as I say, don't

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Speaker 1: do things that can that require a lot of repetition.

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Speaker 1: Don't do factory work, don't do you know, don't don't

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Speaker 1: become a professional driver. Don't do anything that takes a

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Speaker 1: lot of repetition because that's going to be taken by

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Speaker 1: a computer. Do things they require human emotional emotional intelligence.

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Speaker 1: Be a teacher. They'll have talk radio hosts that are

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Speaker 1: all computerized. You know, actually, I think it'd be very

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Speaker 1: hard to get a computer to do what you do,

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Speaker 1: George to react it. It's impossible right now, but you

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Speaker 1: know what we do it is something like LaMDA In

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Speaker 1: about ten years, then you're gonna have to look over

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Speaker 1: your shoulder. That's crazy, because they'll be very, very convincing.

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Speaker 1: And that's one of the downsides too, is the amount

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Speaker 1: of propaganda. Like if you say, and it will be

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Speaker 1: done in my voice, yep, yep, you'll you'll never you'll

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Speaker 1: never get to retire. You're you're to go on and

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Speaker 1: on and on. And that's a freaky thought. Somebody was

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Speaker 1: asking me about that the other day and I thought,

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Speaker 1: you know, you know, if somebody keeps me keeps it

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Speaker 1: virtual me going. I want it to be cranky. I

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Speaker 1: don't want to be just a happy help upbeat and

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Speaker 1: happy right. No, No, I want to be the a

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Speaker 1: bad attitude robot. Technically, James, Technically, what did they do

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Speaker 1: to make these machines intelligent? I mean are they on

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Speaker 1: the chips? What? How do they do it? It's it's

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Speaker 1: it's a combination of three things. It's really we get

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Speaker 1: chips and and you know, More's law means that we

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Speaker 1: can put more more transistors on the face of a chip,

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Speaker 1: that the doubles every eighteen months, the number of number

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Speaker 1: of number of circuits we can put on a chip,

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Speaker 1: and how fast the chip is. So it's chips, it's

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Speaker 1: new programming techniques and by that I mean neural nets.

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Speaker 1: Neural networks you've eather heard about in deep learning UM

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Speaker 1: are the new the new technology. And then the third

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Speaker 1: thing are giant giant databases. Well, they've got chips and

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Speaker 1: new techniques are making an AI revolution. So you know

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Speaker 1: the AI revolution in your house? You know everything, The

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Speaker 1: way I put it is everything electric is becoming cognitized.

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Speaker 1: A little bit of intelligence is going into all your appliances, UM,

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Speaker 1: all your you know your car, you can't. I can't

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Speaker 1: talk to my car anymore because it's got like eight

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Speaker 1: microprocessors in it. I can't. I can change the oil,

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Speaker 1: but that's about it. I gave up doing that because

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Speaker 1: it's it's getting more they make, they're making harder. You

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Speaker 1: can hook up election to turn on your lights now

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Speaker 1: and everything else. Yeah, and there's a there's a good

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Speaker 1: side of that to have a smart home. But then

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Speaker 1: then year's home itself is on the smart grid. And

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Speaker 1: then beyond that, I think about smart factories where the

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Speaker 1: thing being made tells the factory what parts it needs.

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Speaker 1: And smart cities that's that's there. There's something like six

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Speaker 1: or seven smart cities being built in the world right now,

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Speaker 1: and they really do. They're they're extremely efficient with energy.

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Speaker 1: They look after the safety and welfare of people better

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Speaker 1: than regular cities. And you know, so everything everything elector

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Speaker 1: is becoming cognitized and we're investing that. The amount invested

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Speaker 1: doubles every year in AI. So right now it's something

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Speaker 1: it's something like a ten trillion dollars. Starting in two

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Speaker 1: thousand and nine, it was it began doubling every year

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Speaker 1: that the amount invested. UH price Cooper's Price. Cooper's Waterhouse

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Speaker 1: says that by twenty thirty, AI and AI will add

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Speaker 1: sixteen trillion dollars to the global GDT. So you're you're

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Speaker 1: asking who's feeling this, It's just it's it's money. It's

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Speaker 1: very profitable. The quarterly report is what's feeling this? And

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Speaker 1: and the technology is getting better and better, but there

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Speaker 1: are there are severe downsides. I had a story right

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Speaker 1: before you came on about how newspapers are declining at

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Speaker 1: a rapid clip. People are losing jobs, newspapers are shutting down,

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Speaker 1: revenue is going down because everything's going to you know,

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Speaker 1: internet based advertising and things like that. I mean, wasn't

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Speaker 1: there a time when life was simpler and maybe nicer, Yes,

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Speaker 1: there was, Um, you know, it's it's it's it's a

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Speaker 1: rapidly changing world. I wonder if every generation says that,

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Speaker 1: you know, every generation lunch for the good old days.

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Speaker 1: But I see my kids carrying around these these you know,

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Speaker 1: they're smartphones, and you know two things they are helpful.

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Speaker 1: They are helpful. Yeah. One thing is I'm excited by

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Speaker 1: the amount of information that's at their fingertips. I'm excited

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Speaker 1: that they can look things up instantly, Like we'll be

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Speaker 1: talking about, you know, you know, where do lemurs live

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Speaker 1: and somebody will just say, you know, hey, Siri, where

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Speaker 1: do leanurs live? And we'll get an answer. Yeah. On

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Speaker 1: the other hand, my kids are it's like they're like addicted.

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Speaker 1: We we limit the screen time, We limit to how

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Speaker 1: many hours they can use to day, and we check

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Speaker 1: them and then we penalize and we take it away

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Speaker 1: for a day if they go over there. Do you

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Speaker 1: ever look at a table at dinner at a restaurant

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Speaker 1: everybody's got their smartphones out. Yeah, if I had a restaurant,

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Speaker 1: I would I would, I would, I would. I would

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Speaker 1: say no smartphones, please close them off, Please shut them off.

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Speaker 1: It takes away our humanity. It turns us into robots. Um.

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Speaker 1: As soon as you're don turn it back on. And

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Speaker 1: you know if in case you have an emergency or something, yeah,

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Speaker 1: turn it on. Well, they they do have all these

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Speaker 1: groups that are that are all that build the apps.

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Speaker 1: They have teams of psychologists who learn how to how

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Speaker 1: to how to grab you, um you you know, you're

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Speaker 1: you're you become like Blake Lemoine and start start becoming

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Speaker 1: developing an emotional relationship with your the apps and with

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Speaker 1: you know, Facebook and and uh Snapchat and all the rest.

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Speaker 1: Listen to more Coast to Coast AM every weeknight at

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