Speaker 1: Brought to you by the reinvented two thousand twelve camera.
Speaker 1: It's ready. Are you get in touch with technology with
Speaker 1: tech Stuff from how stuff works dot com. Hello again, everyone,
Speaker 1: welcome to tech stuff. My name is Chris Polette. I'm
Speaker 1: the tech editor here at how stuff works dot Com.
Speaker 1: Sitting across from me, as usual, is senior writer Jonathan Strickland.
Speaker 1: The light is green, the trap is clean. I'm sure
Speaker 1: there's some of people listening to you who don't have
Speaker 1: a ghost of an idea what you're talking about. Well,
Speaker 1: considering that most of our fans also listen to stuff
Speaker 1: you should know, and considering Chuck's obsession with that movie,
Speaker 1: I'm pretty sure they picked up on it. Good point.
Speaker 1: So what we're gonna talk about today has nothing to
Speaker 1: do with ghosts. Nope, Oh thing, well done, Pialette. All right,
Speaker 1: we're gonna talk about artificial consciousness, which is sort of
Speaker 1: a similar concept to artificial intelligence. Yes, but it is
Speaker 1: entirely different only similar. Yeah, it's kind of yeah, this
Speaker 1: is this is talking about. So we wanted to talk
Speaker 1: a little bit about whether or not we ever thought
Speaker 1: it was going to be possible to create a conscious
Speaker 1: artificial construct in some form, whether it's a computer or
Speaker 1: a robot or whatever. Well, this's the sort of top
Speaker 1: of mind for us because you've been writing a couple
Speaker 1: of articles for the site along these lines, right, We've
Speaker 1: been writing, or I've been writing quite a bit about
Speaker 1: artificial intelligence and artificial consciousness. I even wrote a blog
Speaker 1: post for Discovery about the subject as well. And um,
Speaker 1: and so we thought we'd kind of talked about it
Speaker 1: because it's a really interesting concept. Um, it's really difficult
Speaker 1: to talk about, as it turns out, because consciousness is
Speaker 1: is not a really well defined term. Yeah, from the
Speaker 1: research that I did for the podcast, in addition to
Speaker 1: having read your articles. Um, it's funny because some people
Speaker 1: think that a computer or a machine can achieve consciousness,
Speaker 1: but it all depends on how you define consciousness, and
Speaker 1: it's very difficult to do that for a human being,
Speaker 1: let alone a machine. Right Exactly, if we can't, if
Speaker 1: we can't define it for ourselves, how can we hope
Speaker 1: to define it in some other kind of of device.
Speaker 1: I mean, you know, when you think about it, our
Speaker 1: total experience is with us, you know, that's that's as
Speaker 1: far as we know that, that's the only experience we
Speaker 1: have with conscious beings is uh and and really some
Speaker 1: would argue. Some philosophers would argue the only experience each
Speaker 1: of us has is with his or her own consciousness,
Speaker 1: and that we can only extrapolate that what other people
Speaker 1: experience is similar to what we experience. Now, did I
Speaker 1: just blow your mind? Because it blew my mind. You
Speaker 1: start thinking about that, and you're thinking, okay, well, let's
Speaker 1: say that Chris and I are both looking at a coin,
Speaker 1: and the coin is blue. As far as you know,
Speaker 1: we it is what we You call it blue and
Speaker 1: I call it blue. But how do I know that
Speaker 1: what Chris calls blue Chris perceives the same way that
Speaker 1: I perceive blue? Like wayn't know. Maybe what Chris sees
Speaker 1: when he looks at a coin, I would call it red.
Speaker 1: But we've arrived at a common vocabulary. We're both calling
Speaker 1: it blue, and as far as we know, the other
Speaker 1: person is experiencing it the same way that we ourselves
Speaker 1: are experiencing it. We don't know for sure. UM. I
Speaker 1: wanted to throw in this quote before we get too
Speaker 1: far away from this thought because psychologist Susan Blackmore had
Speaker 1: an article and a new scientist, UM, actually, it was
Speaker 1: quoted by another uh researcher, igor Alexander Um but her
Speaker 1: I love the quote that he had chosen from her article.
Speaker 1: Um said that the trying to find the inner sensation,
Speaker 1: that's you know her the quote there. But it's like
Speaker 1: looking in a fridge to see whether the light is
Speaker 1: always on right right. So so I mean, just you're
Speaker 1: going by your own self diagnostic, it's like, well, it
Speaker 1: must always be on since right right, because that's what
Speaker 1: I always see. Certain certainly, there are things that we
Speaker 1: can mention about. They seem to be kind of agreed
Speaker 1: upon as being part of consciousness. Things like an inner
Speaker 1: monologue and inner voice, something that is within us that
Speaker 1: we can hear, we can rely on, We can you know,
Speaker 1: think things out without speaking it aloud, without having any
Speaker 1: outward appearance that that's going on, it's happening inside us.
Speaker 1: That's part of consciousness. Uh it could you could also
Speaker 1: argue that anything, any source of sensation, is part of consciousness.
Speaker 1: Sensations like pain or love, or ambition or fear or
Speaker 1: that's hot. I mean, you know, it's it's more than
Speaker 1: it's not just physiological. There's something within the mind as
Speaker 1: well that is bring this into a concept, not just
Speaker 1: a you know, stimulus response. Yes, and and some people
Speaker 1: will argue that a computer or a machine can figure
Speaker 1: that out. It can you know, use it thermometer and go, well,
Speaker 1: that's hot, or you know, a self diagnostic program would say, hey,
Speaker 1: my wheel has fallen off. Therefore I shouldn't go anywhere
Speaker 1: because I will hurt myself. But then the exactly that's
Speaker 1: and that's a good a good way of dividing it,
Speaker 1: because is the machine actually feeling anything? As a human,
Speaker 1: we would say, we'd feel that, you know, we it's
Speaker 1: not just that we've recognized that. We're Like, if you
Speaker 1: cut my hand off, Chris, which I am not recommending
Speaker 1: you do, I'm you know, I have an adversion of blood.
Speaker 1: I don't want to go as lefty for the rest
Speaker 1: of my life. Um, but if you were to cut
Speaker 1: off my hand, chances are I would have some clues
Speaker 1: to that other than just looking down and noticing my
Speaker 1: hand was gone. It wouldn't just be that I had noted, hey,
Speaker 1: my hand is no longer there. I would be feeling pain, fear, probably, uh,
Speaker 1: quite surprised. Chris has never raised a finger to me,
Speaker 1: and I can't believe you would do such a thing
Speaker 1: jerk so um, But at any rate, I would feel
Speaker 1: these things. A machine if it were to lose a
Speaker 1: part but be able to recognize that. We wouldn't say
Speaker 1: that it felt it. We would say that it detected
Speaker 1: it and then maybe even found a way to respond
Speaker 1: appropriately so they could continue to function. But that's not
Speaker 1: the same as feeling, which some would argue is part
Speaker 1: of consciousness. For some reason, I put the image of
Speaker 1: C three Po in my head after he had been
Speaker 1: blown apart and he was trying to figure out where
Speaker 1: the rest of him was. All right, Yes, yes, um,
Speaker 1: that wasn't that great documentary a New Hope. It wasn't
Speaker 1: in a New Hope. Well you know it's in Cloud City.
Speaker 1: Oh you're right, yeah, because yeah he was. He was
Speaker 1: just damaged a bit. Yes, actually no, he came came
Speaker 1: to pardon in New Hope as well. The sad people
Speaker 1: knocked me you know what. That's good point? Yes, uh,
Speaker 1: C three Po, that's I don't know why fee paying. No, No,
Speaker 1: he just was uh, but he did appear to feel something.
Speaker 1: C three Po was definitely cowardly, wouldn't you say? Well,
Speaker 1: he does say one of his most famous lines problem
Speaker 1: Star Wars and you hope is I have a bad
Speaker 1: feeling about this, and then there's yes, who is alive?
Speaker 1: You arub So consciousness is not the only concept that's
Speaker 1: difficult to define. Intelligence, as it turns out, is also tricky. Now.
Speaker 1: If you think of intelligence as the ability to solve problems,
Speaker 1: computers are pretty good at that. In fact, computers have
Speaker 1: gotten I've gotten better at even learning how to solve problems.
Speaker 1: Before you might argue that computers could only solve things
Speaker 1: that um that someone had a programmed into it. In
Speaker 1: other words, they computers knew how to do basic arithmetic
Speaker 1: and that was about it. But if you gave it
Speaker 1: a mathematical problem, it could work it out because it
Speaker 1: knew the rules. Right. But we've made a lot of
Speaker 1: progress in artificial intelligence to the point where computers can
Speaker 1: do things now like recognized patterns. That's how you get
Speaker 1: these cool cameras that have facial recognition stuftware built into them. Um,
Speaker 1: they can learn, they can extrapolate. We have the computer
Speaker 1: from Cornell that was able to extrapolate the basic laws
Speaker 1: of physics just by observing the movements of a pendulum.
Speaker 1: I was able to do that in over a little
Speaker 1: over twenty four hours, which is pretty remarkable considering how
Speaker 1: long it took us to get there. But um, what
Speaker 1: what is this intelligence? Is that what we would define
Speaker 1: as intelligence just the ability to solve problems? Um. I
Speaker 1: have to like Marvin Minsky's definition of intelligence, um, which
Speaker 1: he compared to unexplored regions of Africa. More you learn
Speaker 1: about it, the less there is of it. So in
Speaker 1: other words, we defined and we we defined intelligence not
Speaker 1: by what it is, but by what it isn't. So
Speaker 1: as we find ways to allow computers to do things,
Speaker 1: we have philosophers jump up and say, well, that's not intelligence.
Speaker 1: For example, a computer being a human. At chess, right,
Speaker 1: deep Blue Deep Blue beats Gary casper of In. Gary
Speaker 1: Casperov was the the world champ chess champion at the time,
Speaker 1: and he had met Deep Blue once before and emerged victorious.
Speaker 1: H I think it was ninety six when he played
Speaker 1: it the first time, played the computer the second time
Speaker 1: in ninety seven, and in a series of six games
Speaker 1: actually lost eventually. Um, ultimately Deep Blue came out the
Speaker 1: victory in that one. Well, you could argue, well, this
Speaker 1: is an example of artificial intelligence. Look a machine has
Speaker 1: beaten a human at this this task. But some people
Speaker 1: were jumping up and saying, oh, well, you know, playing
Speaker 1: ches us, that's not really intelligence, that's just you know,
Speaker 1: it's just this kind of task thing. So well, if
Speaker 1: that's not intelligence, what is it. So what you're doing
Speaker 1: is you're you're slowly removing aspects that were grouped kind
Speaker 1: of a nomen in this weird, vague, anomalous form under
Speaker 1: the term intelligence, until intelligence is meaning fewer and fewer things,
Speaker 1: until eventually the word itself maybebe meaningless as as far
Speaker 1: as it applies to machines. So we've got we've established
Speaker 1: that intelligence is hard to define, Consciousness is hard to define.
Speaker 1: We still need to get to can machines have these
Speaker 1: things whatever they may be defined as? Would a machine
Speaker 1: be able to possess this? Um? I'm gonna let you
Speaker 1: answer this one because I know, I know you're the expert,
Speaker 1: and I hate to get in your way. Well, um,
Speaker 1: and uh, er um, maybe no. Here here's the thing.
Speaker 1: It's without being able to define it in ourselves, it's
Speaker 1: really hard to say how would we imbue that into
Speaker 1: a machine? Yeah? Well, I mean, frankly, depending on your definitions,
Speaker 1: they've already achieved consciousness, because I mean some people are
Speaker 1: are a lot more maybe lenient. I don't know. I
Speaker 1: think I think some people may have very very very
Speaker 1: basic definitions of intelligence and consciousness, and to them it
Speaker 1: means perhaps uh, problem solving and perhaps some form of
Speaker 1: self diagnostic And if if that's all it takes for
Speaker 1: you to hit the definition of artificial intelligence and consciousness,
Speaker 1: sure we have devices that can do that. We do
Speaker 1: not have a lot of devices that can do things
Speaker 1: like adapt to a new situation. They can, they can
Speaker 1: possibly you know, and when I'm talking about a new situation,
Speaker 1: I'm talking about totally new, not just like Okay, well
Speaker 1: this this robot can um identify obstacles in its path
Speaker 1: and chart and alter the pathway to get to its destination.
Speaker 1: There we have robots that can do that. Um, I'm
Speaker 1: talking about putting it into a totally new situation. So
Speaker 1: you put this robot that normally can just find its
Speaker 1: way from one point to the next, and give it
Speaker 1: some other sort of task that has nothing to do
Speaker 1: with that. You know, while the robot isn't programmed to
Speaker 1: deal with that situation unless you have built in some
Speaker 1: sort of learning program where it can look at a
Speaker 1: totally new task, a totally new situation and adapt to it.
Speaker 1: I don't know that you could truly call it intelligent
Speaker 1: in the way that I think most people envision when
Speaker 1: they think of the science fiction version of an artificially
Speaker 1: intelligent robot or machine. Yes, so you can take a
Speaker 1: robot to the movies, but you can't put it in
Speaker 1: front of the concession counters say I'm sorry, we're out
Speaker 1: of diet Dr Pepper. What else would you like and
Speaker 1: have it actually make an informed, conscious decision. First second
Speaker 1: choice would be no machine and its right mind would
Speaker 1: ever ask for diet Dr Pepper in the first place.
Speaker 1: So your scenario is just laughable. But well, you know,
Speaker 1: I'm trying. These are difficult philosophical questions. Yes they are.
Speaker 1: These are not These are not These aren't pat answers
Speaker 1: that we're trying to give either. These are Um let's
Speaker 1: think about what, well, how would we even recognize if
Speaker 1: a machine had consciousness or intelligence? Yeah? See, it it
Speaker 1: all goes Yeah, it's right. I mean, like, if you
Speaker 1: ask it a question and it responds, does that mean
Speaker 1: that it was intelligent or does that just mean it
Speaker 1: had an excellent database from which it could pull a response. Yeah. Yeah,
Speaker 1: Now I'm actually going back to Igor Alexander, who by
Speaker 1: the way is the emeritus professor and Senior Investigator in
Speaker 1: Neural Systems and Imperial College in London. UM. He's got
Speaker 1: five axioms that helped define that, he say. He says
Speaker 1: defined consciousness UM, and that is a sense of place, imagination,
Speaker 1: directed attention, planning and decision and emotion. And so basically,
Speaker 1: you create a representation of a scenario in your head.
Speaker 1: You can think about it the way it was in
Speaker 1: the past, you can think about it in the way
Speaker 1: it will be in the future. And that is basically
Speaker 1: more or less in a nutshell and an oversimplified fashion,
Speaker 1: done by me your consciousness. And he said that basically
Speaker 1: a computer probably could be programmed to do that UM
Speaker 1: in some fashion. I just the idea of actually accomplishing
Speaker 1: that is sort of I don't know beyond me how
Speaker 1: you would actually accomplish that. UM. One person who is trying, however,
Speaker 1: UM is somebody who mentioned in his article UH scientists
Speaker 1: at the Technical University of Denmark named Running Codroll, who
Speaker 1: is looking at human and animal brains and the neurochemical
Speaker 1: interactions that take place inside the brain, and he's trying
Speaker 1: to when he identifies these reactions in a brain, he
Speaker 1: tries to replicate that on a computer to see if
Speaker 1: he can find out where consciousness is and make it
Speaker 1: happen on a on a machine, which is kind of
Speaker 1: a weird I mean, that's that's so scientific that you know,
Speaker 1: it's a monumental task. I mean, we've got, for example,
Speaker 1: there's the there's the Blue Brain Project which is in
Speaker 1: Europe now, the Blue Brain Project. Their goal is not
Speaker 1: to create an artificially intelligent or conscious uh entity, That's
Speaker 1: not their goal. What their goal is is to create
Speaker 1: a synthetic model of the human brain so that neuroscientists
Speaker 1: and neuro neurologists can can find new ways of treating
Speaker 1: the human brain for you know, various diseases or conditions,
Speaker 1: that kind of thing without ever having to you know,
Speaker 1: get into a human's brain. You know. The idea is
Speaker 1: that you could simulate these things and then see how
Speaker 1: the brain might respond to specific kinds of treatment, because
Speaker 1: again you're using a simulation of the human brain. Some people, um,
Speaker 1: I read an article in the Daily Mail, which are
Speaker 1: friends over the UK. Maybe giggling right now. But in
Speaker 1: the Daily Mail there was an article written where the
Speaker 1: authors seemed to take the leap of if you were
Speaker 1: to simulate a human brain with all the connections and
Speaker 1: and uh the abilities therein, would you then give birth
Speaker 1: to an artificially intelligent, artificially conscious entity. Uh. The scientists
Speaker 1: there say that's probably not gonna happen. It's just way
Speaker 1: too complicated. Um. They're just trying to create, uh, like
Speaker 1: I said, a simulation, not not recreate the brain itself. Um.
Speaker 1: And they point out that the brain is incredibly complex.
Speaker 1: You're talking about trillions of of neurons, and to try
Speaker 1: and simulate that in a in a meaningful way is
Speaker 1: would require so much computing power that it's it's really
Speaker 1: hard to even conceive of. I mean, yeah, we've got
Speaker 1: computers out there that are really powerful, but you'd have
Speaker 1: to design very specific software for those computers to run
Speaker 1: in order to even come close to simulating what goes
Speaker 1: on in the human brain. So uh, now, this this
Speaker 1: doesn't mean that people haven't tried to create machines or
Speaker 1: or programs that mimic humans in some way. I mean,
Speaker 1: the whole concept of the touring test is The Touring
Speaker 1: test is a test that that when you give it
Speaker 1: to a machine, when a machine passes the Touring test,
Speaker 1: when humans are not able to determine reliably whether it
Speaker 1: was a machine or a human taking the test. Yes,
Speaker 1: the name for Alan Touring, the famous British computer computer scientist. Yes.
Speaker 1: So the idea here is that let's say that you
Speaker 1: have a series of questions that that you would pose
Speaker 1: a an unknown respondent, and then you get the response
Speaker 1: responses back. At the end of the test, you would
Speaker 1: be asked, all right, well do you think that was
Speaker 1: a person or do you think that was a computer?
Speaker 1: And you would give your response, and if you were
Speaker 1: unable to determine that it was a computer better than chance,
Speaker 1: and usually significantly better than chance, uh, then you could
Speaker 1: say that the computer passes the Touring test. However, this
Speaker 1: does not necessarily mean that the program or machine or
Speaker 1: whatever is actually intelligent. In fact, Touring himself said that
Speaker 1: that was not really a definition of intelligence. He said,
Speaker 1: it's possible that a computer that you might think of
Speaker 1: as intelligent because it is capable of responding to new stimuli,
Speaker 1: that's capable of of solving problems, an intelligent computer might
Speaker 1: fail the touring test because it wasn't designed to give responses.
Speaker 1: So so you can have an intelligent computer that fails
Speaker 1: the touring test right on the same by the same token,
Speaker 1: you can have a computer that passes the touring test,
Speaker 1: but does so because it has such a huge database
Speaker 1: from which it can draw responses that it seems like
Speaker 1: it's far too sophisticated for it to be a computer program.
Speaker 1: It's still not being intelligent. And there's a an interesting
Speaker 1: problem that um that another uh scientists suggested, um cirl
Speaker 1: I believe it was who suggested the Chinese room problem.
Speaker 1: Have you heard of this? I believe so, but refresh
Speaker 1: my memory. Alright, So here's the Chinese room problem. This
Speaker 1: is this is comparing a humans experience with let's say
Speaker 1: a machine's experience. I could pass the tourin test. The
Speaker 1: problem is that let's say, UM, let's say I'm transported
Speaker 1: to China. I'm putting into a little room in China,
Speaker 1: and there are two slots in this room. Through one slot,
Speaker 1: I get a little card that has a Chinese figure
Speaker 1: drawn on it alphabe figure from the alphabet and my
Speaker 1: character and I I UM look through a series of tables,
Speaker 1: and I see that there is a particular response that
Speaker 1: I should UM draw that based upon this figure that
Speaker 1: I've seen. So I draw the approa brit figure, and
Speaker 1: then I slide it out of the um the other slot.
Speaker 1: Now I've given the correct response, but I have no
Speaker 1: comprehension of what it is I have just done. All
Speaker 1: I know is I have one card, and I've drawn
Speaker 1: a second card and I've given it back. That's the
Speaker 1: the the challenge of a machine passing the touring test
Speaker 1: but still not being intelligent. The machines responding the correct
Speaker 1: way but has no actual comprehension of what it's doing. Now,
Speaker 1: one UM criticism you can have of this problem is
Speaker 1: that this is just taking into account one part of
Speaker 1: the machine. If you think of the data tables as
Speaker 1: part of the machine, if you think of the slots
Speaker 1: as part of the machine, if you think of the
Speaker 1: whole system as part of the machine, then you could say, well,
Speaker 1: now it's a little fuzzy. Maybe the machine is intelligent.
Speaker 1: It's just that this one part of the machine, the
Speaker 1: machine that's doing this one section itself, is not intelligent.
Speaker 1: But that you can't say the whole system is unintelligent.
Speaker 1: That's the Chinese problem, and the logical response to the
Speaker 1: Chinese problem what is called the logical response, and then
Speaker 1: you're eight. Unfortunately, our consciousness is don't always operate logically?
Speaker 1: No always? Are you talking hardly? Ever? Now, um, I've
Speaker 1: got an interesting little conversation to to read to you. Okay, okay.
Speaker 1: This is a conversation between um, Well, have you heard
Speaker 1: of Perry Perry p A R R Y. It's one
Speaker 1: of the earliest artificially intelligent programs designed. Um, so this
Speaker 1: is this was one of those tests that was done
Speaker 1: where you know, you're familiar with the various artificial intelligent
Speaker 1: UH programs where you type in a question and the
Speaker 1: computer responds to you and then you type back a
Speaker 1: smarter child, right, this is like going back to the
Speaker 1: touring test type stuff. Well, this Perry was written by
Speaker 1: a Stanford University psychiatrist named as Colby, and it was
Speaker 1: a program designed to respond as if it were a
Speaker 1: patient suffering paranoia. And the idea here was that under
Speaker 1: the parameters of a patient suffering from paranoia, it was
Speaker 1: actually fairly um um convincing. Now, granted that's a narrow
Speaker 1: set of parameters, that's not the whole human experience. We
Speaker 1: talked about this once before, I think in artificial intelligence.
Speaker 1: So here's here's an example. Uh, why are you in
Speaker 1: the hospital. I shouldn't be here. Who brought you here?
Speaker 1: The police? What trouble did you have with the police?
Speaker 1: Cops don't do their job? What did they do? Instead?
Speaker 1: Cops arrest the wrong people? They arrest the right ones.
Speaker 1: Sometimes the law should get those Italian crooks? Are you Italian?
Speaker 1: My background is British, but I was born in this country.
Speaker 1: Do you know any Italian crooks? I tried to avoid
Speaker 1: the underworld that was, you know, so it's really kind
Speaker 1: of gone off the reels there. Yeah, but still you
Speaker 1: you would if you were just looking at that as text.
Speaker 1: You know, you don't have any tone, you don't have
Speaker 1: any inflection or anything. It it reads like a paranoid patient.
Speaker 1: It doesn't. It's not. It's close enough to what the
Speaker 1: questions are that you could conceivably think, all right, well,
Speaker 1: that that could possibly be a person on the other
Speaker 1: end of this, not a computer program. Yes, clearly I'm
Speaker 1: not a psychologist, not even remotely. But and I think
Speaker 1: though that when I was listening to you say that
Speaker 1: I was feeding my own I know this, you know,
Speaker 1: my own consciousness, that that was a computer. On the
Speaker 1: other end, it began to seem very random to me.
Speaker 1: If I did not know if I was a computer,
Speaker 1: then I might if I had perhaps presented you with
Speaker 1: a series of conversations, some of which were from real
Speaker 1: patients and some of which were from Perry, you might
Speaker 1: have had more of a challenge. So that was not
Speaker 1: very scientific on my part. Yeah, but no, I mean
Speaker 1: I thought the same thing when I first read it,
Speaker 1: and then I thought, well, wait a minute, let me
Speaker 1: put myself in the position of I don't know from
Speaker 1: whom this is coming. Well, that makes more sense. You
Speaker 1: still might think it's a little unusual. But then again,
Speaker 1: if it you believed that it was coming from a
Speaker 1: human being, you might think that there's something wrong. So,
Speaker 1: for argument's sake, let's say that somehow we have found
Speaker 1: a way to create what we would traditionally consider artificially intelligent,
Speaker 1: artificially conscious machine. What then, Oh good, you gave me
Speaker 1: the easy question. So let's say that put us on
Speaker 1: the road to the singularity. Well, it could, or it
Speaker 1: could put us on the road to uh Morocco. Oh,
Speaker 1: wait now that's a movie terminator, is what I was? Um,
Speaker 1: you create these artificially intelligent creatures that can now not
Speaker 1: only are they self aware, but you know, they can
Speaker 1: truly examine the position that they are in and UM
Speaker 1: and their relationship hup to us and perhaps even decide, hey,
Speaker 1: you know what? UM, Yeah, I can continue to create
Speaker 1: better versions of me UM at a much faster rate
Speaker 1: than evolution will allow humans to. We get to get
Speaker 1: better over millions of years. So why don't I just
Speaker 1: wipe these guys out? And because I don't need them anymore,
Speaker 1: I got everything I need and UM, I'll do it myself. Uh.
Speaker 1: I suppose if you had consciousness without emotion and you
Speaker 1: are logic based, it might seem logical to you know,
Speaker 1: or even with emotion. Just because you have emotion doesn't
Speaker 1: mean you necessarily have compassion towards humans. Good point, you
Speaker 1: could have compassion towards other robots and think, well, why
Speaker 1: are we even though yes, we don't have the benefit
Speaker 1: of being organic, but why should we be forced into servitude?
Speaker 1: You know What's that's of course, that would be the
Speaker 1: whole argument of AI the movie AI UM, where robots
Speaker 1: weren't necessarily uh, malevolent towards humans. They just they had
Speaker 1: been used as tools. And once your tool has the
Speaker 1: ability to figure out how lousy life is, then you
Speaker 1: have a lot of questions to answer, you know, a
Speaker 1: lot of ethical problems. Um. And they're planning of science
Speaker 1: fiction novels and movies and television shows that have explored this. Uh.
Speaker 1: And again it's another philosophical question. Now, garranted, I think
Speaker 1: it's pretty much a moot point because I'm not sure
Speaker 1: that we're ever going to get there. For one thing,
Speaker 1: I don't know that we necessarily need anything that has
Speaker 1: that kind of artificial intelligence or conscious to it. Yeah,
Speaker 1: I mean it's I think people are investigating it more
Speaker 1: because they're curious, then because there's an actual need. If
Speaker 1: nothing else, I think it'll lets us examine ourselves more.
Speaker 1: But when it comes to creating, you know, actually, let's
Speaker 1: say that somehow we had the technological breakthrough where we
Speaker 1: figured out we could do it if we wanted to.
Speaker 1: I don't know that we would want to. I mean,
Speaker 1: for one thing, we're kind of assuming in in this
Speaker 1: case that the machine brain we create is at least
Speaker 1: on some level comparative to a human brain. Well, it
Speaker 1: turns out human brains aren't hard to create. It just
Speaker 1: takes two people. We can make lots and lots of
Speaker 1: human brains. There's no shortage of them, as it turns out,
Speaker 1: which is that's that's kind of why. That's one of
Speaker 1: the arguments that you know, even AI specialists will say that, well,
Speaker 1: there's no point in creating that. Why would we try
Speaker 1: and create an artificial human? We can create real humans.
Speaker 1: In fact, that's kind of a problem in some places.
Speaker 1: We have way too many real humans. Why would we
Speaker 1: create fake ones? Um, I think it's a good argument.
Speaker 1: You know, it makes more sense to create machines that
Speaker 1: are really really good at doing specific tasks and not
Speaker 1: worry so much about creating a machine that is capable
Speaker 1: of doing any task. Yeah, that doesn't really make any sense.
Speaker 1: I mean, it's we should build stuff that that does
Speaker 1: certain things really well and not worry about trying to
Speaker 1: create a mechanical replacement for the human race. Yeah, we
Speaker 1: all know how that's gonna end up. And see that's
Speaker 1: why I vote against robot rights. I do not give
Speaker 1: the right to vote to my toaster, yes, because it
Speaker 1: will probably vote for bagels, and I prefer toast. Okay,
Speaker 1: I do say so, so at any rate, I guess
Speaker 1: we can wrap up this conversation. It has been rather
Speaker 1: high level and uh and and a bit intellectual, and
Speaker 1: it gets pretty cerebral at times. It does have to intelligence,
Speaker 1: and we didn't even get into the mind body problem,
Speaker 1: which that's another philosophical issue. Um, Will we ever get there?
Speaker 1: I don't I looking at what we're doing now, I'm
Speaker 1: not sure that we're going to get there within our
Speaker 1: lifetime because it's just it's incredibly complex. Now, if you're right, Kurts, while,
Speaker 1: he'll probably think that we're going to get there because well, yeah, Kurts,
Speaker 1: while uh, he's the guy who came up with the
Speaker 1: theory of the singularity. UM. He believed that we're going
Speaker 1: to create machines that can create better machines, which in
Speaker 1: turn can create even better machines, and the time between
Speaker 1: generations will get shorter and shorter until we're we reach
Speaker 1: a point where we're just in a constant state of evolution,
Speaker 1: and then either humans become obsolete they merge with this
Speaker 1: new form of technology UM, or they are we're all
Speaker 1: freed up to you know, swim in the pool and
Speaker 1: and watch television and while the machines do everything we
Speaker 1: need them to do. I don't know that that's coming.
Speaker 1: I think that might be a little pie in the sky.
Speaker 1: We never know. We could end up in a ragtag
Speaker 1: fugitive fleet. We could end up in a large deep
Speaker 1: space mining vessel and then have to go into uh
Speaker 1: To to to frozen carbonation for like a couple of
Speaker 1: million years while the cat evolves. You have no idea
Speaker 1: what I'm talking about. Vaguely, you've seen Red Dwarf. I'm
Speaker 1: familiar with the plot. Okay, I've seen a couple of episodes.
Speaker 1: All right, well, I guess that's a good enough reason
Speaker 1: for us to wrap this up then, is right there?
Speaker 1: We're done. Um, let's just move on to a little
Speaker 1: listener mail. This listener mail comes from Chris, and Chris says, Hello,
Speaker 1: Chris and Jonathan. My name is Chris, and I have
Speaker 1: been an avid listener to your podcast since I discovered
Speaker 1: it last year. I had to take a break from
Speaker 1: listening to them as I went into the military. Anyway,
Speaker 1: after I got discharged and got back to work, I
Speaker 1: caught up on them as I was listening to your
Speaker 1: podcast on Augmented Reality my company gout in order for
Speaker 1: parts for an augmented reality system for a car. I
Speaker 1: thought this was really cool, so I thought I would
Speaker 1: shoot you an email your number four hundred sixty third
Speaker 1: fan Chris p S. I'm not sure if I like
Speaker 1: you guys or Josh and Chuck better. That's all right,
Speaker 1: some days I don't know either. Um, that's awesome, Chris.
Speaker 1: And you know, GM just announced an augmented reality windshield project.
Speaker 1: Is pretty darn nifty. Now. We've seen some of this
Speaker 1: in the past already, where we've seen some windshield applications
Speaker 1: for things like night vision and a rear view where
Speaker 1: you you have a little uh cameras showing the rear
Speaker 1: view on the inside of your windshields, so you can
Speaker 1: see what's behind you, um, and stuff like that. Yeah,
Speaker 1: this is this is more of the same, like more
Speaker 1: heads up displays and where you can get real time
Speaker 1: information on the road as you're driving, like GPS stuff
Speaker 1: and things of that nature. Um. I'm really excited about
Speaker 1: this kind of stuff as long as they can present
Speaker 1: it in such a way that does not become a
Speaker 1: distraction to the driver, and that's a big issue these days. Yeah. Yeah,
Speaker 1: it's I mean, anything that keeps takes your eyes off
Speaker 1: the road is always going to be a bit of
Speaker 1: a risk, more than a bit, depending on how fast
Speaker 1: you're going and where you are. But I do think
Speaker 1: it's a pretty exciting application. Um Personally, I'm still waiting
Speaker 1: for the sunglasses that don't weigh like thirty pounds. I
Speaker 1: should jump on that because you could theorectly build a
Speaker 1: pair now, it's just they wouldn't be very light. Thanks
Speaker 1: a lot, Chris. If any of you have any email
Speaker 1: you would like to send us, our address is tech
Speaker 1: stuff at how stuff works dot com. Go to how
Speaker 1: stuff works dot com to learn all about artificial intelligence, robots, computers, processors,
Speaker 1: things like that, and Chris and I will talk to
Speaker 1: you again really soon for more on this and thousands
Speaker 1: of other topics. Does it how stuff works dot com
Speaker 1: and be sure to check out the new tech stuff
Speaker 1: blog now on the house stuff Works homepage, brought to
Speaker 1: you by the reinvented two thousand twelve camera. It's ready,
Speaker 1: are you