WEBVTT - TechStuff Classic: Passing the Turing Test

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<v Speaker 1>Welcome to tech Stuff, a production from I Heart Radio.

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<v Speaker 1>Hey there, and welcome to tech Stuff. I'm your host,

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<v Speaker 1>Jonathan Strickland. I'm an executive producer with I Heart Radio

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<v Speaker 1>and love all things tech, and this is time for

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<v Speaker 1>a classic tech Stuff episode. This episode originally published on

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<v Speaker 1>June twenty three, two thousand fourteen. It is titled passing

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<v Speaker 1>the Turing Test, something that we frequently associate with artificial

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<v Speaker 1>intelligence and actual you know, like machines thinking or at

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<v Speaker 1>least appearing to think. So let's listen in to this

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<v Speaker 1>classic episode. The Touring Test is named after Alan Turing,

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<v Speaker 1>and we've done a full episode on Alan Turing way

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<v Speaker 1>back when, back in November. Yeah, phenomenal person, amazing thinker. Yeah,

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<v Speaker 1>one of the like the grandfather of computer science. Also

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<v Speaker 1>tragic life story which we went into detail back in

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<v Speaker 1>that story. And so you might wonder why, right, So

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<v Speaker 1>what does that have to do was the the guy

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<v Speaker 1>who was the essentially the father of computer science or

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<v Speaker 1>grandfather of computer science? What does he have to do

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<v Speaker 1>with the story about a computer program in June two

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<v Speaker 1>thousand fourteen, a computer program with an interesting name, Eugene

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<v Speaker 1>Goostman passing the Turing test. What does that all have

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<v Speaker 1>to do with each other? Well? To answer that, we

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<v Speaker 1>have to ask what is a Turing test? Well, as

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<v Speaker 1>it turns out, Away back in the nineteen fifties, he

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<v Speaker 1>started envisioning uh I thought experiment. Yeah, he published a

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<v Speaker 1>paper in a journal called Mind in nineteen fifty called Computing,

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<v Speaker 1>Machinery and Intelligence, and he sort of laid out his

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<v Speaker 1>thought experiment there. It's interesting because what he did was

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<v Speaker 1>he took this idea of a party game and then

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<v Speaker 1>adapted it for computers. Right. The party game that it's

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<v Speaker 1>based on would have three participants, an interrogator, a man,

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<v Speaker 1>and a woman um, all situated so that they can't

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<v Speaker 1>see one another, and the interrogator is supposed to ask

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<v Speaker 1>questions um to try to figure out which of the

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<v Speaker 1>participants is the dude and which is the lady exactly.

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<v Speaker 1>And it's the dude's job to try and mislead the

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<v Speaker 1>interrogator to believe that that he, in fact is the

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<v Speaker 1>lady and the other one is the man. It's the

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<v Speaker 1>lady's job to say, hey, I want you to get

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<v Speaker 1>this right. I'm the lady. That other guy that's the dude.

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<v Speaker 1>And so the interrogator has to ask questions. Now, obviously

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<v Speaker 1>they can't see each other. Because they could see each other,

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<v Speaker 1>then that would probably give things away. Probably, they really

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<v Speaker 1>shouldn't be able to hear each other because that could

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<v Speaker 1>also give things away. Sure, and if you use handwritten notes,

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<v Speaker 1>then you the interrogator might be able to make judgments

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<v Speaker 1>based on the handwriting style. So it should really be typewritten, right,

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<v Speaker 1>So you want to you want to remove as many

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<v Speaker 1>easily identifiable traits from this game as possible to make

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<v Speaker 1>it all about the questions and the answers. Now, Touring said,

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<v Speaker 1>what if we were to take the same basic premise,

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<v Speaker 1>but instead of having two human interviewees, replace one of

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<v Speaker 1>those humans with a machine. Now, if that machine can

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<v Speaker 1>convince the interrogator that the machine itself is a human being,

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<v Speaker 1>it would be a pretty phenomenal achievement. Or you know,

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<v Speaker 1>just generally, if the interrogator wasn't sure which of the

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<v Speaker 1>two interrogate, right, whether which one is the human, which

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<v Speaker 1>one is the machine, or even if there could be

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<v Speaker 1>a case where you don't know. It may be that

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<v Speaker 1>you have two humans that you're interrogating, and it may

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<v Speaker 1>be one of those things where you have to you know,

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<v Speaker 1>if you don't know for a fact that one of

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<v Speaker 1>them the machine, that makes it even harder, right, at

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<v Speaker 1>least assuming that the computer program is sophisticated enough. Now,

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<v Speaker 1>Touring was saying that we don't have any machines right

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<v Speaker 1>now that can do this, but I envision a time

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<v Speaker 1>when computers will be able to do such a thing

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<v Speaker 1>where if you were to interrogate a computer, you would

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<v Speaker 1>get back responses that would be uh, convincing enough for

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<v Speaker 1>it to make it difficult to determine if it were

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<v Speaker 1>man or machine. And so he said that he predicted

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<v Speaker 1>in fifty years time, which would be the year two thousand,

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<v Speaker 1>that computers and software be sophisticate enough that interrogators would

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<v Speaker 1>only be able to guess correctly seventy percent of the time,

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<v Speaker 1>meaning that they would be fooled by the computer pent

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<v Speaker 1>of the time. Right. So, uh, this was just kind

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<v Speaker 1>of a thing he was coming up with, like an idea,

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<v Speaker 1>a prediction, not necessarily a test. Although very much like

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<v Speaker 1>Moore's observation became Moore's law, this became what is known

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<v Speaker 1>as the Turing test. People talk about a Touring test

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<v Speaker 1>as a machine capable of fooling people into thinking it's

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<v Speaker 1>another person at least thirty percent of the time after

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<v Speaker 1>five minutes of conversation. Very good point. Yes, it needs

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<v Speaker 1>to be five minutes of conversation. If you are just

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<v Speaker 1>getting maybe two or three responses, that might not be

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<v Speaker 1>enough for you to be able to draw a conclusion

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<v Speaker 1>that you feel good about. If after five minutes you

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<v Speaker 1>still are not entirely, entirely certain, then that might say

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<v Speaker 1>that this machine, in fact has passed the Turing test.

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<v Speaker 1>And this has been extrapolated to mean something about machine

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<v Speaker 1>intelligence because Turing himself tied the idea of of how

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<v Speaker 1>we perceive a machines intelligence directly to artificial intelligence and

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<v Speaker 1>and and even how we perceive human intelligence. Because here's

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<v Speaker 1>Touring's idea is a little cheeky, and I love the

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<v Speaker 1>fact that it's so cheeky. So Turing kind of said,

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<v Speaker 1>would you say such a machine as intelligent if it

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<v Speaker 1>appears to be intelligent, is it fair to say that

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<v Speaker 1>is intelligent? Touring? So why not? Because I'm only able

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<v Speaker 1>to tell that I am intelligent, right because of my experience.

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<v Speaker 1>I'm only able to have my own personal experience. I

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<v Speaker 1>can't experience what someone else's life is like, all right,

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<v Speaker 1>sitting across from each other, Jonathan and I can only

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<v Speaker 1>assume that the other one is intelligent, right, And it's

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<v Speaker 1>because the other person is displaying traits that we associate

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<v Speaker 1>with intelligence. They seem to be able to take an information,

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<v Speaker 1>respond to it, make decisions. And based on the fact

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<v Speaker 1>that we ourselves also do that thing, we go ahead

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<v Speaker 1>and say, all right, well, they clearly have the same

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<v Speaker 1>features that I have, which includes intelligence. Uh. Now, he says,

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<v Speaker 1>why would we not extend that same courtesy to a

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<v Speaker 1>machine if it also appeared to display those same uh features?

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<v Speaker 1>He says, doesn't matter if the computer is quote unquote thinking.

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<v Speaker 1>If it's it can fool you. Yeah, if it's able

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<v Speaker 1>to to simulate it well enough, you might as well

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<v Speaker 1>say it's intelligent, because simulate it is probably a kinder

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<v Speaker 1>phrase for that than fool. Yes. Yeah, well I know

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<v Speaker 1>it's it is fooling essentially, I mean, because ultimately you're

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<v Speaker 1>talking about a computer programmer who's making this happen. So

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<v Speaker 1>nowadays we think of this as the Turing test. Can

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<v Speaker 1>a machine of the time are more fool someone after

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<v Speaker 1>five minutes of conversation into thinking it's a human? Now,

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<v Speaker 1>this is really hard to do. This is is non trivial.

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<v Speaker 1>I mean it sounds almost simple. Yeah, the concept is simple,

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<v Speaker 1>the execution incredibly difficult. Because here's the thing, human language varied.

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<v Speaker 1>We have unstructured, unpredictable ways to say things like if

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<v Speaker 1>if I were to tell you that it's a hundred

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<v Speaker 1>degrees outside and it is humid like the humidities, and

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<v Speaker 1>you go out there, then I'm sure all of our

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<v Speaker 1>listeners would have slightly different ways to express their thoughts

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<v Speaker 1>on the conditions outside. Some of them would probably contain

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<v Speaker 1>colorful metaphors. Mine very likely when it contain colorful metaphors,

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<v Speaker 1>particularly if I had to be outside for any length

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<v Speaker 1>of time. But that's the point. We would all have

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<v Speaker 1>different ways of saying this. So how do you make

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<v Speaker 1>a computer program able to interpret all the myriad of

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<v Speaker 1>ways we can all express the same thought, let alone

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<v Speaker 1>any thought? All right? This is what's referred to as

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<v Speaker 1>natural language recognition, and it's a really huge problem in

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<v Speaker 1>artificial intelligence and and and a lot of other speech

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<v Speaker 1>related computer programming. Exactly. Yeah, this is where a computer

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<v Speaker 1>program has to be able to parse the language so

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<v Speaker 1>it recognizes things like this word is a noun, this

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<v Speaker 1>word is a verb, this this word alters this other word. Uh.

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<v Speaker 1>And not only does it need to be able to

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<v Speaker 1>recognize it, it it needs to be able to respond in kind. Right,

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<v Speaker 1>So if you have appropriately in some way or another share. Yeah,

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<v Speaker 1>you could have a computer program that's literally making up

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<v Speaker 1>sentences or you know, the approximation of a sentence randomly,

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<v Speaker 1>where it's just pulling strings of words and placing them

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<v Speaker 1>in a sequence and then presenting them. But that wouldn't

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<v Speaker 1>be convincing at all. If I were to say, hello,

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<v Speaker 1>how are you today, and Lauren was to say blue

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<v Speaker 1>panther pickup jump down street, I'd be like what? And

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<v Speaker 1>even that was closer to being a sentence than some

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<v Speaker 1>of the random stuff that you would see if it

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<v Speaker 1>was just truly completely So it also has to be

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<v Speaker 1>able to uh endure a five minute long conversation, like

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<v Speaker 1>we said, in order to pass the Turing test. So

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<v Speaker 1>you can't have too much repetition or that gives it away. Absolutely.

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<v Speaker 1>If you've ever been playing a video game and all

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<v Speaker 1>of the NPCs say the same thing over and over

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<v Speaker 1>and over again, yeah, if if all the chat bot

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<v Speaker 1>says is hey, listen, then you're clearly playing Zelda and

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<v Speaker 1>you're not actually having a decent conversation. That being said,

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<v Speaker 1>there is someone I know who plays a ferry at

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<v Speaker 1>the Georgia Renaissance Festival, and hey, listen is heavily represented

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<v Speaker 1>in a repertoire. It's pretty amazing. No, it's pretty awesome.

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<v Speaker 1>But at any rate, Yeah, so so these are these

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<v Speaker 1>are big problems. You have to build a database of words,

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<v Speaker 1>you have to be able to figure out what kind

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<v Speaker 1>of syntax are you going for. It's a wide open,

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<v Speaker 1>huge problem, and solving this problem can be really beneficial

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<v Speaker 1>in lots of ways. We'll talk a little bit about

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<v Speaker 1>that later. It's it's beyond just making a program that

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<v Speaker 1>seems human, right, That's that's one way of looking at it.

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<v Speaker 1>But there are a lot of other benefits that come

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<v Speaker 1>along with it, which will chat about towards the end

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<v Speaker 1>of the show. But for right now, let's go into

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<v Speaker 1>this story behind Eugene Goostman and whether or not it

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<v Speaker 1>was actually the first chat bought to pass the Turing test. Yeah. So,

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<v Speaker 1>first of all, we've got three programmers in this story

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<v Speaker 1>of Vladimir Vslov, Eugene Demchinko and Sarage you listen. As

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<v Speaker 1>you may guess from their names, they all hail from

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<v Speaker 1>Russia and the Ukraine as well, and although not all,

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<v Speaker 1>not all of them still live there. But starting in

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<v Speaker 1>two thousand one they got to work on this, right, Yeah,

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<v Speaker 1>they were trying to design a computer program that would

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<v Speaker 1>pose specifically as a third teen year old boy from

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<v Speaker 1>Odessa in the Ukraine. Yeah, and that meant that they

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<v Speaker 1>had specific parameters that they could work within. It automatically

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<v Speaker 1>helped reduce some of that unpredictability and that lack of

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<v Speaker 1>restriction that you would have if you were to just say,

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<v Speaker 1>this is a fluent adult speaker of a given language. Yeah, Yeah,

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<v Speaker 1>giving him these you know, setting up the expectation from

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<v Speaker 1>the judges that you know, this is a non native

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<v Speaker 1>English speaker. It's it's a kid essentially. Um, you know

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<v Speaker 1>that they'll expect him to have limited knowledge of the

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<v Speaker 1>world and and different subject areas, and a limited understanding

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<v Speaker 1>of English vocabulary and grammar and all that kind of stuff.

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<v Speaker 1>So you're already managing expectations. That's going to come into

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<v Speaker 1>play when we talk about some of the criticisms about this.

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<v Speaker 1>Although although I do think it's a very clever way

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<v Speaker 1>and and a lot of previous chatbots have have had

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<v Speaker 1>similar yes kind of approaches. Yeah, because like we said,

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<v Speaker 1>if you were to take a quote unquote pure approach

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<v Speaker 1>to this, it's really really challenging. So yeah, by by

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<v Speaker 1>limiting this, the judges have an idea of well, this

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<v Speaker 1>this could be a thirteen year old boy or it

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<v Speaker 1>could be a computer program. It means that the computer

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<v Speaker 1>program doesn't have to be as sophisticated as one that

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<v Speaker 1>would be completely fluent and have you know, an adult's experiences,

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<v Speaker 1>uh and ability to communicate. So that was step one

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<v Speaker 1>and uh, Eugene Goosman took part in the competition. UH

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<v Speaker 1>that had five total chatbots. It was it was one

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<v Speaker 1>of five that took place on the sixtieth anniversary of

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<v Speaker 1>Turing's death, and the program managed to full thirty three

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<v Speaker 1>percent of the judges into thinking it was actually a person. Uh,

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<v Speaker 1>and it had there were thirty judges from what I understand,

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<v Speaker 1>So that was where you got all the headlines of

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<v Speaker 1>chat bought. There are computer beats touring tests, which already

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<v Speaker 1>is not accurate. There were some slight um hiccups in

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<v Speaker 1>a little bit of the news reporting that we'll get

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<v Speaker 1>into that part of the story later. But you know,

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<v Speaker 1>the key takeaways I think here are that this was

0:13:10.040 --> 0:13:14.840
<v Speaker 1>a this was a competition that was celebrating touring awesome um.

0:13:14.920 --> 0:13:19.840
<v Speaker 1>And that there were thirty judges, some of whom were celebrities, yes,

0:13:20.160 --> 0:13:24.560
<v Speaker 1>including an actor who had appeared on Red Dwarf right. Yes.

0:13:24.840 --> 0:13:27.679
<v Speaker 1>And then a couple of years before that, because because

0:13:27.679 --> 0:13:29.839
<v Speaker 1>you said they started working on this in two two

0:13:29.840 --> 0:13:32.359
<v Speaker 1>thousand one, this was not the first time that Gustman

0:13:32.480 --> 0:13:37.479
<v Speaker 1>had entered competition. UH. Two years previously, that same software

0:13:37.520 --> 0:13:40.760
<v Speaker 1>had convinced twenty of judges at a similar competition that

0:13:40.840 --> 0:13:43.880
<v Speaker 1>was held at Bletchley Park. Now, but Bletchley Park that's

0:13:43.880 --> 0:13:48.720
<v Speaker 1>where Touring helped crack the Enigma machine, the encoding device

0:13:48.800 --> 0:13:52.000
<v Speaker 1>that the German military was using during World War Two.

0:13:52.559 --> 0:13:54.880
<v Speaker 1>So this was a big celebration. It was at the

0:13:55.120 --> 0:13:59.240
<v Speaker 1>centennial celebrating his birth, and it ended up falling just

0:13:59.400 --> 0:14:05.960
<v Speaker 1>short of passing the Turing test. Uh. The organizer of

0:14:06.000 --> 0:14:09.400
<v Speaker 1>the the more recent event, the one in which Gustman

0:14:09.720 --> 0:14:13.360
<v Speaker 1>ran away with quote unquote beating the Turing test. UH.

0:14:13.400 --> 0:14:16.680
<v Speaker 1>That organizer was Kevin Warwick. That name may sound familiar

0:14:16.720 --> 0:14:18.400
<v Speaker 1>to some of our listeners. If you've ever heard us

0:14:18.440 --> 0:14:22.000
<v Speaker 1>talk about cyborgs. He's the guy who had an r

0:14:22.120 --> 0:14:26.240
<v Speaker 1>f I D chip surgically implanted into him. His wife

0:14:26.240 --> 0:14:29.480
<v Speaker 1>also did at one point. Yes, they could communicate with

0:14:29.520 --> 0:14:33.920
<v Speaker 1>each other through them. Some unflattering news media sometimes refers

0:14:33.960 --> 0:14:37.400
<v Speaker 1>to him as Captain Cyborg. Yeah. There there are some

0:14:37.600 --> 0:14:41.680
<v Speaker 1>critics who say that he, uh, he courts publicity in

0:14:41.720 --> 0:14:47.240
<v Speaker 1>a manner that is unbecoming of of of a scientist. Yes,

0:14:47.320 --> 0:14:51.520
<v Speaker 1>really of anybody. Yes, yes, uh, those are the critics

0:14:51.560 --> 0:14:53.320
<v Speaker 1>who say that. By the way, I just want to

0:14:53.320 --> 0:14:56.320
<v Speaker 1>make that clear. At any rate, He said that this

0:14:56.360 --> 0:14:58.760
<v Speaker 1>was the first time a chatbot had passed the Turing

0:14:58.880 --> 0:15:01.840
<v Speaker 1>test at an event, or the conversation was open ended,

0:15:02.200 --> 0:15:06.080
<v Speaker 1>meaning that they had not previously uh decided upon a

0:15:06.160 --> 0:15:10.440
<v Speaker 1>specific topic or line of questioning that the judges were

0:15:10.440 --> 0:15:13.000
<v Speaker 1>allowed to say whatever they wanted to the chat bot

0:15:13.000 --> 0:15:15.760
<v Speaker 1>and response, which obviously makes it harder because you have

0:15:15.840 --> 0:15:20.760
<v Speaker 1>to have a much wider breadth of potential responses. Yeah. Yeah,

0:15:20.800 --> 0:15:22.840
<v Speaker 1>because again, if you were to say, all right, this

0:15:22.920 --> 0:15:26.400
<v Speaker 1>chat bot is just going to talk about, um, I

0:15:26.400 --> 0:15:29.760
<v Speaker 1>don't know, sporting events from last year, well, then you

0:15:30.040 --> 0:15:32.720
<v Speaker 1>can prepare pretty well for that. Yeah, exactly. So it's

0:15:32.720 --> 0:15:34.480
<v Speaker 1>one of those again, it's one of those things where

0:15:34.680 --> 0:15:38.840
<v Speaker 1>the unrestricted nature adds in a degree of difficulty. It's

0:15:38.880 --> 0:15:41.080
<v Speaker 1>time for us to take a quick break, but will

0:15:41.120 --> 0:15:51.040
<v Speaker 1>be right back. So why would you need to make

0:15:51.040 --> 0:15:53.480
<v Speaker 1>the qualification that this is an open ended approach and

0:15:53.520 --> 0:15:56.280
<v Speaker 1>this is the first chat bot to manage it. That

0:15:56.320 --> 0:16:00.400
<v Speaker 1>would be because despite what you may have heard, Eugene

0:16:00.480 --> 0:16:03.600
<v Speaker 1>Goosband was not the first program to beat the Turing test,

0:16:04.040 --> 0:16:08.440
<v Speaker 1>not by a long shot. So work on these sort

0:16:08.440 --> 0:16:13.760
<v Speaker 1>of chatbots, these kind of artificial conversationalists. That's real recent, right,

0:16:13.800 --> 0:16:16.000
<v Speaker 1>I mean they just started doing that like what like

0:16:16.000 --> 0:16:18.200
<v Speaker 1>like maybe three or four years ago or two thousand,

0:16:18.200 --> 0:16:19.840
<v Speaker 1>one of the earliest, I mean that's when they started

0:16:19.840 --> 0:16:22.600
<v Speaker 1>with Goose. Yeah. No, in the nineteen sixties and seventies.

0:16:22.640 --> 0:16:28.080
<v Speaker 1>Say what back in the mid nineteen sixties there was Eliza,

0:16:28.680 --> 0:16:32.400
<v Speaker 1>which was written by Joseph Weisenbaum. If you're pronouncing it

0:16:32.440 --> 0:16:35.840
<v Speaker 1>in the correct German, that's correct. Excellent, I'm finally learning.

0:16:35.920 --> 0:16:39.800
<v Speaker 1>I'm sure. I'm sure he pronounces at Wisenbaum. But yeah,

0:16:39.880 --> 0:16:43.240
<v Speaker 1>but no, it would be Weisenbaum at any rate. Um,

0:16:43.280 --> 0:16:46.680
<v Speaker 1>this this was a program um that would respond to

0:16:46.760 --> 0:16:50.880
<v Speaker 1>human conversation in what ideally would be a relevant way. Yes,

0:16:51.240 --> 0:16:54.240
<v Speaker 1>it was obviously an early attempt. It was not meant

0:16:54.360 --> 0:16:58.400
<v Speaker 1>to be a program that takes on the Turing test.

0:16:58.400 --> 0:17:00.200
<v Speaker 1>It was really a thought again, kind of like a

0:17:00.200 --> 0:17:02.760
<v Speaker 1>thought experiment, the idea of what does it take to

0:17:02.880 --> 0:17:06.080
<v Speaker 1>create a piece of software that can react to questions

0:17:06.640 --> 0:17:08.960
<v Speaker 1>and make it make sense. At that point, it was

0:17:09.000 --> 0:17:11.000
<v Speaker 1>more a can we do this? Then let's do this

0:17:11.040 --> 0:17:14.880
<v Speaker 1>for real? Yeah, and these are the sort of foundations

0:17:15.040 --> 0:17:16.879
<v Speaker 1>that you have to lay in order for other things

0:17:16.920 --> 0:17:21.679
<v Speaker 1>like the Eugene Goostman program to be uh successful. So

0:17:22.480 --> 0:17:26.720
<v Speaker 1>he created a language analyzer. Now this specifically would look

0:17:26.760 --> 0:17:29.680
<v Speaker 1>at words that users would put in and then compare

0:17:29.680 --> 0:17:32.359
<v Speaker 1>them against a database of words that were stored in

0:17:32.359 --> 0:17:36.879
<v Speaker 1>the computer's memory. And then also created scripts. Now, in

0:17:36.880 --> 0:17:39.159
<v Speaker 1>this case, the scripts were sets of rules. They're kind

0:17:39.160 --> 0:17:41.280
<v Speaker 1>of like, you know, like a protocol or an algorithm

0:17:41.280 --> 0:17:45.639
<v Speaker 1>in a way. These rules dictated how Eliza would respond

0:17:45.680 --> 0:17:49.000
<v Speaker 1>to messages in order to cut down on that huge,

0:17:49.320 --> 0:17:51.760
<v Speaker 1>massive number of variables we were talking about, that the

0:17:51.840 --> 0:17:55.800
<v Speaker 1>whole unrestricted, unpredictable thing, And so they would have different

0:17:56.080 --> 0:17:58.840
<v Speaker 1>uh kind of like like overlays. Think of him as

0:17:58.880 --> 0:18:02.000
<v Speaker 1>an overlay that would kind of guide Aliza's responses, And

0:18:02.000 --> 0:18:05.880
<v Speaker 1>the most well known one was called Doctor, which put

0:18:05.880 --> 0:18:11.080
<v Speaker 1>Eliza in the role of a Rogerian psychiatrist. Uh. This

0:18:11.160 --> 0:18:13.959
<v Speaker 1>is the person who responds to everything with a question.

0:18:14.040 --> 0:18:17.760
<v Speaker 1>Al right. It's that it's that passive interview style where

0:18:17.760 --> 0:18:20.719
<v Speaker 1>where you know, you repeat back. You know, if if

0:18:20.920 --> 0:18:23.080
<v Speaker 1>if I go, oh, man, like I'm I'm I'm really

0:18:23.119 --> 0:18:26.120
<v Speaker 1>sad about my cat, Oh, tell what is it about

0:18:26.119 --> 0:18:28.280
<v Speaker 1>your cat that makes you sad? And then you can

0:18:28.359 --> 0:18:30.400
<v Speaker 1>say things like you know, And that's one of those

0:18:30.400 --> 0:18:34.639
<v Speaker 1>things that where as a conversation starts to wind down,

0:18:34.960 --> 0:18:37.600
<v Speaker 1>you then have another line of questions, So tell me

0:18:37.640 --> 0:18:40.639
<v Speaker 1>more about your mother, like that the whole tell me

0:18:40.720 --> 0:18:42.879
<v Speaker 1>about your mother thing. That's really coming back to this

0:18:42.960 --> 0:18:45.200
<v Speaker 1>kind of model of psychiatrists. But yeah, if you've ever

0:18:45.240 --> 0:18:48.520
<v Speaker 1>heard the joke about them responding to anything with another question,

0:18:48.960 --> 0:18:51.000
<v Speaker 1>so I just just taking the last word and turning

0:18:51.040 --> 0:18:53.560
<v Speaker 1>it into a question what am I paying you for?

0:18:53.720 --> 0:18:57.800
<v Speaker 1>Why do you think you're paying for? That kind of thing? Uh?

0:18:57.840 --> 0:19:00.880
<v Speaker 1>So that's what that's how Aliza spotted and in fact,

0:19:00.920 --> 0:19:07.080
<v Speaker 1>you can find examples of the Eliza proscript transcripts, and

0:19:07.119 --> 0:19:10.080
<v Speaker 1>even even the actual there's there. There are ports you

0:19:10.119 --> 0:19:13.119
<v Speaker 1>could say, or people have essentially created their own version

0:19:13.119 --> 0:19:16.199
<v Speaker 1>of Eliza just using the originalize as a guide. You

0:19:16.240 --> 0:19:18.439
<v Speaker 1>can find tons of them on the web, and you

0:19:18.480 --> 0:19:21.640
<v Speaker 1>can attempt to have a conversation with them. It's not

0:19:21.880 --> 0:19:25.520
<v Speaker 1>terribly compelling, but it's it's kind of fun. Usually within

0:19:25.640 --> 0:19:28.840
<v Speaker 1>maybe four or five exchanges, you've already run into something

0:19:28.840 --> 0:19:31.760
<v Speaker 1>where you're like, well, this can't be a person, or

0:19:31.800 --> 0:19:33.880
<v Speaker 1>if it's a person, it's the weirdest person I've ever

0:19:34.040 --> 0:19:36.719
<v Speaker 1>conversed with. But but again, it wasn't really an earnest

0:19:36.720 --> 0:19:41.119
<v Speaker 1>attempt to to create something that would pass the quote

0:19:41.160 --> 0:19:43.359
<v Speaker 1>unquote tearing tests, right, which I don't think was being

0:19:43.400 --> 0:19:45.199
<v Speaker 1>referred to as such at that point yet. Yeah, it

0:19:45.240 --> 0:19:48.199
<v Speaker 1>was kind of people knew about tourings prediction, but it

0:19:48.240 --> 0:19:51.400
<v Speaker 1>wasn't so much called a Turing test. Another chat bought

0:19:51.440 --> 0:19:54.480
<v Speaker 1>that premiered in the early nineteen seventies went even further

0:19:54.560 --> 0:19:58.080
<v Speaker 1>and actually was an attempt to try and pass the

0:19:58.119 --> 0:20:01.160
<v Speaker 1>Turing test in a very specific approach, kind of like

0:20:01.560 --> 0:20:04.000
<v Speaker 1>you know, Eugene Goostman is a very specific approach to

0:20:04.119 --> 0:20:07.120
<v Speaker 1>narrow down that those parameters. In this case, this one

0:20:07.200 --> 0:20:10.920
<v Speaker 1>was called Perry p A R R y A. Right,

0:20:10.960 --> 0:20:15.000
<v Speaker 1>and Kenneth Colby created it too to emulate a patient

0:20:15.119 --> 0:20:18.919
<v Speaker 1>who has paranoid schizophrenia. Yeah, someone who has you know,

0:20:18.960 --> 0:20:23.679
<v Speaker 1>sort of a persecution complex. Uh. They imagined that that

0:20:23.840 --> 0:20:27.520
<v Speaker 1>there are people or other entities that are out to

0:20:27.560 --> 0:20:31.720
<v Speaker 1>get them, and in this uh specific case, he kinda

0:20:31.960 --> 0:20:35.919
<v Speaker 1>he kind of really embraced this approach. It reminds me

0:20:35.960 --> 0:20:39.639
<v Speaker 1>of people who create a like a Dungeons and Dragon's character,

0:20:39.680 --> 0:20:42.600
<v Speaker 1>but then give their character an entire backstory. Yeah. Yeah, yeah,

0:20:42.600 --> 0:20:45.720
<v Speaker 1>this this Perry persona was an entire persona. It was

0:20:45.720 --> 0:20:47.560
<v Speaker 1>a twenty eight year old man with a job as

0:20:47.560 --> 0:20:50.200
<v Speaker 1>a post office clerk who was single, had no brothers

0:20:50.200 --> 0:20:54.000
<v Speaker 1>and sisters, and rarely saw his parents. He had specific hobbies.

0:20:54.080 --> 0:20:57.200
<v Speaker 1>He liked to go to the movies and horse racing. Yeah,

0:20:57.200 --> 0:20:59.800
<v Speaker 1>he liked to bet on the horses. Uh. And he

0:21:00.080 --> 0:21:02.280
<v Speaker 1>placed about with bookies in the past, right, and that

0:21:03.080 --> 0:21:07.520
<v Speaker 1>he realized later bookies have an association with the criminal

0:21:07.640 --> 0:21:11.919
<v Speaker 1>underworld and that therefore the mafia knew about him and

0:21:12.040 --> 0:21:14.199
<v Speaker 1>we're out to get him. Now, now all of that

0:21:14.280 --> 0:21:16.760
<v Speaker 1>might sound very ridiculous to you if you never had

0:21:16.840 --> 0:21:20.920
<v Speaker 1>any kind of interaction with someone who suffers from paranoid schizophrenia,

0:21:21.040 --> 0:21:23.880
<v Speaker 1>that can seem like, well, that seems cartoonish. But no, this,

0:21:23.880 --> 0:21:28.000
<v Speaker 1>this kind of thinking is not uncommon, you know, whether

0:21:28.080 --> 0:21:31.399
<v Speaker 1>it's whether it's a criminal organization or the government or

0:21:31.520 --> 0:21:36.160
<v Speaker 1>some other even unnamed entity. Oh absolutely, uh, it's it's

0:21:36.280 --> 0:21:39.440
<v Speaker 1>very much realistic in terms of that kind of diagnosis.

0:21:39.520 --> 0:21:41.520
<v Speaker 1>And and if I was speaking about it with humor

0:21:41.520 --> 0:21:43.399
<v Speaker 1>in my voice a moment ago, it's it's only because

0:21:43.440 --> 0:21:47.359
<v Speaker 1>I am absolutely tickled that the programmers of this of

0:21:47.440 --> 0:21:51.199
<v Speaker 1>this program built it, built it in. Yeah, I mean

0:21:51.440 --> 0:21:54.360
<v Speaker 1>it's it's actually pretty entertaining that they went so far

0:21:54.400 --> 0:21:57.720
<v Speaker 1>as to make this whole, uh, this whole backstory to explain,

0:21:57.760 --> 0:22:01.160
<v Speaker 1>because that's what gives it the believability, and then they

0:22:01.240 --> 0:22:04.160
<v Speaker 1>ended up testing it in conversation with a human. Perry

0:22:04.200 --> 0:22:08.640
<v Speaker 1>would gradually start to introduce his thoughts quote unquote thoughts

0:22:08.680 --> 0:22:12.359
<v Speaker 1>about being persecuted, and would respond sensitively to anything said

0:22:12.359 --> 0:22:16.280
<v Speaker 1>about his appearance, family, or religious beliefs. I've actually seen

0:22:16.400 --> 0:22:19.320
<v Speaker 1>lots of transcripts of conversations with Perry, and sure enough,

0:22:19.560 --> 0:22:21.920
<v Speaker 1>it's one of those things where you know, you might

0:22:22.280 --> 0:22:24.639
<v Speaker 1>have a few exchanges and then Perry ends up saying

0:22:24.760 --> 0:22:28.520
<v Speaker 1>something that seems really odd, but not so odd as

0:22:28.560 --> 0:22:31.680
<v Speaker 1>to seem artificial. It just seems like it's a non sequitur,

0:22:32.240 --> 0:22:34.280
<v Speaker 1>you know, something like, well, that's what they want you

0:22:34.320 --> 0:22:35.760
<v Speaker 1>to think. And if you were to say, who are

0:22:35.800 --> 0:22:38.840
<v Speaker 1>they the mafia? Who did you think I was talking about?

0:22:39.520 --> 0:22:42.760
<v Speaker 1>Like the mafia after you? Of course they're after me.

0:22:43.240 --> 0:22:44.879
<v Speaker 1>They know who I am. That kind of stuff, and

0:22:45.119 --> 0:22:48.040
<v Speaker 1>it's disturbing, like it's you know, when you know what

0:22:48.080 --> 0:22:50.199
<v Speaker 1>it is, it's kind of amusing, but like if you're

0:22:50.200 --> 0:22:55.040
<v Speaker 1>in the middle of a conversation, join, oh this poor person. Yeah.

0:22:55.200 --> 0:22:58.560
<v Speaker 1>And so in order to test it, Kolby did a

0:22:58.560 --> 0:23:01.880
<v Speaker 1>couple of different things. Did one test where eight psychiatrists

0:23:01.920 --> 0:23:06.040
<v Speaker 1>interviewed both Perry and a human patient via teletypewriter. So

0:23:06.359 --> 0:23:10.879
<v Speaker 1>in both cases the the the psychiatrists could not see

0:23:10.920 --> 0:23:12.639
<v Speaker 1>who they were interviewing. This is going back to the

0:23:12.680 --> 0:23:15.560
<v Speaker 1>kind of the original Touring test idea, or at least

0:23:15.560 --> 0:23:19.960
<v Speaker 1>Touring's proposed experiment, and in this case, only two of

0:23:19.960 --> 0:23:21.879
<v Speaker 1>the eight were able to identify that one of the

0:23:21.880 --> 0:23:24.800
<v Speaker 1>interviewees was human. And the other was a machine. In

0:23:24.840 --> 0:23:28.760
<v Speaker 1>a second test, Colby presented a group of a hundred psychiatrists,

0:23:29.040 --> 0:23:34.720
<v Speaker 1>almost a psychics, transcripts of interviews between Perry changed the Yeah,

0:23:34.960 --> 0:23:39.480
<v Speaker 1>he had he had pairs of exactly I foresee no.

0:23:39.640 --> 0:23:44.160
<v Speaker 1>But they gave these psychiatrists transcripts of interviews between an

0:23:44.160 --> 0:23:46.879
<v Speaker 1>interviewer and Perry, and an interviewer and a human patient,

0:23:47.680 --> 0:23:51.119
<v Speaker 1>and forty out of the responded. I don't know if

0:23:51.119 --> 0:23:54.040
<v Speaker 1>the other sixty just never got it or if they didn't.

0:23:54.920 --> 0:23:58.080
<v Speaker 1>Response rates are variable, right, so I'll the forty who responded,

0:23:58.160 --> 0:24:03.199
<v Speaker 1>nineteen of them guessed incorrectly. So that's almost a fifty percent,

0:24:03.840 --> 0:24:06.840
<v Speaker 1>you know, getting you know, right up there with a

0:24:06.920 --> 0:24:12.639
<v Speaker 1>pretty impressive amount. Now, again, we have to look at

0:24:12.680 --> 0:24:15.480
<v Speaker 1>the fact that Perry is operating under a very restricted,

0:24:15.920 --> 0:24:20.200
<v Speaker 1>uh set of rules. We're talking about paranoid schizophrenic, someone

0:24:20.240 --> 0:24:25.160
<v Speaker 1>who we would assume would occasionally an non normative answers

0:24:25.200 --> 0:24:29.159
<v Speaker 1>exactly two conversational pieces. And and again it's it's a

0:24:29.200 --> 0:24:32.040
<v Speaker 1>limited time that you're having with this person or this

0:24:32.200 --> 0:24:37.119
<v Speaker 1>entity in this case, this this program, and uh. Because

0:24:37.560 --> 0:24:41.919
<v Speaker 1>the psychiatrists had a specific expectation of the type of

0:24:41.920 --> 0:24:45.320
<v Speaker 1>interactions they were going to see that could have affected

0:24:45.720 --> 0:24:52.600
<v Speaker 1>their their uh answer right. So ideally, in the perfect situation,

0:24:53.240 --> 0:24:56.399
<v Speaker 1>you would have this interview happening where you have no

0:24:56.520 --> 0:25:01.040
<v Speaker 1>expectation as to what the answers should be. In other words,

0:25:01.240 --> 0:25:05.239
<v Speaker 1>you don't know ahead of time that the interviewee is

0:25:05.760 --> 0:25:07.879
<v Speaker 1>having any kind of other, you know, any kind of

0:25:07.880 --> 0:25:10.760
<v Speaker 1>restrictions upon that person, so that you would be interviewing

0:25:10.840 --> 0:25:14.280
<v Speaker 1>anyone like any average person. But that's obviously not what

0:25:14.320 --> 0:25:16.159
<v Speaker 1>we're talking about here, nor was it the one for

0:25:16.200 --> 0:25:20.840
<v Speaker 1>Eugene Goost Bond. So I've also seen, by the way,

0:25:21.200 --> 0:25:25.399
<v Speaker 1>transcripts of people who set up Eliza and Perry to

0:25:25.440 --> 0:25:28.320
<v Speaker 1>talk to each other. So you have Eliza acting as

0:25:28.359 --> 0:25:35.240
<v Speaker 1>the Rogerian psychiatrist and Perry the paranoid schizophrenic, having bizarre conversations,

0:25:35.640 --> 0:25:38.240
<v Speaker 1>and they usually don't last very long because Perry gets upset,

0:25:39.960 --> 0:25:42.560
<v Speaker 1>And obviously by gets upset, I just mean that Perry

0:25:42.640 --> 0:25:46.240
<v Speaker 1>ends up essentially shutting down the conversation because Eliza just

0:25:46.280 --> 0:25:49.200
<v Speaker 1>wants to ask questions and Perry gets suspicious of people

0:25:49.200 --> 0:25:52.320
<v Speaker 1>who are asking questions, and by again get suspicious, I'm

0:25:52.320 --> 0:25:54.919
<v Speaker 1>saying following specific rules that make it feel like this.

0:25:55.320 --> 0:25:58.240
<v Speaker 1>Computer programs getting suspicious, but they are entertaining. If you

0:25:58.280 --> 0:26:01.480
<v Speaker 1>ever do a search on line, just look for Eliza

0:26:01.600 --> 0:26:04.480
<v Speaker 1>Perry transcripts. There. There are a few of them, and

0:26:04.520 --> 0:26:08.040
<v Speaker 1>they're all pretty entertaining. But so since since that time,

0:26:08.119 --> 0:26:10.880
<v Speaker 1>I mean obviously, lots and lots of chatbots have been

0:26:10.920 --> 0:26:13.760
<v Speaker 1>created for multiple reasons. Oh yeah, well, you know, some

0:26:13.840 --> 0:26:16.280
<v Speaker 1>of them are trying to test the Turing test, and

0:26:16.440 --> 0:26:19.640
<v Speaker 1>others are trying to fool you into giving out your

0:26:19.680 --> 0:26:22.400
<v Speaker 1>credit card information or plaining on a link that has

0:26:22.480 --> 0:26:27.680
<v Speaker 1>malicious uh links to malicious software. Yeah, anyone who's been

0:26:27.720 --> 0:26:33.280
<v Speaker 1>on any kind of chat program, specifically like AIM has

0:26:33.320 --> 0:26:35.720
<v Speaker 1>probably encountered this at least once or twice, where they're

0:26:35.720 --> 0:26:41.440
<v Speaker 1>they're getting an unsolicited message from someone or something or something. Yeah,

0:26:41.760 --> 0:26:43.760
<v Speaker 1>if you type a couple of times, you realize, oh,

0:26:43.760 --> 0:26:46.919
<v Speaker 1>this is not actually this is an attempt for to

0:26:47.000 --> 0:26:49.439
<v Speaker 1>either get information from me or have me click on

0:26:49.440 --> 0:26:53.400
<v Speaker 1>a link. Yeah, that's a that's a thing. But there

0:26:53.440 --> 0:26:58.439
<v Speaker 1>are some examples of uh, I guess saying legitimate is weird,

0:26:58.480 --> 0:27:01.280
<v Speaker 1>but there are some examples of they're more and more

0:27:01.320 --> 0:27:06.760
<v Speaker 1>scholarly attempts. Yeah, like a PC therapist that one was

0:27:06.920 --> 0:27:12.880
<v Speaker 1>by Joseph Weintraub, and it fooled of its judges into

0:27:12.880 --> 0:27:17.040
<v Speaker 1>thinking that it was human. Of ten judges, of course,

0:27:17.119 --> 0:27:19.359
<v Speaker 1>so like, if I'm doing my math correctly, that's five

0:27:19.560 --> 0:27:24.120
<v Speaker 1>that I believe you are. Unless we're talking about quantum judges. Um,

0:27:24.119 --> 0:27:26.359
<v Speaker 1>these judges were both right and wrong at the same time.

0:27:27.119 --> 0:27:30.680
<v Speaker 1>And um, and it was it was a whimsical program.

0:27:30.720 --> 0:27:32.800
<v Speaker 1>I guess you could say, yeah, it had come some

0:27:33.520 --> 0:27:35.240
<v Speaker 1>I think it's fair to say its answers could be

0:27:35.240 --> 0:27:39.160
<v Speaker 1>pretty smart ass. Also, I read some of these transcripts

0:27:39.160 --> 0:27:42.399
<v Speaker 1>and it actually surprised me that enough judges thought that

0:27:42.480 --> 0:27:44.720
<v Speaker 1>it was a person. Maybe they thought it was a

0:27:44.760 --> 0:27:48.119
<v Speaker 1>person who was purposefully attempting to fool them into thinking

0:27:48.119 --> 0:27:50.680
<v Speaker 1>it was a computer, huh, you know, because it would

0:27:50.680 --> 0:27:53.000
<v Speaker 1>say things like I compute, therefore I am that kind

0:27:53.000 --> 0:27:57.280
<v Speaker 1>of stuff where it was specifically yeah. So you're looking

0:27:57.280 --> 0:27:59.000
<v Speaker 1>at this stuff and you're thinking, all right, well, maybe

0:27:59.040 --> 0:28:01.080
<v Speaker 1>this is kind of going back to that original touring

0:28:01.119 --> 0:28:05.040
<v Speaker 1>test party game, where the the effort is for a

0:28:05.160 --> 0:28:07.480
<v Speaker 1>person like the person who's being interviewed is trying to

0:28:07.520 --> 0:28:11.000
<v Speaker 1>throw everybody off, and that's perfectly within the rules, unless

0:28:11.040 --> 0:28:13.720
<v Speaker 1>you stay upfront. No, just be honest in your in

0:28:13.720 --> 0:28:15.960
<v Speaker 1>your answers. There's nothing in here, by the way that

0:28:16.040 --> 0:28:19.880
<v Speaker 1>says that the interviewee has to tell the truth necessarily,

0:28:20.200 --> 0:28:22.480
<v Speaker 1>unless you just state that as a parameter at the beginning.

0:28:23.160 --> 0:28:24.919
<v Speaker 1>So in other words, you could you could be like,

0:28:25.000 --> 0:28:28.480
<v Speaker 1>I'm totally the computer and you're the human being interviewed. Uh.

0:28:28.640 --> 0:28:30.720
<v Speaker 1>I don't know if that's a fair way of saying

0:28:30.800 --> 0:28:34.720
<v Speaker 1>that the device won or lost, but it is a possibility. Uh.

0:28:34.800 --> 0:28:36.520
<v Speaker 1>Then we have a two thousand eleven. Now, this one

0:28:36.560 --> 0:28:40.440
<v Speaker 1>is a really pretty impressive one. And this was clever Butt,

0:28:40.960 --> 0:28:44.200
<v Speaker 1>which was made by a fellow named Rollo Carpenter, and

0:28:44.240 --> 0:28:47.520
<v Speaker 1>it fooled fifty nine point three percent of a live

0:28:47.560 --> 0:28:50.200
<v Speaker 1>audience and an event in India with more than a

0:28:50.280 --> 0:28:53.680
<v Speaker 1>thousand people. Yeah, the way this worked was that the

0:28:53.680 --> 0:28:58.360
<v Speaker 1>audience watched as interviewers interacted via text with either clever

0:28:58.440 --> 0:29:01.880
<v Speaker 1>Bot or a human in the course of a four

0:29:01.920 --> 0:29:04.680
<v Speaker 1>minute interview. So it's a little shorter than what Turing

0:29:04.720 --> 0:29:07.120
<v Speaker 1>had said, but not by not by a whole lot.

0:29:07.560 --> 0:29:09.280
<v Speaker 1>In four mints is still a good amount of time.

0:29:09.440 --> 0:29:13.080
<v Speaker 1>Sure that that is twenty less, that's true, that's true.

0:29:13.360 --> 0:29:16.440
<v Speaker 1>So keep that in mind. But but at any rate,

0:29:16.520 --> 0:29:19.520
<v Speaker 1>it was you know, pretty interesting experience. And also from

0:29:19.520 --> 0:29:24.400
<v Speaker 1>why I read they misidentified, they thought that the human

0:29:24.480 --> 0:29:28.640
<v Speaker 1>was a computer sixty of the time. Um, because they

0:29:28.640 --> 0:29:32.160
<v Speaker 1>didn't necessarily just say that it was a computer or

0:29:32.200 --> 0:29:37.480
<v Speaker 1>it was. So now we see that there are a

0:29:37.520 --> 0:29:41.560
<v Speaker 1>few examples of chat bots quote unquote passing the Turing test.

0:29:42.000 --> 0:29:45.600
<v Speaker 1>So what does that mean. Does it mean that the

0:29:45.720 --> 0:29:52.120
<v Speaker 1>machines are actually thinking? Um? No, I mean, and it's

0:29:52.160 --> 0:29:53.880
<v Speaker 1>not to say that that computers don't have a certain

0:29:53.920 --> 0:29:57.880
<v Speaker 1>amount of machine intelligence, but there's absolutely a distinction between

0:29:57.920 --> 0:30:01.600
<v Speaker 1>that and what we consider to be human intelligence. That's true.

0:30:01.840 --> 0:30:04.720
<v Speaker 1>The programmers themselves have said that this doesn't mean a

0:30:04.760 --> 0:30:08.760
<v Speaker 1>machine is able to think. Uh, they're just able to

0:30:08.840 --> 0:30:12.640
<v Speaker 1>interpret commands then to follow a set of rules to

0:30:12.840 --> 0:30:16.320
<v Speaker 1>make a response, which is still pretty cool. And and

0:30:16.360 --> 0:30:18.960
<v Speaker 1>it doesn't It certainly doesn't mean that the Turing test

0:30:19.200 --> 0:30:22.640
<v Speaker 1>is worthless as an exercise. No, it is. In fact,

0:30:22.680 --> 0:30:27.080
<v Speaker 1>it's improving our ability to create programs that that can

0:30:27.200 --> 0:30:31.800
<v Speaker 1>understand or at least respond to natural language. Natural language

0:30:31.840 --> 0:30:34.280
<v Speaker 1>recognition is one of those big things where if you're

0:30:34.360 --> 0:30:36.880
<v Speaker 1>really able to crack it, then you can have some

0:30:37.000 --> 0:30:39.840
<v Speaker 1>amazing opportunities open up, and we've seen this recently with

0:30:39.880 --> 0:30:43.520
<v Speaker 1>stuff like Siri. Oh absolutely being able to speak to

0:30:43.560 --> 0:30:46.840
<v Speaker 1>your computer rather than having to I mean, even if

0:30:46.880 --> 0:30:49.240
<v Speaker 1>you could speak to your computer through a keyboard and

0:30:49.360 --> 0:30:51.920
<v Speaker 1>have it understand what you're what you're saying, I mean,

0:30:51.960 --> 0:30:55.240
<v Speaker 1>like it's it's the reason why Google spends so much

0:30:55.280 --> 0:30:57.960
<v Speaker 1>time and money, and it's search algorithms of of trying

0:30:58.000 --> 0:31:01.040
<v Speaker 1>to figure out what you really mean when you search

0:31:01.120 --> 0:31:06.200
<v Speaker 1>for a certain phrase, because traditionally, you know, before we

0:31:06.320 --> 0:31:10.880
<v Speaker 1>really got into the natural language recognition era, it meant

0:31:10.880 --> 0:31:12.479
<v Speaker 1>that in order to work with a computer, you had

0:31:12.520 --> 0:31:14.800
<v Speaker 1>to work with a computer on the computer's terms. You

0:31:14.840 --> 0:31:17.000
<v Speaker 1>had to learn the commands, you had to learn the

0:31:17.000 --> 0:31:19.560
<v Speaker 1>way to navigate a computer system in order for it

0:31:19.560 --> 0:31:21.880
<v Speaker 1>to do what you wanted it to do. Once you

0:31:21.880 --> 0:31:25.000
<v Speaker 1>get to a point where natural language recognition software is

0:31:25.680 --> 0:31:29.920
<v Speaker 1>robust enough the computer is working on your terms, you

0:31:29.920 --> 0:31:33.600
<v Speaker 1>you can put in however you're thinking, like whatever, whatever

0:31:34.080 --> 0:31:37.920
<v Speaker 1>mental exercise you've gone through to ask this computer to

0:31:37.960 --> 0:31:41.840
<v Speaker 1>do something, whatever you do to kind of express a thought,

0:31:42.440 --> 0:31:45.239
<v Speaker 1>uh as a command to this computer, the computer can

0:31:45.280 --> 0:31:49.600
<v Speaker 1>then interpret then respond and it's not just for serving

0:31:49.640 --> 0:31:52.640
<v Speaker 1>you back whatever information you happen to be looking for.

0:31:52.760 --> 0:31:55.280
<v Speaker 1>It's I mean, I mean, we're talking about being able

0:31:55.280 --> 0:31:58.360
<v Speaker 1>to just look at a computer and say, you know,

0:31:58.560 --> 0:32:02.360
<v Speaker 1>I really want a graph that looks blue and has

0:32:02.440 --> 0:32:06.400
<v Speaker 1>these percentages in it and is about this thing, and

0:32:06.440 --> 0:32:08.680
<v Speaker 1>it just doesn't. Yeah, like I want to see what

0:32:08.800 --> 0:32:12.640
<v Speaker 1>the population distribution of Atlanta is in a bar chart

0:32:12.760 --> 0:32:15.360
<v Speaker 1>or something, and then it could bring that shows out,

0:32:15.440 --> 0:32:18.640
<v Speaker 1>finds that information, put it into a bar chart, and yeah,

0:32:18.640 --> 0:32:21.440
<v Speaker 1>that's pretty phenomenal stuff. We have a little bit more

0:32:21.480 --> 0:32:23.760
<v Speaker 1>to say about passing the Turing test, but before we

0:32:23.800 --> 0:32:33.960
<v Speaker 1>get to that, let's take another quick break. We see

0:32:34.000 --> 0:32:37.480
<v Speaker 1>other examples of machine intelligence everywhere, things like pattern recognition,

0:32:37.520 --> 0:32:42.920
<v Speaker 1>probabilistic predictions, for example, Pandora. You know the Music Genome project.

0:32:42.960 --> 0:32:45.920
<v Speaker 1>It's yeah, that's that's pattern recognition. Yeah, it's looking for

0:32:47.000 --> 0:32:49.480
<v Speaker 1>elements of songs that you say you like and then

0:32:49.520 --> 0:32:52.440
<v Speaker 1>looking for other stuff that's not in the specific category

0:32:52.480 --> 0:32:56.960
<v Speaker 1>you mentioned or the specific examples you mentioned, and there's

0:32:57.000 --> 0:32:58.800
<v Speaker 1>something else you probably will like because you like these

0:32:58.800 --> 0:33:01.800
<v Speaker 1>other things that also have this stuff in it. Uh,

0:33:01.840 --> 0:33:05.320
<v Speaker 1>you know, sometimes that's less functional than other times. It

0:33:05.360 --> 0:33:07.880
<v Speaker 1>makes me think of Patton Oswald has a great routine

0:33:07.920 --> 0:33:10.120
<v Speaker 1>about TiVo that does the same sort of thing where

0:33:10.160 --> 0:33:12.840
<v Speaker 1>he says, you know, TiVo is great. I mean, I like,

0:33:12.920 --> 0:33:15.760
<v Speaker 1>I love Westerns, and I'll have it set to TiVo

0:33:15.840 --> 0:33:17.600
<v Speaker 1>a Western for me, and I come back, and then

0:33:17.640 --> 0:33:20.120
<v Speaker 1>they'll be all these other Westerns that will be suggested.

0:33:20.160 --> 0:33:22.960
<v Speaker 1>I didn't even know about. Thank you, TiVo. But then

0:33:23.040 --> 0:33:25.560
<v Speaker 1>sometimes TiVo gets it wrong and I come back and

0:33:25.600 --> 0:33:29.600
<v Speaker 1>everything has got horses in it, because Westerns have horses

0:33:29.600 --> 0:33:31.960
<v Speaker 1>in it. So I've got my little pony and cartoons

0:33:31.960 --> 0:33:34.760
<v Speaker 1>with horses and unicorns and things, and I have to say, no, TiVo,

0:33:34.960 --> 0:33:38.040
<v Speaker 1>that's a bad TiVo. But TiVo says, but you said

0:33:38.080 --> 0:33:41.480
<v Speaker 1>you liked horses. Same sort of thing. Like when you

0:33:41.560 --> 0:33:45.920
<v Speaker 1>get more sophisticated than the the computer program starts to

0:33:45.960 --> 0:33:50.200
<v Speaker 1>anticipate things and makes these probabilistic models. These these models

0:33:50.200 --> 0:33:56.000
<v Speaker 1>where there there are certain percentages associated with various responses,

0:33:56.080 --> 0:33:58.640
<v Speaker 1>and it goes with whichever one seems to be the

0:33:58.640 --> 0:34:01.720
<v Speaker 1>most prevalent, assoning it meets a threshold. If this sounds

0:34:01.720 --> 0:34:06.239
<v Speaker 1>familiar to you, it's because that's how IBM S. Watson worked, right,

0:34:06.320 --> 0:34:10.880
<v Speaker 1>which is a really good example of natural language recognition, absolutely,

0:34:10.920 --> 0:34:13.840
<v Speaker 1>because not only was it able to recognize natural language,

0:34:14.160 --> 0:34:18.440
<v Speaker 1>it had to interpret things like wordplay that Jeopardy do.

0:34:18.600 --> 0:34:21.080
<v Speaker 1>This is the machine that went up on Jeopardy and

0:34:21.120 --> 0:34:26.239
<v Speaker 1>beat the returning champions or former champions. Uh And you know,

0:34:26.280 --> 0:34:29.520
<v Speaker 1>if you've ever played Jeopardy or watched Jeopardy, you know

0:34:29.600 --> 0:34:32.960
<v Speaker 1>that there are categories that depend on things like puns

0:34:33.160 --> 0:34:37.200
<v Speaker 1>or hominem's or other forms of word play. So it

0:34:37.239 --> 0:34:39.879
<v Speaker 1>has to parse all of that, and that's even more

0:34:39.920 --> 0:34:42.719
<v Speaker 1>complicated than just taking a simple sentence and figuring out,

0:34:43.080 --> 0:34:46.440
<v Speaker 1>all right, what are the potential responses to whatever this

0:34:46.440 --> 0:34:50.640
<v Speaker 1>this this phrase is so great, great example. You know,

0:34:50.680 --> 0:34:53.280
<v Speaker 1>they would end up coming up with a potential answer.

0:34:53.760 --> 0:34:57.160
<v Speaker 1>It would assign a percentage of how quote unquote sure

0:34:57.320 --> 0:34:59.680
<v Speaker 1>it was that that was the right answer, and if

0:34:59.680 --> 0:35:02.359
<v Speaker 1>the percentage was higher than its threshold, which I think

0:35:02.400 --> 0:35:05.919
<v Speaker 1>was something like that, it would buzz in and give

0:35:05.920 --> 0:35:09.239
<v Speaker 1>that as a guess. Sometimes it was wrong, but it

0:35:09.280 --> 0:35:12.120
<v Speaker 1>was right a lot of the time, so that's kind

0:35:12.120 --> 0:35:17.799
<v Speaker 1>of cool. Uh So, getting back to Eugene Gene, the

0:35:17.800 --> 0:35:19.759
<v Speaker 1>main machine as I called him in in my notes

0:35:19.800 --> 0:35:23.560
<v Speaker 1>at one point. Uh And of course, I'm anthropomorphizing when

0:35:23.560 --> 0:35:25.640
<v Speaker 1>I say him, it's a it's a it's an it. Well,

0:35:25.880 --> 0:35:27.879
<v Speaker 1>it has a dude name. Yeah, it has a dude

0:35:27.960 --> 0:35:31.520
<v Speaker 1>name and a dude persona. But it's ultimately, isn't it.

0:35:33.440 --> 0:35:37.440
<v Speaker 1>Would you say that perhaps some of the reporting around

0:35:37.440 --> 0:35:40.960
<v Speaker 1>this was was maybe a little misleading or at least

0:35:41.680 --> 0:35:47.040
<v Speaker 1>hype is well, you know, Okay, the entire Eugene Gooseman

0:35:47.239 --> 0:35:51.080
<v Speaker 1>chat bought sounds really cool. I haven't met it personally, No,

0:35:51.360 --> 0:35:54.440
<v Speaker 1>I haven't either, although you can. There is an Internet version,

0:35:54.560 --> 0:35:56.399
<v Speaker 1>and I'm not sure that it's the same version that's

0:35:56.400 --> 0:35:59.160
<v Speaker 1>being used in competition, because I've seen some transcripts from

0:35:59.160 --> 0:36:02.480
<v Speaker 1>the Internet version and they don't seem good at all.

0:36:02.800 --> 0:36:05.160
<v Speaker 1>They seem bad, right, I guess you'd have to talk

0:36:05.200 --> 0:36:09.080
<v Speaker 1>to some actual thirteen year old boys from actually, yeah,

0:36:09.120 --> 0:36:12.760
<v Speaker 1>that this is part of it. You know. There's certainly

0:36:12.800 --> 0:36:18.520
<v Speaker 1>been some some questions among uh natural language AI enthusiasts

0:36:18.520 --> 0:36:22.400
<v Speaker 1>online about whether we're really just lowering our expectations for

0:36:22.520 --> 0:36:26.040
<v Speaker 1>human communication. Which, yeah, that's that's a totally different way

0:36:26.040 --> 0:36:29.480
<v Speaker 1>of looking at and a depressing one to say that, Oh, well,

0:36:29.520 --> 0:36:32.040
<v Speaker 1>if you come from this place and if you are

0:36:32.160 --> 0:36:34.719
<v Speaker 1>of this age, then I expect you to only be

0:36:34.800 --> 0:36:40.280
<v Speaker 1>able to communicate at this level, right, which is depressing.

0:36:40.800 --> 0:36:42.680
<v Speaker 1>It certainly is well, but you know, but it's a

0:36:42.760 --> 0:36:45.000
<v Speaker 1>valid point, I think. I think it's a good thing

0:36:45.000 --> 0:36:48.319
<v Speaker 1>to be thinking about in this kind of situation. UM.

0:36:48.560 --> 0:36:51.359
<v Speaker 1>You know. Beyond that though, and I certainly don't want

0:36:51.400 --> 0:36:57.279
<v Speaker 1>to downplay the apparent achievements of its programmers, because I

0:36:57.320 --> 0:37:02.239
<v Speaker 1>haven't programmed any capable chatbots today, I it's been ever

0:37:02.480 --> 0:37:05.560
<v Speaker 1>since I did. But there are a few things that

0:37:05.600 --> 0:37:08.520
<v Speaker 1>are just a little bit shady about the news UM.

0:37:08.960 --> 0:37:12.520
<v Speaker 1>First off, the original press release, which came out of

0:37:12.560 --> 0:37:16.400
<v Speaker 1>the University of Reading, I believe so UM stated that

0:37:16.560 --> 0:37:22.600
<v Speaker 1>a quote supercomputer had achieved this feat, and perhaps charitably,

0:37:22.719 --> 0:37:25.680
<v Speaker 1>it was a mistake or misunderstanding on the part of

0:37:25.920 --> 0:37:28.440
<v Speaker 1>the writer of the press release, but some skeptics have

0:37:28.600 --> 0:37:32.640
<v Speaker 1>suggested that it was in fact a purposeful publicity play

0:37:32.680 --> 0:37:34.719
<v Speaker 1>that in fact worked, because a whole lot of news

0:37:34.800 --> 0:37:39.680
<v Speaker 1>headlines around the interwebs repeated the error very excitedly. Yes,

0:37:39.680 --> 0:37:42.000
<v Speaker 1>because it was not a supercomputer. It was a computer

0:37:42.160 --> 0:37:44.440
<v Speaker 1>running a piece of software. It's a program, Yes, the

0:37:44.440 --> 0:37:46.640
<v Speaker 1>program that did the work. I mean, the computer just

0:37:46.760 --> 0:37:50.040
<v Speaker 1>provided the horsepower. Right, it's the software that did all

0:37:50.040 --> 0:37:52.200
<v Speaker 1>the action work, and it was not It wasn't on

0:37:52.239 --> 0:37:58.719
<v Speaker 1>a supercomputer. Little little known fact. Supercomputers have better things

0:37:58.760 --> 0:38:03.560
<v Speaker 1>to do than run chat bought software generally. Yeah. Yeah,

0:38:03.600 --> 0:38:07.440
<v Speaker 1>we're talking about things like figuring out global weather changing

0:38:07.840 --> 0:38:10.239
<v Speaker 1>change patterns and things like that, you know, or or

0:38:10.280 --> 0:38:14.839
<v Speaker 1>the way that money works. Chat bots low on their

0:38:14.840 --> 0:38:19.399
<v Speaker 1>priority list. It's like number seven at least. Um And

0:38:19.400 --> 0:38:23.120
<v Speaker 1>and also that this press release in question was largely

0:38:23.280 --> 0:38:28.240
<v Speaker 1>a quotation from Dr Kevin Warwick. Kevin Warwick, of course

0:38:28.280 --> 0:38:33.600
<v Speaker 1>being the fellow who organized this entire competition. Um who

0:38:33.640 --> 0:38:36.359
<v Speaker 1>who's an engineer and a futurist, um and also the

0:38:36.440 --> 0:38:41.040
<v Speaker 1>instigator and or enjoyer of a certain amount of hype

0:38:41.120 --> 0:38:47.440
<v Speaker 1>and debate about future technologies. Yeah, he is, obviously you

0:38:47.440 --> 0:38:49.759
<v Speaker 1>can tell. This is the guy who elected to have

0:38:49.800 --> 0:38:53.120
<v Speaker 1>surgery performed on him so he could have that r

0:38:53.200 --> 0:38:55.239
<v Speaker 1>F I D chip and call himself aside Wars. This

0:38:55.280 --> 0:39:01.239
<v Speaker 1>is someone who not only embraces this these ideas of futurism,

0:39:01.239 --> 0:39:04.799
<v Speaker 1>but is actively trying to promote them and get to

0:39:04.840 --> 0:39:06.799
<v Speaker 1>them that we're not even saying that that's a bad thing.

0:39:06.840 --> 0:39:09.879
<v Speaker 1>What we are saying, is that that may give him

0:39:09.920 --> 0:39:13.200
<v Speaker 1>somewhat of a bias when it comes to proclaiming a

0:39:13.239 --> 0:39:17.800
<v Speaker 1>computer software piece of computer software being an amazing achievement

0:39:17.840 --> 0:39:20.760
<v Speaker 1>that beat the Turing test, right sure. I mean he

0:39:21.080 --> 0:39:24.319
<v Speaker 1>admits basically to to being a provocateur. He he says

0:39:24.360 --> 0:39:26.360
<v Speaker 1>that that's really his job, you know, it is to

0:39:26.440 --> 0:39:31.160
<v Speaker 1>get people excited about tech and engineering and in the future.

0:39:31.320 --> 0:39:34.200
<v Speaker 1>And we get that like that that we agree that's

0:39:34.200 --> 0:39:36.560
<v Speaker 1>our job too. We think it's red. We think that

0:39:36.760 --> 0:39:40.040
<v Speaker 1>perhaps I don't want to put words into your mount Lauren.

0:39:40.200 --> 0:39:42.759
<v Speaker 1>I think perhaps that there's a different way of going

0:39:42.760 --> 0:39:46.319
<v Speaker 1>about it where you can still be excited, but you

0:39:46.360 --> 0:39:49.080
<v Speaker 1>can be a little more grounded in the way you

0:39:49.160 --> 0:39:51.920
<v Speaker 1>present things, because I I also think the achievement of

0:39:51.920 --> 0:39:56.080
<v Speaker 1>creating a chatbot that could be uh convincing is a

0:39:56.120 --> 0:39:58.759
<v Speaker 1>fantastic achievement. I mean, it's something that, even under any

0:39:58.840 --> 0:40:01.879
<v Speaker 1>number of qualifications, incredibly challenging to do, no matter how

0:40:01.960 --> 0:40:05.480
<v Speaker 1>you frame it. Um. I do think, however, that if

0:40:05.520 --> 0:40:09.319
<v Speaker 1>you seem to over inflate the achievement, you run the

0:40:09.400 --> 0:40:12.839
<v Speaker 1>danger of making people feel jaded about it later, which

0:40:12.880 --> 0:40:18.080
<v Speaker 1>I think Computer Wolf exactly. Yeah, exactly. So it's one

0:40:18.120 --> 0:40:20.879
<v Speaker 1>of those things where you know, you have to take

0:40:20.880 --> 0:40:25.160
<v Speaker 1>the context into account, right and don't don't downplay the achievement,

0:40:25.200 --> 0:40:27.399
<v Speaker 1>but don't sit there and say, like, ah ha, now

0:40:27.440 --> 0:40:30.480
<v Speaker 1>we have intelligent computers everywhere. That's not that's not true either.

0:40:31.320 --> 0:40:35.480
<v Speaker 1>I saw there's a great Wired article that specifically went

0:40:35.520 --> 0:40:40.120
<v Speaker 1>into uh, kind of debunking the whole beating the Turing

0:40:40.160 --> 0:40:42.960
<v Speaker 1>test thing and again kind of saying the same thing

0:40:42.960 --> 0:40:45.920
<v Speaker 1>we're saying, like, take the context into account, and and

0:40:45.920 --> 0:40:50.000
<v Speaker 1>part of that article. They ended up asking a cognitive

0:40:50.080 --> 0:40:53.959
<v Speaker 1>scientist named Gary Marcus of n y U about this,

0:40:54.120 --> 0:40:57.480
<v Speaker 1>and Marcus proposed a new version of the Turing test

0:40:57.560 --> 0:41:00.120
<v Speaker 1>because he says the old version is not really a

0:41:00.200 --> 0:41:04.759
<v Speaker 1>measurement of machine intelligence. Uh, it does kind of illustrate

0:41:04.920 --> 0:41:08.640
<v Speaker 1>ways of creating natural language recognition and clever ways to

0:41:08.840 --> 0:41:12.520
<v Speaker 1>fool the human side, huh. And that it was very

0:41:12.600 --> 0:41:16.440
<v Speaker 1>valid historically at the time because you know, text textual

0:41:16.480 --> 0:41:20.080
<v Speaker 1>communication was new and exciting and it was you know,

0:41:20.160 --> 0:41:22.759
<v Speaker 1>it pushed the field forward, it really did. But now

0:41:22.800 --> 0:41:25.400
<v Speaker 1>we've gotten to a point where fooling the person on

0:41:25.440 --> 0:41:29.000
<v Speaker 1>the other side of a keyboard is not necessarily the

0:41:29.040 --> 0:41:31.520
<v Speaker 1>goal that we should be looking at. He proposes, the

0:41:31.560 --> 0:41:34.440
<v Speaker 1>next version of the Turing test should be that a

0:41:34.440 --> 0:41:38.280
<v Speaker 1>computer software, uh, like any kind of program that wants

0:41:38.280 --> 0:41:40.120
<v Speaker 1>to beat it, what it has to do is first

0:41:40.400 --> 0:41:45.280
<v Speaker 1>quote unquote watch a movie, television show, YouTube video something,

0:41:45.680 --> 0:41:48.000
<v Speaker 1>some kind of video media, and then be able to

0:41:48.080 --> 0:41:51.239
<v Speaker 1>respond to questions about it. So sort of like here,

0:41:51.320 --> 0:41:55.000
<v Speaker 1>let me show you this ten minute video on car safety,

0:41:55.440 --> 0:41:58.719
<v Speaker 1>and then asking questions about specifically about the video, what

0:41:58.840 --> 0:42:01.960
<v Speaker 1>happened after they fastened the seat belt, that kind of thing,

0:42:02.239 --> 0:42:04.520
<v Speaker 1>and if the computer program is able to answer it,

0:42:04.960 --> 0:42:08.160
<v Speaker 1>then that would be a much more convincing touring test

0:42:08.239 --> 0:42:12.600
<v Speaker 1>than just kind of spewing out a script, which is,

0:42:12.840 --> 0:42:16.000
<v Speaker 1>you know, it's adding another layer of difficulty on top

0:42:16.040 --> 0:42:18.520
<v Speaker 1>of an already difficult task. But that's that's the whole

0:42:18.520 --> 0:42:20.600
<v Speaker 1>only way you can go forward. Otherwise we're just going

0:42:20.640 --> 0:42:24.799
<v Speaker 1>to see increasingly sophisticated chat box. Yeah, and and that

0:42:24.960 --> 0:42:28.359
<v Speaker 1>is actually a very difficult and interesting problem. What wasn't

0:42:28.360 --> 0:42:31.000
<v Speaker 1>it just recently that there was a computer that we

0:42:31.000 --> 0:42:33.240
<v Speaker 1>we taught I mean not us personally, but that humanity,

0:42:33.920 --> 0:42:38.440
<v Speaker 1>some researchers and we're taught taught to identify cats pictures

0:42:38.440 --> 0:42:41.359
<v Speaker 1>of cats. That was the AI program that essentially went

0:42:41.400 --> 0:42:44.480
<v Speaker 1>through thousands and thousands of uh I think it was

0:42:44.600 --> 0:42:48.440
<v Speaker 1>images and videos and then became able to identify cats.

0:42:48.440 --> 0:42:51.759
<v Speaker 1>It essentially defined what a cat was because no one

0:42:51.880 --> 0:42:56.080
<v Speaker 1>taught it right. It learned what cats are based upon

0:42:56.120 --> 0:42:59.200
<v Speaker 1>their appearance, on their appearance and can look at pictures

0:42:59.200 --> 0:43:01.880
<v Speaker 1>of cats and say that is totally a cat, essentially

0:43:01.960 --> 0:43:04.239
<v Speaker 1>saying that thing that is in that video is the

0:43:04.320 --> 0:43:06.719
<v Speaker 1>same as this other thing that's in this picture. That's

0:43:06.719 --> 0:43:08.400
<v Speaker 1>the same as this other thing that's in this totally

0:43:08.440 --> 0:43:12.919
<v Speaker 1>different video, which sounds trivial and hilarious, and it kind

0:43:13.000 --> 0:43:15.719
<v Speaker 1>of is hilarious. Also easy because I mean, come on,

0:43:15.800 --> 0:43:18.720
<v Speaker 1>everything on the internet has cats in it. Yeah, that

0:43:18.600 --> 0:43:20.239
<v Speaker 1>is That is kind of a gimme, isn't it? But

0:43:20.239 --> 0:43:22.399
<v Speaker 1>but still no, it is. It is cool. I mean

0:43:22.640 --> 0:43:25.399
<v Speaker 1>because just just that level of image recognition, I mean

0:43:25.800 --> 0:43:27.680
<v Speaker 1>being able to take an object and look at it

0:43:27.760 --> 0:43:31.359
<v Speaker 1>from a different angle than you were taught or that's

0:43:31.360 --> 0:43:35.080
<v Speaker 1>a different color, different different size. Yeah, all these things.

0:43:35.120 --> 0:43:37.880
<v Speaker 1>All of these things are easy for us, hard for computers,

0:43:37.880 --> 0:43:42.400
<v Speaker 1>so seeing something make that breakthrough is really exciting. Anyway,

0:43:42.600 --> 0:43:44.440
<v Speaker 1>we thought we would take that story and kind of

0:43:44.440 --> 0:43:47.280
<v Speaker 1>break it down for you guys, explain how it's still

0:43:47.320 --> 0:43:49.759
<v Speaker 1>cool but maybe not as cool as the way some

0:43:49.800 --> 0:43:52.759
<v Speaker 1>of the headlines are saying. Right, and also say hey

0:43:52.840 --> 0:43:57.239
<v Speaker 1>internet journalists, UM, step up your game. Yeah, I understand

0:43:57.719 --> 0:43:59.759
<v Speaker 1>that you want people to read your stuff. Oh yeah,

0:43:59.800 --> 0:44:02.440
<v Speaker 1>And and you're under deadline pressure and that's terrible. But

0:44:02.520 --> 0:44:07.319
<v Speaker 1>let's look hard. Let's represent reality, shall we don't just

0:44:07.360 --> 0:44:09.600
<v Speaker 1>don't just spit out press releases the way that you

0:44:09.680 --> 0:44:12.680
<v Speaker 1>found them. Yeah, and uh, and I would be criminal

0:44:12.840 --> 0:44:17.440
<v Speaker 1>to to neglect to mention Noel. Our producer reminded me

0:44:18.040 --> 0:44:21.600
<v Speaker 1>that obviously this is a very important field of study

0:44:21.760 --> 0:44:24.240
<v Speaker 1>because we want to be able to tell the difference

0:44:24.280 --> 0:44:28.640
<v Speaker 1>between computers and humans when the future of Blade Runner

0:44:28.800 --> 0:44:32.600
<v Speaker 1>becomes our reality and you're chasing down a replicant and

0:44:32.640 --> 0:44:34.759
<v Speaker 1>you have to determine if it's actually a replicate or

0:44:34.840 --> 0:44:38.000
<v Speaker 1>human being. And that wraps up this classic episode about

0:44:38.040 --> 0:44:41.759
<v Speaker 1>passing the Turing Test. Honestly, the whole Turing Test thing,

0:44:41.880 --> 0:44:47.919
<v Speaker 1>that general concept has morphed over the decades, and it's

0:44:47.960 --> 0:44:51.319
<v Speaker 1>it's more like shorthand right. Passing the Touring test isn't

0:44:51.320 --> 0:44:55.560
<v Speaker 1>so much about passing a specific hypothetical test. It's more

0:44:55.680 --> 0:45:00.239
<v Speaker 1>about this idea of creating a machine that of here's

0:45:00.280 --> 0:45:03.920
<v Speaker 1>to be indistinguishable from a human as far as you know,

0:45:04.040 --> 0:45:07.960
<v Speaker 1>processing and communicating information so that you feel like the

0:45:08.000 --> 0:45:11.640
<v Speaker 1>machine is truly intelligent. I think the turning test is

0:45:11.680 --> 0:45:16.439
<v Speaker 1>one of those concepts that changes over time, and and

0:45:17.200 --> 0:45:19.279
<v Speaker 1>it's more like you start to find out what it's

0:45:19.360 --> 0:45:22.160
<v Speaker 1>not rather than what it is. It's an interesting things,

0:45:22.320 --> 0:45:25.719
<v Speaker 1>very much like our artificial intelligence itself, or even machine consciousness.

0:45:26.280 --> 0:45:30.360
<v Speaker 1>These are all concepts that are are kind of wibbly wobbly.

0:45:30.560 --> 0:45:33.640
<v Speaker 1>As dr who might say, well, if you have suggestions

0:45:33.640 --> 0:45:36.480
<v Speaker 1>for topics I should cover in future episodes of tech Stuff,

0:45:36.520 --> 0:45:38.440
<v Speaker 1>reach out to me. The best way to do that

0:45:38.600 --> 0:45:41.040
<v Speaker 1>is over on Twitter. The handle for the show is

0:45:41.080 --> 0:45:45.440
<v Speaker 1>text Stuff HSW and I'll talk to you again really soon.

0:45:52.080 --> 0:45:55.120
<v Speaker 1>Text Stuff is an I Heart Radio production. For more

0:45:55.200 --> 0:45:58.600
<v Speaker 1>podcasts from my Heart Radio, visit the i Heart Radio app,

0:45:58.719 --> 0:46:01.880
<v Speaker 1>Apple Podcasts, or wherever you listen to your favorite shows.