WEBVTT - Passing the Turing Test

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<v Speaker 1>Get in test with technology with text stuff from dot com.

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<v Speaker 1>Say everyone, and welcome to text Uff. I'm Jonathan Strickland,

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<v Speaker 1>and uh, you know, something hit the news recently. You

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<v Speaker 1>may have seen it, in fact, you may have seen

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<v Speaker 1>it in multiple places about a program, a computer program

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<v Speaker 1>passing the Turing test, possibly the first such program to

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<v Speaker 1>ever pass the Turing test ever. And we had planned

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<v Speaker 1>on doing an episode on this, and then on top

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<v Speaker 1>of that, one of our listeners, Nick on Twitter said,

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<v Speaker 1>just saw this headline on Google News. A computer just

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<v Speaker 1>passed the Turing test in landmark trial. So we knew

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<v Speaker 1>that the timing was perfect. Thank you Nick for writing in.

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<v Speaker 1>We are really ready to talk about this, but in

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<v Speaker 1>order to do that, it's important that we, you know,

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<v Speaker 1>kind of lay some groundwork. So first of all, the

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<v Speaker 1>Touring test is named after Alan Turing, and we've done

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<v Speaker 1>a full episode on Alan Turing way back when, back

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<v Speaker 1>in November of Yeah. Phenomenal person, amazing thinker. Yeah, one

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<v Speaker 1>of the like the grandfather of computer science. Also tragic

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<v Speaker 1>life story which we went into detail back in that story.

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<v Speaker 1>And so you might wonder why, right, So what does

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<v Speaker 1>that have to do? Was the guy who was the

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<v Speaker 1>essentially the father of computer science or grandfather of computer science.

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<v Speaker 1>What does he have to do with the story about

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<v Speaker 1>a computer program in June two thousand fourteen, a computer

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<v Speaker 1>program with an interesting name, Eugene Goostman passing the Turing test.

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<v Speaker 1>What does that all have to do with each other? Well?

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<v Speaker 1>To answer that, we have to ask what is a

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<v Speaker 1>Turing test? Well, as it turns out Away, back in

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<v Speaker 1>the nineteen fifties, he started envisioning uh I thought experiment. Yeah,

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<v Speaker 1>he published a paper in a journal called Mind in

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<v Speaker 1>ninety fifty called Computing, Machinery and Intelligence, and he sort

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<v Speaker 1>of laid out his thought experiment there. And it's interesting

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<v Speaker 1>because what he did was he took this idea of

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<v Speaker 1>a party game and then adapted it for computers. Right.

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<v Speaker 1>The party game that it's based on would have three participants,

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<v Speaker 1>an interrogator, a man, and a woman um all situated

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<v Speaker 1>so that they can't see one another, and the interrogator

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<v Speaker 1>is supposed to ask questions to try to figure out

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<v Speaker 1>which of the participants is the dude and which is

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<v Speaker 1>the lady exactly, And it's the dude's job to try

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<v Speaker 1>and mislead the interrogator to believe that that he, in fact,

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<v Speaker 1>is the lady and the other one is the man.

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<v Speaker 1>It's the lady's job to say, hey, I want you

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<v Speaker 1>to get this right. I'm the lady. That other guy

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<v Speaker 1>that's the dude. And so the interrogator has to ask questions. Now,

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<v Speaker 1>obviously they can't see each other. Because they could see

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<v Speaker 1>each other, then that would probably give things away. Probably,

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<v Speaker 1>they really shouldn't be able to hear each other because

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<v Speaker 1>that could also give things away. Sure, and if you

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<v Speaker 1>use handwritten notes, then you the interrogator might be able

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<v Speaker 1>to make judgments based on the handwriting style. So it

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<v Speaker 1>should really be typewritten, right, So you want to you

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<v Speaker 1>want to remove as many easily identifiable traits from this

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<v Speaker 1>game as possible to make it all about the questions

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<v Speaker 1>and the answers. Now, Touring said, what if we were

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<v Speaker 1>to take the same basic premise, but instead of having

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<v Speaker 1>two human interviewees, replace one of those humans with a machine. Now,

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<v Speaker 1>if that machine can convince the interrogator that the machine

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<v Speaker 1>itself is a human being, it would be a pretty

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<v Speaker 1>phenomenal achievement. Or you know, just generally, if the interrogator

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<v Speaker 1>wasn't sure which of the two interrogate ease, right, which

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<v Speaker 1>one is the human, which one is the machine? Or

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<v Speaker 1>even if there could be a case where you don't know.

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<v Speaker 1>It may be that you have two humans that you're interrogating,

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<v Speaker 1>and it may be one of those things where you

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<v Speaker 1>have to you know, if you don't know for a

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<v Speaker 1>fact that one of them the machine, that makes it

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<v Speaker 1>even hard, right, at least assuming that the computer program

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<v Speaker 1>is sophisticated enough. Now, Touring was saying that we don't

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<v Speaker 1>have any machines right now that can do this, but

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<v Speaker 1>I envision a time when computers will be able to

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<v Speaker 1>do such a thing where if you were to interrogate

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<v Speaker 1>a computer, you would get back responses that would be uh,

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<v Speaker 1>convincing enough for it to make it difficult to determine

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<v Speaker 1>if it were man or machine. And so he said

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<v Speaker 1>that he predicted in fifty years time, which would be

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<v Speaker 1>the year two thousand, that computers and software be sophisticate

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<v Speaker 1>enough that interrogators would only be able to guess correctly

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<v Speaker 1>seventy of the time, meaning they would be fooled by

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<v Speaker 1>the computer of the time. Right, So, uh, this was

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<v Speaker 1>just kind of a thing he was coming up with,

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<v Speaker 1>like an idea, a prediction not necessarily a test, although

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<v Speaker 1>very much like Moore's observation became Moore's law, this became

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<v Speaker 1>what is known as the touring test. People talk about

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<v Speaker 1>a touring test as a machine capable of fooling people

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<v Speaker 1>into thinking it's another person at least thirty of the

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<v Speaker 1>time after five minutes of conversation. Very good point. Yes,

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<v Speaker 1>it needs to be five minutes of conversation. If you

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<v Speaker 1>are just getting maybe two or three responses, that might

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<v Speaker 1>not be enough for you to be able to draw

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<v Speaker 1>a conclusion that you feel good about. If after five

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<v Speaker 1>minutes you still are not entirely, entirely certain, then that

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<v Speaker 1>might say that this machine, in fact has passed the

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<v Speaker 1>touring test. And this has been extrapolated to mean something

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<v Speaker 1>about machine intelligence because Turing himself tied the idea of

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<v Speaker 1>of how we perceive a machines intelligence directly to artificial

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<v Speaker 1>intelligence and and and even how we perceive human intelligence.

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<v Speaker 1>Because here's Touring's idea is a little cheeky, and I

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<v Speaker 1>love the fact that'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 they seem to be able to take

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<v Speaker 1>an information, respond to it, make decisions. And based on

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<v Speaker 1>the fact that we ourselves also do that thing, we

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<v Speaker 1>go ahead and say, all right, well, they clearly have

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<v Speaker 1>the same features that I have, which includes intelligence. Uh. Now,

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<v Speaker 1>he says, why would we not extend that same courtesy

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<v Speaker 1>to a machine if it also appeared to display those

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<v Speaker 1>same uh features? He says, doesn't matter if the computer

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<v Speaker 1>is quote unquote thinking. If it's it can fool you. Yeah,

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<v Speaker 1>if it's able to to simulate it well enough, you

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<v Speaker 1>might as well say it's intelligent, because stimulate is probably

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<v Speaker 1>a kinder phrase for that than fool. Yeah. Yeah, well

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<v Speaker 1>I know it's it is fooling essentially, I mean, because

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<v Speaker 1>ultimately you're talking about a computer programmer, who's making this happen?

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<v Speaker 1>So nowadays we think of this as the Turing test.

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<v Speaker 1>Can a machine of the time are more fool someone

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<v Speaker 1>after 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 yeah, this

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<v Speaker 1>is non trivial. I mean it sounds almost simple. Yeah,

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<v Speaker 1>the concept is simple, the execution incredibly difficult. Because here's

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<v Speaker 1>the thing, human language varied. We have unstructured, unpredictable ways

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<v Speaker 1>to say things like if if I were to tell

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<v Speaker 1>you that it's a hundred degrees outside and it is

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<v Speaker 1>humid like the humidities at and you go out there,

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<v Speaker 1>then I'm sure all of our listeners would have slightly

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<v Speaker 1>different ways to express their thoughts on the conditions out side.

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<v Speaker 1>Some of them would probably contain colorful metaphors, probably mine

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<v Speaker 1>very likely when it contain colorful metaphors, particularly if I

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<v Speaker 1>had to be outside for any length of time. But

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<v Speaker 1>that's the point. We would all have different ways of

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<v Speaker 1>saying this. So how do you make a computer program

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<v Speaker 1>able to interpret all the myriad of ways we can

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<v Speaker 1>all express the same thought, let alone any thought. Right,

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<v Speaker 1>this is what's referred to as natural language. Recognition, and

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<v Speaker 1>it's a really huge problem in artificial intelligence and and

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<v Speaker 1>and a lot of other speech related computer programming. Exactly. Yeah,

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<v Speaker 1>this is where a computer program has to be able

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<v Speaker 1>to parse the language so it recognizes things like this

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<v Speaker 1>word is a noun, this word is a verb, this

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<v Speaker 1>this word alters this other word. Uh. And not only

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<v Speaker 1>does it need to be able to recognize it, it it

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<v Speaker 1>needs to be able to respond in kind. Right, So

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<v Speaker 1>if you 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

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<v Speaker 1>away absolutely. If you've ever been playing a video game

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<v Speaker 1>and all of the NPCs say the same thing over

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<v Speaker 1>and over and over again. Yeah, if if all the

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<v Speaker 1>chat bot says is hey listen, then you're clearly playing

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<v Speaker 1>Zelda and you're not actually having a decent conversation. That

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<v Speaker 1>being said, there is someone I know who plays a

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<v Speaker 1>ferry at the Georgia Renaissance Festival, and hey listen is

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<v Speaker 1>heavily represented in a repertoire. 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 Vassilov, 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>the not all of them still live there. But starting

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<v Speaker 1>in 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 thirteen year old boy from Odessa

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<v Speaker 1>in the Ukraine. Yeah, and that meant that they had

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<v Speaker 1>specific parameters that they could work within. It automatically helped

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<v Speaker 1>reduce some of that unpredictability and that lack of restriction

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<v Speaker 1>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 in a lot of previous chat bots have have

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<v Speaker 1>had similar, yes, similar kind of approaches. Yeah, because like

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<v Speaker 1>we said, if you're to take a quote unquote pure

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<v Speaker 1>approach to this, it's really really challenging. So yeah, by

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<v Speaker 1>by limiting this, the judges have an idea of well,

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<v Speaker 1>this this could be a thirteen year old boy or

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<v Speaker 1>it could be a computer program. It means that the

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<v Speaker 1>computer program doesn't have to be as sophisticated as one

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<v Speaker 1>that would be completely fluent and have you know, an

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<v Speaker 1>adult's experiences, uh and ability to communicate. So that was

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<v Speaker 1>step one. And uh. Eugene Goosman took part in the

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<v Speaker 1>competition UH that had five total chatbots. It was it

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<v Speaker 1>was one of five that took place on the sixtieth

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<v Speaker 1>anniversary of Touring's death, and the program managed to full

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<v Speaker 1>thirty three percent of the judges into thinking it was

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<v Speaker 1>actually a person. UH. And it had there were thirty judges.

0:13:03.120 --> 0:13:07.120
<v Speaker 1>From what I understand. So that was where you got

0:13:07.160 --> 0:13:10.320
<v Speaker 1>all the headlines of chat bought. There are computer beats

0:13:10.360 --> 0:13:14.840
<v Speaker 1>touring tests, which already is not accurate. There were some

0:13:15.040 --> 0:13:18.800
<v Speaker 1>slight um hiccups in a little bit of the news

0:13:18.840 --> 0:13:22.319
<v Speaker 1>reporting that We'll get into that part of the story later,

0:13:22.880 --> 0:13:25.360
<v Speaker 1>but you know, the key takeaways I think here are

0:13:25.440 --> 0:13:28.000
<v Speaker 1>that this was a this was a competition that was

0:13:28.040 --> 0:13:33.959
<v Speaker 1>celebrating touring awesome um and that there were thirty judges,

0:13:34.400 --> 0:13:38.160
<v Speaker 1>some of whom were celebrities, yes, including an actor who

0:13:38.280 --> 0:13:41.360
<v Speaker 1>had appeared on Red Dwarf right. Yes. And then a

0:13:41.360 --> 0:13:44.360
<v Speaker 1>couple of years before that, because because you said they

0:13:44.360 --> 0:13:46.559
<v Speaker 1>started working on this on two th two thousand one,

0:13:46.640 --> 0:13:49.719
<v Speaker 1>this was not the first time that Gustman had entered competition.

0:13:50.400 --> 0:13:55.240
<v Speaker 1>Two years previously, that same software had convinced twenty of

0:13:55.320 --> 0:13:58.840
<v Speaker 1>judges at a similar competition that was held at Bletchley Park. Now,

0:13:58.920 --> 0:14:02.640
<v Speaker 1>but Bletchley Park's where touring helped crack the Enigma machine,

0:14:03.440 --> 0:14:07.080
<v Speaker 1>the the encoding device that the German military was using

0:14:07.160 --> 0:14:10.600
<v Speaker 1>during World War Two. So this was a big celebration.

0:14:10.600 --> 0:14:14.120
<v Speaker 1>It was at the centennial celebrating his birth, and it

0:14:14.440 --> 0:14:20.440
<v Speaker 1>ended up falling just short of passing the Turing Test. Uh.

0:14:20.520 --> 0:14:24.520
<v Speaker 1>The organizer of the the more recent event, the one

0:14:24.560 --> 0:14:28.000
<v Speaker 1>in which Goostman ran away with quote unquote beating the

0:14:28.000 --> 0:14:31.960
<v Speaker 1>Turing test. Uh. That organizer was Kevin Warwick. That name

0:14:32.000 --> 0:14:34.080
<v Speaker 1>may sound familiar to some of our listeners if you've

0:14:34.120 --> 0:14:37.480
<v Speaker 1>ever heard us talk about cyborgs. He's the guy who

0:14:37.680 --> 0:14:41.560
<v Speaker 1>had an r f I D chip surgically implanted into him.

0:14:42.000 --> 0:14:45.000
<v Speaker 1>His wife also did at one point. Yes, they could

0:14:45.000 --> 0:14:49.200
<v Speaker 1>communicate with each other through them. Some unflattering news media

0:14:49.360 --> 0:14:53.040
<v Speaker 1>sometimes refers to him as Captain Cyborg. Yeah. There there

0:14:53.080 --> 0:14:56.280
<v Speaker 1>are some critics who say that he uh, he courts

0:14:56.440 --> 0:15:02.000
<v Speaker 1>publicity in a manner that is um unbeco umming of

0:15:02.000 --> 0:15:05.360
<v Speaker 1>of of a scientist, yes, really of anybody. Yes, yes,

0:15:05.960 --> 0:15:08.800
<v Speaker 1>uh those are the critics who say that. By the way,

0:15:08.960 --> 0:15:11.560
<v Speaker 1>I just want to make that clear. At any rate,

0:15:11.720 --> 0:15:13.680
<v Speaker 1>He said that this was the first time a chat

0:15:13.680 --> 0:15:16.320
<v Speaker 1>bot had passed the Turing test at an event where

0:15:16.360 --> 0:15:19.280
<v Speaker 1>the conversation was open ended, meaning that they had not

0:15:19.560 --> 0:15:25.240
<v Speaker 1>previously uh decided upon a specific topic or line of questioning.

0:15:25.640 --> 0:15:28.400
<v Speaker 1>That the judges were allowed to say whatever they wanted

0:15:28.440 --> 0:15:30.960
<v Speaker 1>to the chat bot and response, which obviously makes it

0:15:31.000 --> 0:15:33.640
<v Speaker 1>harder because you have to have a much wider breadth

0:15:33.840 --> 0:15:37.880
<v Speaker 1>of potential responses. Yeah. Yeah, because again, if you were

0:15:37.920 --> 0:15:40.160
<v Speaker 1>to say, all right, this chat bot is just going

0:15:40.200 --> 0:15:43.920
<v Speaker 1>to talk about, um, I don't know, sporting events from

0:15:44.000 --> 0:15:48.560
<v Speaker 1>last year, Well, then you can prepare pretty well for that. Yeah, exactly.

0:15:48.600 --> 0:15:50.160
<v Speaker 1>So it's one of those again, it's one of those

0:15:50.160 --> 0:15:54.720
<v Speaker 1>things where the unrestricted nature adds in a degree of difficulty.

0:15:54.800 --> 0:15:57.440
<v Speaker 1>So why would you need to make the qualification that

0:15:57.520 --> 0:15:59.320
<v Speaker 1>this is an open ended approach and this is the

0:15:59.320 --> 0:16:03.840
<v Speaker 1>first chat to manage it. That would be because despite

0:16:03.880 --> 0:16:06.960
<v Speaker 1>what you may have heard, Eugene Goosband was not the

0:16:07.000 --> 0:16:09.960
<v Speaker 1>first program to beat the Turing test, not by a

0:16:10.000 --> 0:16:14.720
<v Speaker 1>long shot. So work on these sort of chatbots, these

0:16:14.800 --> 0:16:19.520
<v Speaker 1>kind of artificial conversationalists. That's real recent, right, I mean

0:16:19.600 --> 0:16:21.880
<v Speaker 1>they just started doing that like what like like maybe

0:16:21.880 --> 0:16:23.840
<v Speaker 1>three or four years ago or two thousand, one of

0:16:23.880 --> 0:16:26.560
<v Speaker 1>the earliest, I mean that's when they started with Goosman. Yeah. No,

0:16:26.640 --> 0:16:31.320
<v Speaker 1>in the nineteen sixties and seventies, say, back in the

0:16:31.440 --> 0:16:35.160
<v Speaker 1>mid nineteen sixties there was Eliza, which was written by

0:16:35.360 --> 0:16:38.800
<v Speaker 1>Joseph Weisenbaum. If you're pronouncing it in the correct German,

0:16:39.000 --> 0:16:42.160
<v Speaker 1>that's correct. Excellent, I'm finally learning. I'm sure, I'm sure

0:16:42.240 --> 0:16:45.920
<v Speaker 1>he pronounces it Wisenbaum, but yeah, but no, it would

0:16:45.920 --> 0:16:49.840
<v Speaker 1>be Weisenbaum at any rate. Um. This this was a

0:16:49.880 --> 0:16:53.400
<v Speaker 1>program UM that would respond to human conversation and what

0:16:53.880 --> 0:16:57.720
<v Speaker 1>ideally would be a relevant way. Yes, it was obviously

0:16:57.760 --> 0:17:01.040
<v Speaker 1>an early attempt. It was not meant to be a

0:17:01.920 --> 0:17:04.320
<v Speaker 1>program that takes on the Turing test. It was really

0:17:04.359 --> 0:17:06.439
<v Speaker 1>a thought again, kind of like a thought experiment, the

0:17:06.440 --> 0:17:09.320
<v Speaker 1>idea of what does it take to create a piece

0:17:09.320 --> 0:17:12.680
<v Speaker 1>of software that can react to questions and make it

0:17:12.840 --> 0:17:15.080
<v Speaker 1>make sense. At that point, it was more a can

0:17:15.160 --> 0:17:17.480
<v Speaker 1>we do this? Then let's do this for real? Yeah,

0:17:17.520 --> 0:17:20.879
<v Speaker 1>and these are the sort of foundations that you have

0:17:20.920 --> 0:17:23.280
<v Speaker 1>to lay in order for other things like the Eugene

0:17:23.320 --> 0:17:28.840
<v Speaker 1>Goostman program to be uh successful. So he created a

0:17:28.920 --> 0:17:33.000
<v Speaker 1>language analyzer. Now this specifically would look at words that

0:17:33.280 --> 0:17:36.000
<v Speaker 1>users would put in and then compare them against a

0:17:36.080 --> 0:17:38.720
<v Speaker 1>database of words that were stored in the computer's memory.

0:17:39.240 --> 0:17:42.840
<v Speaker 1>And then also created scripts. Now, in this case, the

0:17:42.880 --> 0:17:45.119
<v Speaker 1>scripts were sets of rules. They're kind of like, you know,

0:17:45.160 --> 0:17:48.200
<v Speaker 1>like a protocol or an algorithm in a way. These

0:17:48.280 --> 0:17:52.640
<v Speaker 1>rules dictated how Eliza would respond to messages in order

0:17:52.680 --> 0:17:56.160
<v Speaker 1>to cut down on that huge, massive number of variables

0:17:56.160 --> 0:17:59.719
<v Speaker 1>we were talking about, the whole unrestricted, unpredictable thing, and

0:17:59.800 --> 0:18:03.679
<v Speaker 1>so they would have different uh kind of like like overlays.

0:18:03.720 --> 0:18:05.520
<v Speaker 1>Think of him as an overlay that would kind of

0:18:05.840 --> 0:18:09.359
<v Speaker 1>guide Aliza's responses. And the most well known one was

0:18:09.400 --> 0:18:13.040
<v Speaker 1>called doctor, which put Eliza in the role of a

0:18:13.200 --> 0:18:18.480
<v Speaker 1>Rogerian psychiatrist. Uh. This is the person who responds to

0:18:18.480 --> 0:18:20.600
<v Speaker 1>everything with a question. Al Right. It's that it's that

0:18:20.800 --> 0:18:25.080
<v Speaker 1>passive interview style where where you know, you repeat back.

0:18:25.640 --> 0:18:27.560
<v Speaker 1>You know, if if if I go, oh, man, like

0:18:27.600 --> 0:18:30.440
<v Speaker 1>I'm I'm I'm really sad about my cat, Oh, tell

0:18:30.920 --> 0:18:32.640
<v Speaker 1>what is it about your cat that makes you sad?

0:18:33.320 --> 0:18:35.159
<v Speaker 1>And then you can say things like you know, And

0:18:35.359 --> 0:18:38.919
<v Speaker 1>that's one of those things where as a conversation starts

0:18:38.960 --> 0:18:42.560
<v Speaker 1>to wind down, you then have another line of questions,

0:18:42.600 --> 0:18:45.280
<v Speaker 1>So tell me more about your mother, like that the

0:18:45.560 --> 0:18:47.960
<v Speaker 1>whole tell me about your mother thing. That's really coming

0:18:47.960 --> 0:18:50.160
<v Speaker 1>back to this kind of model of psychiatrists. But yeah,

0:18:50.200 --> 0:18:52.600
<v Speaker 1>if you've ever heard the joke about them responding to

0:18:52.640 --> 0:18:56.040
<v Speaker 1>anything with another question, just just taking the last word

0:18:56.080 --> 0:18:58.600
<v Speaker 1>and turning it into a question, what am I paying

0:18:58.600 --> 0:19:01.800
<v Speaker 1>you for Why do you think your page for that

0:19:01.880 --> 0:19:05.840
<v Speaker 1>kind of thing? Uh So that's what That's how Eliza responded,

0:19:05.880 --> 0:19:10.040
<v Speaker 1>And in fact, you can find examples of the Eliza

0:19:10.400 --> 0:19:14.159
<v Speaker 1>program script transcripts and even even the actual there's there.

0:19:14.160 --> 0:19:17.399
<v Speaker 1>There are ports, you could say, or people have essentially

0:19:17.440 --> 0:19:20.280
<v Speaker 1>created their own version of Eliza just using the original

0:19:20.320 --> 0:19:22.800
<v Speaker 1>Liza as a guide. You can find tons of them

0:19:22.800 --> 0:19:25.000
<v Speaker 1>on the web, and you can attempt to have a

0:19:25.040 --> 0:19:29.200
<v Speaker 1>conversation with them. It's not terribly compelling, but it's it's

0:19:29.280 --> 0:19:33.240
<v Speaker 1>kind of fun. Usually within maybe four or five exchanges,

0:19:33.240 --> 0:19:35.120
<v Speaker 1>you've already run into something where you're like, well, this

0:19:35.160 --> 0:19:38.120
<v Speaker 1>can't be a person, or if it's a person, it's

0:19:38.119 --> 0:19:41.040
<v Speaker 1>the weirdest person I've ever conversed with. But but again,

0:19:41.080 --> 0:19:44.600
<v Speaker 1>it wasn't really an earnest attempt to to create something

0:19:44.640 --> 0:19:48.159
<v Speaker 1>that would pass the quote unquote tearing tests, which I

0:19:48.200 --> 0:19:49.800
<v Speaker 1>don't think was being referred to as such at that

0:19:49.840 --> 0:19:52.240
<v Speaker 1>point yet. Yeah, it was kind of people knew about

0:19:52.280 --> 0:19:55.520
<v Speaker 1>tourings prediction, but it wasn't so much called a turing test.

0:19:56.000 --> 0:19:59.080
<v Speaker 1>Another chat bought that premiered in the early nineties seventies

0:19:59.119 --> 0:20:02.880
<v Speaker 1>went even further and actually was an attempt to try

0:20:03.000 --> 0:20:06.000
<v Speaker 1>and pass the Turing test in a very specific approach,

0:20:06.080 --> 0:20:08.560
<v Speaker 1>kind of like you know, Eugene Goostman, is a very

0:20:08.560 --> 0:20:12.200
<v Speaker 1>specific approach to narrow down that those parameters. In this case,

0:20:12.280 --> 0:20:15.639
<v Speaker 1>this one was called Perry p A R R Y

0:20:15.920 --> 0:20:19.520
<v Speaker 1>A Right, and Kenneth Colby created it too to emulate

0:20:19.800 --> 0:20:24.080
<v Speaker 1>a patient who has paranoid schizophrenia. Yeah, someone who has

0:20:24.200 --> 0:20:28.360
<v Speaker 1>you know, sort of a persecution complex. Uh. They imagined

0:20:28.440 --> 0:20:32.639
<v Speaker 1>that's that there are people or other entities that are

0:20:32.680 --> 0:20:36.000
<v Speaker 1>out to get them. And in this uh specific case,

0:20:36.320 --> 0:20:40.080
<v Speaker 1>he he kinda he kind of really embraced this approach.

0:20:40.600 --> 0:20:43.840
<v Speaker 1>It reminds me of people who create a like a

0:20:43.960 --> 0:20:46.080
<v Speaker 1>Dungeons and Dragon's character, but then give their character an

0:20:46.200 --> 0:20:49.960
<v Speaker 1>entire backstory. Yeah. Yeah, yeah, this this Perry persona was

0:20:50.040 --> 0:20:52.040
<v Speaker 1>an entire persona. It was a twenty eight year old

0:20:52.080 --> 0:20:54.400
<v Speaker 1>man with a job as a post office clerk who

0:20:54.440 --> 0:20:57.240
<v Speaker 1>was single, had no brothers and sisters, and rarely saw

0:20:57.359 --> 0:21:00.119
<v Speaker 1>his parents. He had specific hobbies. He liked to of

0:21:00.160 --> 0:21:03.240
<v Speaker 1>the movies and horse racing. Yeah, he liked to bet

0:21:03.240 --> 0:21:06.720
<v Speaker 1>on the horses and placed a bet with bookies in

0:21:06.720 --> 0:21:11.240
<v Speaker 1>the past. Right, and that he realized later bookies have

0:21:11.359 --> 0:21:15.639
<v Speaker 1>an association with the criminal underworld, and that therefore the

0:21:15.800 --> 0:21:19.240
<v Speaker 1>mafia knew about him and we're out to get him. Now. Now,

0:21:19.280 --> 0:21:21.479
<v Speaker 1>all of that might sound very ridiculous to you if

0:21:21.520 --> 0:21:24.400
<v Speaker 1>you never had any kind of interaction with someone who

0:21:24.440 --> 0:21:27.560
<v Speaker 1>suffers from paranoid schizophrenia, that can seem like, well, that

0:21:27.640 --> 0:21:31.600
<v Speaker 1>seems cartoonish. But no, this, this kind of thinking is

0:21:31.680 --> 0:21:34.719
<v Speaker 1>not uncommon, you know, whether it's whether it's a criminal

0:21:34.800 --> 0:21:40.760
<v Speaker 1>organization or the government or some other even unnamed entity. Oh. Absolutely, Uh,

0:21:40.880 --> 0:21:44.000
<v Speaker 1>it's it's very much realistic in terms of that kind

0:21:44.000 --> 0:21:46.560
<v Speaker 1>of diagnosis. And and if I was speaking about it

0:21:46.600 --> 0:21:48.320
<v Speaker 1>with humor in my voice a moment ago, it's it's

0:21:48.320 --> 0:21:51.800
<v Speaker 1>only because I am absolutely tickled that the programmers of

0:21:52.000 --> 0:21:56.200
<v Speaker 1>this of this program built it, built it in. Yeah,

0:21:56.880 --> 0:21:59.800
<v Speaker 1>it's it's actually pretty entertaining that they went so far

0:21:59.840 --> 0:22:03.199
<v Speaker 1>as to make this whole uh, this whole backstory to explain,

0:22:03.240 --> 0:22:06.280
<v Speaker 1>because that's what gives it the believability, right, and then

0:22:06.440 --> 0:22:09.359
<v Speaker 1>they ended up testing it in conversation with a human.

0:22:09.359 --> 0:22:13.080
<v Speaker 1>Perry would gradually start to introduce his thoughts quote unquote

0:22:13.200 --> 0:22:17.560
<v Speaker 1>thoughts about being persecuted, and would respond sensitively to anything

0:22:17.600 --> 0:22:21.480
<v Speaker 1>said about his appearance, family, or religious beliefs. I've actually

0:22:21.520 --> 0:22:24.760
<v Speaker 1>seen lots of transcripts of conversations with Perry, and sure enough,

0:22:25.000 --> 0:22:27.360
<v Speaker 1>it's one of those things where you know, you might

0:22:27.720 --> 0:22:30.080
<v Speaker 1>have a few exchanges and then Perry ends up saying

0:22:30.240 --> 0:22:34.000
<v Speaker 1>something that seems really odd, but not so odd as

0:22:34.040 --> 0:22:37.120
<v Speaker 1>to seem artificial. It just seems like it's a non sequitur,

0:22:37.720 --> 0:22:39.760
<v Speaker 1>you know, something like, well, that's what they want you

0:22:39.800 --> 0:22:41.240
<v Speaker 1>to think. And if you were to say, who are

0:22:41.280 --> 0:22:44.280
<v Speaker 1>they the mafia? Who did you think I was talking about?

0:22:45.000 --> 0:22:48.199
<v Speaker 1>Like the mafia after you? Of course they're after me.

0:22:48.720 --> 0:22:50.320
<v Speaker 1>They know who I am. That kind of stuff, and

0:22:50.560 --> 0:22:53.439
<v Speaker 1>it's disturbing, like it's you know, when you know what

0:22:53.520 --> 0:22:55.680
<v Speaker 1>it is, it's kind of amusing, but like if you're

0:22:55.680 --> 0:23:00.320
<v Speaker 1>in the middle of a conversation, oh, this poor person. Yeah.

0:23:00.680 --> 0:23:03.920
<v Speaker 1>And so in order to test it, uh Kolby did

0:23:03.920 --> 0:23:06.400
<v Speaker 1>a couple of different things. He did one test where

0:23:06.440 --> 0:23:11.240
<v Speaker 1>eight psychiatrists interviewed both Perry and a human patient via teletypewriter.

0:23:11.359 --> 0:23:15.919
<v Speaker 1>So in both cases, the the the psychiatrists could not

0:23:16.080 --> 0:23:18.000
<v Speaker 1>see who they were interviewing. This is going back to

0:23:18.040 --> 0:23:20.720
<v Speaker 1>the kind of the original touring test. Idea, or at

0:23:20.760 --> 0:23:25.119
<v Speaker 1>least Touring's proposed experiment. And in this case, only two

0:23:25.240 --> 0:23:27.240
<v Speaker 1>of the eight were able to identify that one of

0:23:27.240 --> 0:23:29.680
<v Speaker 1>the interviewees was human and the other was a machine.

0:23:30.200 --> 0:23:32.439
<v Speaker 1>In a second test, Colby presented a group of a

0:23:32.520 --> 0:23:40.159
<v Speaker 1>hundreds psychiatrists, most a psychics, transcripts of interviews between Perry. Yeah,

0:23:40.200 --> 0:23:44.920
<v Speaker 1>he had, he had pairs of exactly food, I foresee. No.

0:23:45.119 --> 0:23:49.600
<v Speaker 1>But they gave these psychiatrists transcripts of interviews between an

0:23:49.640 --> 0:23:52.359
<v Speaker 1>interviewer and Perry, and an interviewer and a human patient,

0:23:53.119 --> 0:23:56.439
<v Speaker 1>and forty out of the one responded. I don't know

0:23:56.480 --> 0:23:58.879
<v Speaker 1>if the other sixty just never got it or if

0:23:58.920 --> 0:24:02.239
<v Speaker 1>they didn't take The response rates are variable, right, so

0:24:02.359 --> 0:24:05.680
<v Speaker 1>I'll the forty who responded, nineteen of them guessed incorrectly.

0:24:06.040 --> 0:24:10.159
<v Speaker 1>So that's almost a fifty percent, you know, getting you know,

0:24:10.320 --> 0:24:15.160
<v Speaker 1>right up there with a pretty impressive amount. Now, again,

0:24:16.280 --> 0:24:19.359
<v Speaker 1>we have to look at the fact that Perry is

0:24:19.400 --> 0:24:24.080
<v Speaker 1>operating under a very restricted set of rules. We're talking

0:24:24.119 --> 0:24:28.320
<v Speaker 1>about paranoid schizophrenic, someone who we would assume would occasionally

0:24:28.760 --> 0:24:33.560
<v Speaker 1>have a non normative answers exactly to conversational pieces. And

0:24:33.560 --> 0:24:36.120
<v Speaker 1>and again it's it's a limited time that you're having

0:24:36.160 --> 0:24:38.920
<v Speaker 1>with this person or this entity in this case, this

0:24:38.920 --> 0:24:45.840
<v Speaker 1>this program, and uh, because the psychiatrists had a specific

0:24:45.920 --> 0:24:48.480
<v Speaker 1>expectation of the type of interactions they were going to

0:24:48.520 --> 0:24:56.200
<v Speaker 1>see that could have affected their their answer right. So ideally,

0:24:56.640 --> 0:25:00.359
<v Speaker 1>in the perfect situation, you would have this in review

0:25:00.440 --> 0:25:03.879
<v Speaker 1>happening where you have no expectation as to what the

0:25:03.920 --> 0:25:07.719
<v Speaker 1>answers should be. In other words, you don't know ahead

0:25:07.720 --> 0:25:12.320
<v Speaker 1>of time that the interviewee is having any kind of

0:25:12.320 --> 0:25:15.199
<v Speaker 1>other any kind of restrictions upon that person, so that

0:25:15.280 --> 0:25:18.560
<v Speaker 1>you would be interviewing anyone like any average person. But

0:25:18.640 --> 0:25:21.040
<v Speaker 1>that's obviously not what we're talking about here, nor was

0:25:21.080 --> 0:25:25.720
<v Speaker 1>it the one for Eugene Goosband. So I've also seen

0:25:25.800 --> 0:25:30.119
<v Speaker 1>by the way transcripts of people who set up Eliza

0:25:30.240 --> 0:25:32.720
<v Speaker 1>and Perry to talk to each other. So you have

0:25:32.760 --> 0:25:37.640
<v Speaker 1>Eliza acting as the Rogerian psychiatrist and Perry the paranoid schizophrenic,

0:25:38.000 --> 0:25:42.520
<v Speaker 1>having bizarre conversations, and they usually don't last very long

0:25:42.560 --> 0:25:47.159
<v Speaker 1>because Perry gets upset, And obviously by gets upset, I

0:25:47.200 --> 0:25:49.399
<v Speaker 1>just mean that Perry ends up essentially shutting down the

0:25:49.440 --> 0:25:53.280
<v Speaker 1>conversation because Eliza just wants to ask questions, and Perry

0:25:53.320 --> 0:25:56.439
<v Speaker 1>gets suspicious of people who are asking questions, and by

0:25:56.560 --> 0:25:59.479
<v Speaker 1>again get suspicious, I'm saying following specific rules that make

0:25:59.520 --> 0:26:02.800
<v Speaker 1>it feel like this computer programs getting suspicious, but they

0:26:02.800 --> 0:26:06.000
<v Speaker 1>are entertaining. If you ever do a search online, just

0:26:06.080 --> 0:26:09.560
<v Speaker 1>look for Eliza Perry transcripts. There. There are a few

0:26:09.600 --> 0:26:12.560
<v Speaker 1>of them, and they're all pretty entertaining. But so since

0:26:12.600 --> 0:26:15.440
<v Speaker 1>since that time, I mean obviously, lots and lots of

0:26:15.520 --> 0:26:18.719
<v Speaker 1>chatbots have been created for multiple reasons. Oh yeah, well,

0:26:18.760 --> 0:26:20.720
<v Speaker 1>you know, some of them are trying to test the

0:26:20.760 --> 0:26:23.919
<v Speaker 1>Turing test, and others are trying to fool you into

0:26:24.320 --> 0:26:27.240
<v Speaker 1>giving out your credit card information or planing on a

0:26:27.320 --> 0:26:31.800
<v Speaker 1>link that has malicious uh links to malicious software. Yeah.

0:26:32.359 --> 0:26:37.080
<v Speaker 1>Anyone who's been on any kind of chat program, specifically

0:26:37.119 --> 0:26:40.760
<v Speaker 1>like AIM has probably encountered this at least once or twice,

0:26:40.800 --> 0:26:45.680
<v Speaker 1>where they're they're getting an unsolicited message from someone or

0:26:45.720 --> 0:26:48.280
<v Speaker 1>something or something. Yeah, and if you type a couple

0:26:48.280 --> 0:26:51.280
<v Speaker 1>of times, you realize, oh, this is not actually this

0:26:51.320 --> 0:26:54.080
<v Speaker 1>is an attempt for to either get information from me

0:26:54.200 --> 0:26:56.800
<v Speaker 1>or have me click on a link. Yeah, that's a

0:26:57.200 --> 0:27:01.760
<v Speaker 1>that's the thing. But there are some example of I

0:27:01.800 --> 0:27:05.160
<v Speaker 1>guess saying legitimate is weird. But there are some examples

0:27:05.200 --> 0:27:09.600
<v Speaker 1>of other more and more scholarly attempts. Yeah, like a

0:27:09.600 --> 0:27:15.960
<v Speaker 1>PC therapist. Uh. That one was by Joseph Weintraub, and

0:27:16.119 --> 0:27:19.280
<v Speaker 1>it fooled of its judges into thinking that it was human.

0:27:20.760 --> 0:27:23.639
<v Speaker 1>Of ten judges, of course, so if I'm doing my

0:27:23.680 --> 0:27:26.760
<v Speaker 1>math correctly, that's five that I believe you are. Unless

0:27:26.800 --> 0:27:30.439
<v Speaker 1>we're talking about quantum judges. Um, these judges were both

0:27:30.560 --> 0:27:33.719
<v Speaker 1>right and wrong at the same time. And um, and

0:27:33.800 --> 0:27:36.600
<v Speaker 1>it was it was a whimsical program. I guess you

0:27:36.600 --> 0:27:39.400
<v Speaker 1>could say, yeah, it had come some I think it's

0:27:39.400 --> 0:27:42.760
<v Speaker 1>fair to say its answers could be pretty smart ass. Also,

0:27:43.000 --> 0:27:45.840
<v Speaker 1>I read some of these transcripts and it actually surprised

0:27:45.880 --> 0:27:48.600
<v Speaker 1>me that enough judges thought that it was a person.

0:27:49.080 --> 0:27:51.760
<v Speaker 1>Maybe they thought it was a person who was purposefully

0:27:51.880 --> 0:27:55.040
<v Speaker 1>attempting to fool them into thinking it was a computer. Uh,

0:27:55.280 --> 0:27:57.320
<v Speaker 1>you know, because it would say things like I compute,

0:27:57.359 --> 0:27:59.919
<v Speaker 1>therefore I am that kind of stuff where it was

0:28:00.000 --> 0:28:03.760
<v Speaker 1>specifically Yeah, so you're looking at this stuff and you're thinking,

0:28:03.840 --> 0:28:05.400
<v Speaker 1>all right, well, maybe this is kind of going back

0:28:05.440 --> 0:28:09.240
<v Speaker 1>to that original touring test party game where the the

0:28:09.280 --> 0:28:12.119
<v Speaker 1>effort is for a person like the person who's being

0:28:12.119 --> 0:28:15.240
<v Speaker 1>interviewed is trying to throw everybody off, And that's perfectly

0:28:15.280 --> 0:28:18.240
<v Speaker 1>within the rules unless you stay upfront. No, just be

0:28:18.320 --> 0:28:20.920
<v Speaker 1>honest in your in your answers. There's nothing in here,

0:28:20.960 --> 0:28:23.800
<v Speaker 1>by the way that says that the interviewee has to

0:28:23.840 --> 0:28:26.800
<v Speaker 1>tell the truth necessarily unless you just state that as

0:28:26.800 --> 0:28:29.480
<v Speaker 1>a parameter at the beginning. So in other words, you

0:28:29.520 --> 0:28:31.679
<v Speaker 1>could you could be like, I'm totally the computer and

0:28:31.720 --> 0:28:34.639
<v Speaker 1>you're the human being interviewed. Uh. I don't know if

0:28:34.640 --> 0:28:37.440
<v Speaker 1>that's a fair way of saying that the device won

0:28:37.560 --> 0:28:40.480
<v Speaker 1>or lost, but it is a possibility. Uh. Then we

0:28:40.560 --> 0:28:42.160
<v Speaker 1>have a two thousand eleven. Now, this one is a

0:28:42.200 --> 0:28:46.640
<v Speaker 1>really pretty impressive one. And this was clever Butt, which

0:28:46.680 --> 0:28:49.800
<v Speaker 1>was made by a fellow named Rollo Carpenter, and it

0:28:49.920 --> 0:28:53.520
<v Speaker 1>fooled fifty nine point three percent of a live audience

0:28:53.560 --> 0:28:57.960
<v Speaker 1>and an event in India with more than a thousand people. Yeah,

0:28:58.000 --> 0:29:00.160
<v Speaker 1>the way this worked was that the audience watched as

0:29:00.200 --> 0:29:04.440
<v Speaker 1>interviewers interacted via text with either clever Bot or a

0:29:04.520 --> 0:29:08.120
<v Speaker 1>human in the course of a four minute interview. So

0:29:08.160 --> 0:29:11.240
<v Speaker 1>it's a little shorter than what Turing had said, but

0:29:11.280 --> 0:29:13.600
<v Speaker 1>not by not by a whole lot. In fourmants is

0:29:13.640 --> 0:29:15.800
<v Speaker 1>still a good amount of time. Sure that that is

0:29:15.840 --> 0:29:20.560
<v Speaker 1>twent less, that's true. That's true, so keep that in mind.

0:29:20.640 --> 0:29:23.320
<v Speaker 1>But but at any rate, it was you know, pretty

0:29:23.320 --> 0:29:27.760
<v Speaker 1>interesting experience. And also from why I read they misidentified,

0:29:28.640 --> 0:29:31.800
<v Speaker 1>they thought that the human was a computer sixty of

0:29:31.840 --> 0:29:36.240
<v Speaker 1>the time. Um, because they didn't necessarily just say that

0:29:36.360 --> 0:29:39.880
<v Speaker 1>it was a computer or it was clever. But so

0:29:41.000 --> 0:29:44.120
<v Speaker 1>now we see that there are a few examples of

0:29:44.240 --> 0:29:49.000
<v Speaker 1>chat bots quote unquote passing the Turing test. So what

0:29:49.040 --> 0:29:51.760
<v Speaker 1>does that mean? Does it mean that the machines are

0:29:51.760 --> 0:29:57.800
<v Speaker 1>actually thinking? Um? No, I mean, and it's not to

0:29:57.840 --> 0:29:59.880
<v Speaker 1>say that that computers don't have a certain amount of

0:30:00.200 --> 0:30:04.000
<v Speaker 1>machine intelligence, but there's absolutely a distinction between that and

0:30:04.200 --> 0:30:07.400
<v Speaker 1>what we consider to be human intelligence. That's true. The

0:30:07.440 --> 0:30:10.560
<v Speaker 1>programmers themselves have said that this doesn't mean a machine

0:30:10.600 --> 0:30:14.920
<v Speaker 1>is able to think. Uh, they're just able to interpret

0:30:15.720 --> 0:30:18.440
<v Speaker 1>commands then to follow a set of rules to make

0:30:18.480 --> 0:30:21.880
<v Speaker 1>a response, which is still pretty cool. And and it

0:30:21.920 --> 0:30:24.680
<v Speaker 1>doesn't It certainly doesn't mean that the Turing test is

0:30:25.160 --> 0:30:28.320
<v Speaker 1>worthless as an exercise. No, it is. In fact, it's

0:30:28.360 --> 0:30:33.360
<v Speaker 1>improving our ability to create programs that that can understand

0:30:34.000 --> 0:30:37.800
<v Speaker 1>or at least respond to natural language. Natural language recognition

0:30:37.800 --> 0:30:40.120
<v Speaker 1>is one of those big things where if you're really

0:30:40.160 --> 0:30:42.960
<v Speaker 1>able to crack it, then you can have some amazing

0:30:43.040 --> 0:30:45.640
<v Speaker 1>opportunities open up. And we've seen this recently with stuff

0:30:45.680 --> 0:30:49.160
<v Speaker 1>like Siri. Oh absolutely being able to speak to your

0:30:49.200 --> 0:30:52.400
<v Speaker 1>computer rather than having to I mean, even if you

0:30:52.400 --> 0:30:54.880
<v Speaker 1>could speak to your computer through a keyboard and have

0:30:54.920 --> 0:30:57.520
<v Speaker 1>it understand what you're what you're saying, I mean, like

0:30:57.840 --> 0:31:00.960
<v Speaker 1>it's it's the reason why Google spend so much time

0:31:00.960 --> 0:31:03.560
<v Speaker 1>and money, and it's search algorithms of of trying to

0:31:03.560 --> 0:31:06.640
<v Speaker 1>figure out what you really mean when you search for

0:31:06.680 --> 0:31:12.000
<v Speaker 1>a certain phrase, because traditionally, you know, before we really

0:31:12.000 --> 0:31:16.440
<v Speaker 1>got into the natural language recognition era, it meant that

0:31:16.480 --> 0:31:18.040
<v Speaker 1>in order to work with a computer, you had to

0:31:18.040 --> 0:31:20.480
<v Speaker 1>work with a computer on the computer's terms. You had

0:31:20.520 --> 0:31:22.720
<v Speaker 1>to learn the commands, you had to learn the way

0:31:22.760 --> 0:31:25.120
<v Speaker 1>to navigate a computer system in order for it to

0:31:25.120 --> 0:31:27.520
<v Speaker 1>do what you wanted it to do. Once you get

0:31:27.560 --> 0:31:31.520
<v Speaker 1>to a point where natural language recognition software is robust

0:31:31.640 --> 0:31:35.560
<v Speaker 1>enough the computer is working on your terms, you you

0:31:35.600 --> 0:31:39.920
<v Speaker 1>can put in however you're thinking, like whatever, whatever mental

0:31:40.080 --> 0:31:44.080
<v Speaker 1>exercise you've gone through to ask this computer to do something.

0:31:44.480 --> 0:31:48.160
<v Speaker 1>Whatever you do to kind of express a thought, uh

0:31:48.440 --> 0:31:51.040
<v Speaker 1>as a command to this computer. The computer can then

0:31:51.720 --> 0:31:55.160
<v Speaker 1>interpret then respond And it's not just for serving you

0:31:55.200 --> 0:31:58.400
<v Speaker 1>back whatever information you happen to be looking for. It's

0:31:58.560 --> 0:32:00.840
<v Speaker 1>I mean, I mean, we're talking about being able to

0:32:00.920 --> 0:32:04.160
<v Speaker 1>just look at a computer and say, you know, I

0:32:04.240 --> 0:32:08.200
<v Speaker 1>really want a graph that looks blue and has these

0:32:08.240 --> 0:32:11.880
<v Speaker 1>percentages in it and it is about this thing, and

0:32:11.920 --> 0:32:14.040
<v Speaker 1>it just does it. Yeah, like I want to see

0:32:14.040 --> 0:32:17.720
<v Speaker 1>what the population distribution of Atlanta is in a bar

0:32:17.880 --> 0:32:20.840
<v Speaker 1>chart or something, and then it could bring that, goes out,

0:32:20.920 --> 0:32:24.080
<v Speaker 1>finds that information, put it into a bar chart, and yeah,

0:32:24.120 --> 0:32:26.800
<v Speaker 1>that's pretty phenomenal stuff. We see other examples of machine

0:32:26.840 --> 0:32:32.480
<v Speaker 1>intelligence everywhere, things like pattern recognition, probabilistic predictions, for example, Pandora.

0:32:32.880 --> 0:32:35.560
<v Speaker 1>You know the Music Genome project. It's yeah, that's that's

0:32:35.560 --> 0:32:39.920
<v Speaker 1>pattern recognition. It's looking for elements of songs that you

0:32:39.960 --> 0:32:42.600
<v Speaker 1>say you like, and then looking for other stuff that's

0:32:42.640 --> 0:32:45.640
<v Speaker 1>not in the specific category you mentioned or the specific

0:32:45.720 --> 0:32:49.640
<v Speaker 1>examples you mentioned, and there's something else you probably will

0:32:49.680 --> 0:32:51.360
<v Speaker 1>like because you like these other things that also have

0:32:51.440 --> 0:32:54.720
<v Speaker 1>this stuff in it. Sure, Uh, you know sometimes that's

0:32:54.800 --> 0:32:57.640
<v Speaker 1>less functional than other times. It makes me think of

0:32:57.800 --> 0:33:00.880
<v Speaker 1>Patton Oswald has a great routine about Evo that does

0:33:00.920 --> 0:33:02.720
<v Speaker 1>the same sort of thing where he says, you know,

0:33:02.760 --> 0:33:05.480
<v Speaker 1>TiVo is great. I mean, I like, I love Westerns,

0:33:05.520 --> 0:33:08.400
<v Speaker 1>and I'll have it set to TiVo a Western for me,

0:33:08.440 --> 0:33:09.920
<v Speaker 1>and I come back, and then there'll be all these

0:33:09.920 --> 0:33:12.720
<v Speaker 1>other Westerns that will be suggested. I didn't even know about.

0:33:13.160 --> 0:33:16.080
<v Speaker 1>Thank you, TiVo. But then sometimes TiVo gets it wrong

0:33:16.400 --> 0:33:19.200
<v Speaker 1>and I come back and everything has got horses in it,

0:33:19.760 --> 0:33:22.080
<v Speaker 1>because Westerns have horses in it. So I've got my

0:33:22.160 --> 0:33:25.000
<v Speaker 1>little pony and cartoons with horses and unicorns and things,

0:33:25.200 --> 0:33:28.160
<v Speaker 1>and I have to say, no, TiVo, that's a bad TiVo.

0:33:28.400 --> 0:33:32.080
<v Speaker 1>But TiVo says, but you said you liked horses. Same

0:33:32.120 --> 0:33:34.920
<v Speaker 1>sort of thing. Like when you get more sophisticated than

0:33:35.160 --> 0:33:39.320
<v Speaker 1>the the computer program starts to anticipate things and makes

0:33:39.360 --> 0:33:42.920
<v Speaker 1>these probabilistic models. These these models where there there are

0:33:42.960 --> 0:33:48.280
<v Speaker 1>certain percentages associated with various responses, and it goes with

0:33:48.320 --> 0:33:51.880
<v Speaker 1>whichever one seems to be the most prevalent, assuming it

0:33:51.920 --> 0:33:54.920
<v Speaker 1>meets a threshold. If this sounds familiar to you, it's

0:33:54.920 --> 0:33:59.280
<v Speaker 1>because that's how ibms Watson worked, which is a really

0:33:59.320 --> 0:34:03.280
<v Speaker 1>good example of natural language recognition absolutely because not only

0:34:03.360 --> 0:34:06.240
<v Speaker 1>was it able to recognize natural language, it had to

0:34:06.960 --> 0:34:11.440
<v Speaker 1>interpret things like word play Jeopardy. This is the machine

0:34:11.480 --> 0:34:14.480
<v Speaker 1>that went up on Jeopardy and beat the returning champions

0:34:15.360 --> 0:34:18.520
<v Speaker 1>or former champions. Uh And you know, if you've ever

0:34:18.640 --> 0:34:21.759
<v Speaker 1>played Jeopardy or watch Jeopardy, you know that there are

0:34:21.880 --> 0:34:26.319
<v Speaker 1>categories that depend on things like puns or hominem's or

0:34:26.680 --> 0:34:29.720
<v Speaker 1>other forms of word play. So it has to parse

0:34:29.800 --> 0:34:32.359
<v Speaker 1>all of that, and that's even more complicated than just

0:34:32.400 --> 0:34:35.120
<v Speaker 1>taking a simple sentence and figuring out, all, right, what

0:34:35.200 --> 0:34:39.240
<v Speaker 1>are the potential responses to whatever this this this phrase

0:34:39.480 --> 0:34:42.799
<v Speaker 1>is so great, great example. You know, it would end

0:34:42.840 --> 0:34:46.480
<v Speaker 1>up coming up with a potential answer. It would assign

0:34:46.480 --> 0:34:49.520
<v Speaker 1>a percentage of how quote unquote sure it was that

0:34:49.520 --> 0:34:52.279
<v Speaker 1>that was the right answer, and if the percentage was

0:34:52.360 --> 0:34:55.520
<v Speaker 1>higher than its threshold, which I think was something like that,

0:34:56.200 --> 0:34:58.240
<v Speaker 1>it would buzz in and give that as a guess.

0:34:58.880 --> 0:35:02.319
<v Speaker 1>Sometimes it was wrong, but it was right a lot

0:35:02.360 --> 0:35:05.960
<v Speaker 1>of the time, so that's kind of cool. Uh So,

0:35:07.040 --> 0:35:10.279
<v Speaker 1>getting back to Eugene Gene, the main machine as I

0:35:10.280 --> 0:35:13.240
<v Speaker 1>called him in in my notes, at one point uh,

0:35:13.320 --> 0:35:15.879
<v Speaker 1>and of course I'm anthropomorphizing when I say him, it's

0:35:15.880 --> 0:35:18.000
<v Speaker 1>a it's a it's an it. Well, it has a

0:35:18.080 --> 0:35:19.880
<v Speaker 1>dude name. Yeah, it has a dude name and a

0:35:19.960 --> 0:35:26.120
<v Speaker 1>dude persona. But it's ultimately, isn't it. Would you say

0:35:26.200 --> 0:35:30.279
<v Speaker 1>that perhaps some of the reporting around this was was

0:35:30.360 --> 0:35:34.680
<v Speaker 1>maybe a little misleading or at least hype is well,

0:35:35.360 --> 0:35:39.920
<v Speaker 1>you know, okay, the entire Eugene Gooseman chat bought sounds

0:35:40.040 --> 0:35:43.520
<v Speaker 1>really cool. I haven't met it personally, No, I haven't either,

0:35:43.560 --> 0:35:46.440
<v Speaker 1>although you can. There is an Internet version, and I'm

0:35:46.480 --> 0:35:48.399
<v Speaker 1>not sure that it's the same version that's being used

0:35:48.400 --> 0:35:51.240
<v Speaker 1>in competition, because I've seen some transcripts from the Internet

0:35:51.320 --> 0:35:55.600
<v Speaker 1>version and they don't seem good at all. They seem bad, right,

0:35:55.800 --> 0:35:58.040
<v Speaker 1>I guess you'd have to talk to some actual thirteen

0:35:58.120 --> 0:36:02.279
<v Speaker 1>year old boys from actually yeah, that well, this is

0:36:02.360 --> 0:36:05.120
<v Speaker 1>part of it. You know. There's certainly been some some

0:36:05.280 --> 0:36:11.200
<v Speaker 1>questions among uh natural language AI enthusiasts online about whether

0:36:11.800 --> 0:36:15.839
<v Speaker 1>we're really just lowering our expectations for human communication. Which, yeah,

0:36:15.840 --> 0:36:18.440
<v Speaker 1>that's that's a totally different way of looking at and

0:36:18.480 --> 0:36:21.440
<v Speaker 1>a depressing one to say that, Oh, well, if you

0:36:21.560 --> 0:36:24.520
<v Speaker 1>come from this place and if you are of this age,

0:36:24.600 --> 0:36:27.320
<v Speaker 1>then I expect you to only be able to communicate

0:36:27.360 --> 0:36:33.479
<v Speaker 1>at this level, right, which is depressing. It certainly is well,

0:36:33.560 --> 0:36:35.439
<v Speaker 1>but you know, but it's a valid point. I think.

0:36:35.480 --> 0:36:37.480
<v Speaker 1>I think it's a good thing to be thinking about

0:36:37.520 --> 0:36:41.760
<v Speaker 1>in this kind of situation. UM. You know. Beyond that though,

0:36:41.800 --> 0:36:47.080
<v Speaker 1>and I certainly don't want to downplay the apparent achievements

0:36:47.160 --> 0:36:50.960
<v Speaker 1>of its programmers, because I haven't programmed any capable chatbots

0:36:51.000 --> 0:36:56.839
<v Speaker 1>today ever since I did. But there are a few

0:36:56.880 --> 0:36:58.960
<v Speaker 1>things that are just a little bit shady about the

0:36:59.000 --> 0:37:03.480
<v Speaker 1>news UM. First off, the original press release, which came

0:37:03.480 --> 0:37:07.319
<v Speaker 1>out of the University of Reading, I believe so UM

0:37:07.520 --> 0:37:12.239
<v Speaker 1>stated that a quote supercomputer had achieved this feat, and

0:37:12.520 --> 0:37:16.920
<v Speaker 1>perhaps charitably, it was a mistake or misunderstanding on the

0:37:16.960 --> 0:37:19.239
<v Speaker 1>part of the writer of the press release, But some

0:37:19.280 --> 0:37:23.040
<v Speaker 1>skeptics have suggested that it was in fact a purposeful

0:37:23.080 --> 0:37:25.920
<v Speaker 1>publicity play that in fact worked, because a whole lot

0:37:25.960 --> 0:37:31.279
<v Speaker 1>of news headlines around the interwebs repeated the error very excitedly. Yes,

0:37:31.320 --> 0:37:33.640
<v Speaker 1>because it was not a supercomputer. It was a computer

0:37:33.760 --> 0:37:36.719
<v Speaker 1>running a piece of software program. Yes, the program that

0:37:36.760 --> 0:37:40.359
<v Speaker 1>did the work. I mean, the computer just provided the horsepower. Right,

0:37:40.400 --> 0:37:42.560
<v Speaker 1>it's the software that did all the action work, and

0:37:42.560 --> 0:37:47.080
<v Speaker 1>it was not it wasn't on a supercomputer. Little little

0:37:47.680 --> 0:37:51.319
<v Speaker 1>known fact. Supercomputers have better things to do than run

0:37:51.400 --> 0:37:56.279
<v Speaker 1>chatbot software generally. Yeah. Yeah, we're talking about things like

0:37:56.320 --> 0:38:00.560
<v Speaker 1>figuring out global weather changing change pad and some things

0:38:00.600 --> 0:38:03.480
<v Speaker 1>like that, you know, or or the way that money works.

0:38:04.760 --> 0:38:07.880
<v Speaker 1>Chat Bots low on their priority list. It's like number

0:38:07.960 --> 0:38:12.680
<v Speaker 1>seven at least. Um And and also that this press

0:38:12.719 --> 0:38:17.840
<v Speaker 1>release in question was largely a quotation from Dr Kevin Warwick.

0:38:18.640 --> 0:38:22.319
<v Speaker 1>Kevin Warwick, of course being the fellow who organized this

0:38:22.600 --> 0:38:27.080
<v Speaker 1>entire competition, who who's an engineer and a futurist um

0:38:27.160 --> 0:38:31.280
<v Speaker 1>and also the instigator and or enjoyer of a certain

0:38:31.320 --> 0:38:37.440
<v Speaker 1>amount of hype and debate about future technologies. Yeah, he is,

0:38:37.640 --> 0:38:41.160
<v Speaker 1>obviously you can tell. This is the guy who elected

0:38:41.160 --> 0:38:43.399
<v Speaker 1>to have surgery performed on him so he could have

0:38:44.200 --> 0:38:46.200
<v Speaker 1>h that r F I D chip and call himself

0:38:46.239 --> 0:38:51.359
<v Speaker 1>a cybors. This is someone who not only embraces this

0:38:51.600 --> 0:38:54.960
<v Speaker 1>these ideas of futurism, but is actively trying to promote

0:38:55.040 --> 0:38:57.560
<v Speaker 1>them and get to them that we're not even saying

0:38:57.600 --> 0:38:59.319
<v Speaker 1>that that's a bad thing. What we are saying is

0:38:59.320 --> 0:39:03.360
<v Speaker 1>that may give him somewhat of a bias when it

0:39:03.400 --> 0:39:07.600
<v Speaker 1>comes to proclaiming a computer software piece of computer software

0:39:07.760 --> 0:39:11.680
<v Speaker 1>being an amazing achievement that beat the Turing test, right sure.

0:39:11.760 --> 0:39:15.239
<v Speaker 1>I mean he admits basically to to being a provocateur.

0:39:15.400 --> 0:39:17.520
<v Speaker 1>He he says that that's really his job, you know,

0:39:17.800 --> 0:39:22.040
<v Speaker 1>is to get people excited about tech and engineering and

0:39:22.040 --> 0:39:25.000
<v Speaker 1>and the future. And we get that like that that

0:39:25.200 --> 0:39:27.360
<v Speaker 1>we agree that a job too. We think it's red

0:39:27.560 --> 0:39:30.759
<v Speaker 1>We think that perhaps I don't want to put words

0:39:30.800 --> 0:39:33.600
<v Speaker 1>into your mouth, Lauren, I think perhaps that there's a

0:39:33.600 --> 0:39:35.800
<v Speaker 1>different way of going about it where you can still

0:39:36.120 --> 0:39:40.160
<v Speaker 1>be excited, but you can be a little more grounded

0:39:40.200 --> 0:39:42.440
<v Speaker 1>in the way you present things, because I I also

0:39:42.520 --> 0:39:45.040
<v Speaker 1>think the achievement of creating a chatbot that could be

0:39:45.600 --> 0:39:49.440
<v Speaker 1>uh convincing is a fantastic achievement. I mean, it's something that,

0:39:49.760 --> 0:39:52.759
<v Speaker 1>even under any number of qualifications, incredibly challenging to do,

0:39:52.840 --> 0:39:56.400
<v Speaker 1>no matter how you frame it. Um. I do think, however,

0:39:56.520 --> 0:40:00.120
<v Speaker 1>that if you seem to over inflate the achieve it,

0:40:00.480 --> 0:40:03.280
<v Speaker 1>you run the danger of making people feel jaded about

0:40:03.320 --> 0:40:08.360
<v Speaker 1>it later, which I think Computer Wolf exactly, yeah, exactly.

0:40:08.880 --> 0:40:11.719
<v Speaker 1>So it's one of those things where you know, you

0:40:11.800 --> 0:40:15.320
<v Speaker 1>have to take the context into account, right and don't

0:40:15.360 --> 0:40:18.400
<v Speaker 1>don't downplay the achievement. But don't sit there and say like,

0:40:18.440 --> 0:40:21.120
<v Speaker 1>ah ha, now we have intelligent computers everywhere. That's not

0:40:21.200 --> 0:40:24.800
<v Speaker 1>that's not true either. I saw there's a great Wired

0:40:24.880 --> 0:40:30.200
<v Speaker 1>article that specifically went into uh, kind of debunking the

0:40:30.239 --> 0:40:33.960
<v Speaker 1>whole beating the Turing test thing and again kind of

0:40:33.960 --> 0:40:36.080
<v Speaker 1>saying the same thing we're saying, like take the context

0:40:36.120 --> 0:40:39.239
<v Speaker 1>into account, and and part of that article they ended

0:40:39.320 --> 0:40:43.520
<v Speaker 1>up asking a cognitive scientist named Gary Marcus of n

0:40:43.640 --> 0:40:48.040
<v Speaker 1>y U about this, and Marcus proposed a new version

0:40:48.200 --> 0:40:51.040
<v Speaker 1>of the Turing test because he says, the old version

0:40:51.160 --> 0:40:54.480
<v Speaker 1>is not really a measurement of machine intelligence. Uh, it

0:40:54.880 --> 0:40:58.880
<v Speaker 1>does kind of illustrate ways of creating natural language recognition

0:40:59.000 --> 0:41:03.080
<v Speaker 1>and clever way is to fool the human side, uh huh.

0:41:03.160 --> 0:41:06.040
<v Speaker 1>And that it was very valid historically at the time

0:41:06.160 --> 0:41:10.720
<v Speaker 1>because you know, text textual communication was new and exciting

0:41:10.800 --> 0:41:13.320
<v Speaker 1>and it was you know, it pushed the field forward,

0:41:13.360 --> 0:41:15.319
<v Speaker 1>it really did. But now we've gotten to a point

0:41:15.320 --> 0:41:17.880
<v Speaker 1>where fooling the person on the other side of a

0:41:17.960 --> 0:41:21.600
<v Speaker 1>keyboard is not necessarily the goal that we should be

0:41:21.640 --> 0:41:24.279
<v Speaker 1>looking at he proposes. The next version of the Turing

0:41:24.360 --> 0:41:28.520
<v Speaker 1>test should be that a computer software, uh, like any

0:41:28.600 --> 0:41:30.600
<v Speaker 1>kind of program that wants to beat it, what it

0:41:30.640 --> 0:41:34.880
<v Speaker 1>has to do is first quote unquote watch a movie,

0:41:34.920 --> 0:41:38.279
<v Speaker 1>television show, YouTube video, something, some kind of video media,

0:41:38.560 --> 0:41:41.680
<v Speaker 1>and then be able to respond to questions about it.

0:41:41.760 --> 0:41:43.759
<v Speaker 1>So sort of like here, let me show you this

0:41:43.840 --> 0:41:48.560
<v Speaker 1>ten minute video on car safety, and then asking questions

0:41:48.560 --> 0:41:52.360
<v Speaker 1>about specifically about the video, what happened after they fastened

0:41:52.360 --> 0:41:54.279
<v Speaker 1>the seat belt, that kind of thing, and if the

0:41:54.280 --> 0:41:57.359
<v Speaker 1>computer program is able to answer it, then that would

0:41:57.400 --> 0:42:00.960
<v Speaker 1>be a much more convincing touring test than just kind

0:42:00.960 --> 0:42:05.200
<v Speaker 1>of spewing out a script, which is, you know, it's

0:42:05.200 --> 0:42:08.280
<v Speaker 1>adding another layer of difficulty on top of an already

0:42:08.280 --> 0:42:10.719
<v Speaker 1>difficult task. But that's that's the whole only way you

0:42:10.760 --> 0:42:14.120
<v Speaker 1>can go forward. Otherwise we're just going to see increasingly

0:42:14.160 --> 0:42:17.480
<v Speaker 1>sophisticated chat box. Yeah, and and that is actually a

0:42:17.600 --> 0:42:20.720
<v Speaker 1>very difficult and interesting problem. What wasn't it just recently

0:42:20.760 --> 0:42:23.080
<v Speaker 1>that there was a computer that we we taught I

0:42:23.080 --> 0:42:26.239
<v Speaker 1>mean not us personally, but that humanity, some researchers, and

0:42:26.320 --> 0:42:30.719
<v Speaker 1>we're taught taught to identify cats pictures of cats that

0:42:30.800 --> 0:42:34.319
<v Speaker 1>was the AI program that essentially went through thousands and

0:42:34.360 --> 0:42:37.560
<v Speaker 1>thousands of uh I think it was images and videos

0:42:37.680 --> 0:42:41.319
<v Speaker 1>and then became able to identify cats, essentially defined what

0:42:41.480 --> 0:42:44.480
<v Speaker 1>a cat was because no one taught it right. It

0:42:44.880 --> 0:42:48.640
<v Speaker 1>learned what cats are based upon their appearance, on their

0:42:48.640 --> 0:42:51.560
<v Speaker 1>appearance and can look at pictures of cats and say

0:42:51.600 --> 0:42:54.719
<v Speaker 1>that is totally a cat, essentially saying that thing that

0:42:54.840 --> 0:42:56.960
<v Speaker 1>is in that video is the same as this other

0:42:57.040 --> 0:42:58.880
<v Speaker 1>thing that's in this picture. That's the same as this

0:42:58.960 --> 0:43:01.560
<v Speaker 1>other thing that's in this totally different video, which sounds

0:43:01.800 --> 0:43:05.840
<v Speaker 1>trivial and hilarious, and it kind of is hilarious. Also

0:43:05.960 --> 0:43:08.320
<v Speaker 1>easy because I mean, come on, everything on the internet

0:43:08.360 --> 0:43:10.759
<v Speaker 1>has cats in it. Yeah, that is That is kind

0:43:10.760 --> 0:43:12.799
<v Speaker 1>of a gimme, isn't it? But still no, it is.

0:43:12.840 --> 0:43:15.440
<v Speaker 1>It is cool. I mean because just just that level

0:43:15.480 --> 0:43:18.319
<v Speaker 1>of image recognition, I mean being able to take an

0:43:18.320 --> 0:43:20.960
<v Speaker 1>object and look at it from a different angle than

0:43:21.000 --> 0:43:25.879
<v Speaker 1>you were taught or that's a different color, different different size. Yeah,

0:43:25.920 --> 0:43:28.279
<v Speaker 1>all these things. All of these things are easy for us,

0:43:28.480 --> 0:43:32.400
<v Speaker 1>hard for computers. So seeing something make that breakthrough is

0:43:32.440 --> 0:43:35.560
<v Speaker 1>really exciting. Anyway, we thought we would take that story

0:43:35.719 --> 0:43:37.560
<v Speaker 1>and kind of break it down for you guys, explain

0:43:38.000 --> 0:43:41.000
<v Speaker 1>how it's still cool but maybe not as cool as

0:43:41.000 --> 0:43:43.440
<v Speaker 1>the way some of the headlines are saying. Right, and

0:43:43.480 --> 0:43:47.759
<v Speaker 1>also say, hey internet journalists, um, step up your game. Yeah,

0:43:47.880 --> 0:43:50.960
<v Speaker 1>I understand that you want people to read your stuff.

0:43:51.000 --> 0:43:53.840
<v Speaker 1>Oh yeah, and you're under deadline pressure and that's terrible.

0:43:53.960 --> 0:43:59.200
<v Speaker 1>But that's that's hard. Let's reality. We don't just don't

0:43:59.200 --> 0:44:02.640
<v Speaker 1>just spit up us releases the way that you found them. Yeah,

0:44:02.680 --> 0:44:05.560
<v Speaker 1>and uh, and I would be criminal to to neglect

0:44:05.719 --> 0:44:11.040
<v Speaker 1>to mention, knowl Our producer reminded me that obviously this

0:44:11.080 --> 0:44:14.680
<v Speaker 1>is a very important field of study because we want

0:44:14.719 --> 0:44:16.920
<v Speaker 1>to be able to tell the difference between computers and

0:44:17.040 --> 0:44:22.279
<v Speaker 1>humans when the future of Blade Runner becomes our reality

0:44:22.400 --> 0:44:24.680
<v Speaker 1>and you're chasing down a replicant and you have to

0:44:24.680 --> 0:44:27.399
<v Speaker 1>determine if it's actually a replicate or human. Being very

0:44:27.440 --> 0:44:31.960
<v Speaker 1>good point, computer programmers, just make sure you don't explain

0:44:32.080 --> 0:44:33.680
<v Speaker 1>sort of you know, what you do if you see

0:44:33.680 --> 0:44:36.319
<v Speaker 1>in turtle laying on back and you've decided not to

0:44:36.360 --> 0:44:40.960
<v Speaker 1>turn it over, because that's like that's like our gimme, Yeah, yeah,

0:44:41.120 --> 0:44:45.319
<v Speaker 1>we got yeah, we need that. So everything else fair game.

0:44:45.520 --> 0:44:48.399
<v Speaker 1>All right, So that wraps up this discussion. Guys. First

0:44:48.440 --> 0:44:51.840
<v Speaker 1>of all, thank you so much Nick for for asking

0:44:52.040 --> 0:44:54.719
<v Speaker 1>us about that. And if anyone else wants to ask

0:44:54.840 --> 0:44:57.840
<v Speaker 1>us to talk about anything in particular right now, I

0:44:57.840 --> 0:45:01.440
<v Speaker 1>would highly suggest you use Twitter, Facebook, or Tumbler. We

0:45:01.480 --> 0:45:04.520
<v Speaker 1>have to handle tech stuff hs W. We will soon

0:45:04.640 --> 0:45:07.359
<v Speaker 1>have an email address, but coming any day now. Yeah,

0:45:07.360 --> 0:45:11.359
<v Speaker 1>we need we're making this transition from one kind of

0:45:11.400 --> 0:45:14.440
<v Speaker 1>email server to a different one. We're getting new email addresses,

0:45:14.880 --> 0:45:17.520
<v Speaker 1>and as of right now, as we're recording this podcast,

0:45:17.560 --> 0:45:20.200
<v Speaker 1>I think tech Stuff does not yet have one. Our

0:45:20.239 --> 0:45:24.439
<v Speaker 1>future address will be tech stuff at how stuff works

0:45:24.480 --> 0:45:28.959
<v Speaker 1>dot com. So if you're listening to this in try it. Yeah,

0:45:28.960 --> 0:45:31.279
<v Speaker 1>it should be fine. But if you're listening to this

0:45:31.920 --> 0:45:34.239
<v Speaker 1>the day it comes out and you wanted to send

0:45:34.280 --> 0:45:36.840
<v Speaker 1>us a message and it's bouncing back, try Twitter, Facebook

0:45:36.920 --> 0:45:39.960
<v Speaker 1>or Tumbler and we will get your message there. And yes,

0:45:40.040 --> 0:45:41.680
<v Speaker 1>we are working on this. We'll have it up as

0:45:41.680 --> 0:45:43.839
<v Speaker 1>soon as we possibly can, and we'll talk to you

0:45:43.880 --> 0:45:49.960
<v Speaker 1>again really soon for more on this and bathens of

0:45:49.960 --> 0:46:02.000
<v Speaker 1>other topics. Because it how stuff works dot com