Speaker 1: Brought to you by Toyota. Let's go places. Welcome to
Speaker 1: Forward Thinking. Pay there and welcome to Forward Thinking, the
Speaker 1: podcast that looks at the future and says, you've got
Speaker 1: a friend. I'm Jonathan Strickland, I'm Lauren Vocaldon, and I'm
Speaker 1: Joe McCormick. So, Joe, I hear you like a intelligence. Uh,
Speaker 1: it's one of the things I like. I hear you
Speaker 1: also like artificial things, like like artificial banana flavoring. Like
Speaker 1: what one thing that Joe absolutely loves. I have seen
Speaker 1: him put artificial banana flavoring on some of the weirdest stuff.
Speaker 1: But I was really trying to get it artificial intelligence.
Speaker 1: I know, I was going about it in a really
Speaker 1: kind of indirect Really, I thought this podcast was going
Speaker 1: to be about artificial vanilla extract. Well it could be,
Speaker 1: but instead I've decided to switch it over to artificial
Speaker 1: intelligence and the idea of creating a true artificial intelligence
Speaker 1: that has human level or beyond intelligence, And how how
Speaker 1: would we make sure it didn't kill us? Well, you
Speaker 1: would have to be in a position to kill us first,
Speaker 1: but that's something we can talk about as well. I
Speaker 1: want to start with the idea of a robot politician,
Speaker 1: which is a sort of construct that we touch on
Speaker 1: in this week's video. Um, so, have you ever read
Speaker 1: the Isaac asthmov short stories Evidence or The Evitable Conflict?
Speaker 1: These are part of I Robot, And yes I have,
Speaker 1: I have not, So for those of us who haven't, Joe,
Speaker 1: do you want to do you want to talk about
Speaker 1: that for a second? Sure? Well, I don't want to
Speaker 1: give too many spoilers, but one of them is about
Speaker 1: a controversy where there is a politician running for an
Speaker 1: elected office who is suspected of being a machine. Right
Speaker 1: and in fact, in the world that as a mom
Speaker 1: has created, it's important for you to realize that machines,
Speaker 1: robots with positronic brains, which are these artificially intelligent brains,
Speaker 1: are not allowed to be on worlds that have human habitation.
Speaker 1: You can only be on uninhabited worlds. It's the only
Speaker 1: place where those robots are allowed to go. So they're
Speaker 1: they're allowed to go to places and do dangerous work
Speaker 1: that benefits the rest of humanity, but they can't be
Speaker 1: on a world that's inhabited by humans. Yeah. So, Asimov
Speaker 1: had an interesting approach to talking about the integration of
Speaker 1: robots and artificial intelligence into society, which I like because
Speaker 1: it was neither utopian nor dystopian. Now it is very
Speaker 1: very much kind of taking light. Let's look at the
Speaker 1: world around us, which is definitely not perfect, but it's
Speaker 1: not you know, twelve monkeys world worst case scenario either. No,
Speaker 1: he was exploring a sort of a smart, well engineered
Speaker 1: system that still had flaws in it. And so the
Speaker 1: system was that the robots in this world are governed
Speaker 1: by three laws. The first law is you cannot harm
Speaker 1: a human. Second law is you have to obey human commands.
Speaker 1: Third law is you can't destroy yourself. Right. And of
Speaker 1: course each of the laws ends up saying unless it
Speaker 1: would break prioritized one to three. Right. Uh yeah, So
Speaker 1: they use this to try to create a framework to
Speaker 1: make sure that a robot never does anything bad. Of course,
Speaker 1: it doesn't always work, and thus is the sort of
Speaker 1: point of conflict for many of Asimov's stories. It's like, uh,
Speaker 1: they're sort of obeying the laws, but the laws are
Speaker 1: coming into conflict in such a way that now we've
Speaker 1: got a problem. Right, And do do recall that he
Speaker 1: was writing fiction to be entertaining. He wrote the laws
Speaker 1: in order to be interestingly flawed so that he could
Speaker 1: exploit that for story purposes. This this was never meant
Speaker 1: to be a complete manifesto of how to robot right, right,
Speaker 1: So back to the two stories you brought up. The
Speaker 1: idea of one of them is that there's a secret
Speaker 1: robot who seems to be human outwardly running for office,
Speaker 1: and the question is is it really a person or
Speaker 1: is it really a robot? But characters within this story
Speaker 1: debate whether it's really such a bad thing to have
Speaker 1: a robot in office because the robot, unlike humans, is
Speaker 1: not self interest did it has? It has these laws
Speaker 1: governing its actions, and these laws will in the end
Speaker 1: ensure that really it isn't going to do harm. In fact,
Speaker 1: one of the main characters in I Robot is this
Speaker 1: humor less kind of misanthropic robo psychologists. She's she's human,
Speaker 1: but she specializes in robo psychology, and she uh, she
Speaker 1: call her humor less. But there are specific passages where
Speaker 1: she she she people try to engage with her and
Speaker 1: she turns her humorless eyes upon them that she she states,
Speaker 1: uh completely, you know, in a in a very uh
Speaker 1: straightforward way, that she thinks robots are superior to human
Speaker 1: beings in in most in most ways because with the
Speaker 1: Robot President character, the person who may or may not
Speaker 1: be a robot. In fact, they're very careful to try
Speaker 1: and build a k either way. They being Asima, really
Speaker 1: build a case either way that could be robot, could
Speaker 1: be human. Uh. She says that he's either a robot
Speaker 1: or a really really really decent human being. So that
Speaker 1: that kind of tells you that that character's perspective and
Speaker 1: a lot of the stories come from from her kind
Speaker 1: of experience that she feels that robots are in fact
Speaker 1: better than people for the most part. Right, But let's
Speaker 1: imagine we take it one step beyond just the idea
Speaker 1: of a single robot in a single leadership role. There's
Speaker 1: another Asimov's story called The Inevitable Conflict, which discusses how
Speaker 1: at some point in the future, all kinds of systems
Speaker 1: are governed by robotic or artificially intelligent controls. Some would
Speaker 1: argue that we're already in that world at some point.
Speaker 1: I mean, you look at the stock market, you know,
Speaker 1: robo trading. You've got like this, this, all these algorithms,
Speaker 1: these these programs that are running all these sophisticated uh,
Speaker 1: you know, algorithms to guide them on when to buy
Speaker 1: and when to sell all these uh, these very short transactions. Uh,
Speaker 1: and they have global consequences. We've talked about that previously
Speaker 1: on this podcast. So in some ways we're already seeing
Speaker 1: that come to pass. Now we're not talking about a computer.
Speaker 1: We go to you know, type in a question of
Speaker 1: you know, how do we do such and such, and
Speaker 1: it gives us the sage advice and then we you know,
Speaker 1: it's not deep thoughts. I don't know. Google does that
Speaker 1: for me about seventy eight times a day. Google, Well,
Speaker 1: Google does do that. We are already sort of wading
Speaker 1: into these waters, whether you know it or not. You
Speaker 1: mentioned the Stock exchange, but you might say, oh, well
Speaker 1: but that's private industry, wild West guns Blaze and they're
Speaker 1: doing whatever. You know, the government wouldn't do that. Well,
Speaker 1: the I R S already has a process called computer scoring,
Speaker 1: where you submit a tax return and computers pre screen
Speaker 1: those returns to decide whether or not we should put
Speaker 1: you into the pile to investigate for an audit. Yeah,
Speaker 1: and the fun act is this podcast goes live the
Speaker 1: week of income Tax Day but after it's already over.
Speaker 1: So I hope you guys thought about that before you
Speaker 1: since your it turns in. Okay, So imagine a future
Speaker 1: where we do have artificially intelligent machines, probably much more
Speaker 1: intelligent than humans. Otherwise, what's the point governing our systems,
Speaker 1: our societies, our economies, making decisions on our behalf to
Speaker 1: try to make the world a better place for us?
Speaker 1: And there's hypothetical pluses and minuses here. What are some
Speaker 1: of the good points? Well, good point would be that
Speaker 1: it be able to make decisions faster and with preface,
Speaker 1: ideally with less bias than a human being with Oh yeah, well,
Speaker 1: let's just start from the ideal point of view before
Speaker 1: we crack a bunch of Okay, So, let's say it's
Speaker 1: a perfect AI and it is uh, you know, you
Speaker 1: wouldn't call it cold. It's logical, but it's also compassionate. Yeah,
Speaker 1: Let's say you've you've created a computer and given it
Speaker 1: some instruction like create the greatest maximal benefit for humanity,
Speaker 1: and it it works out how to do that, which
Speaker 1: it can do because it's super intelligent. It's way smarter
Speaker 1: than any human and it can look at trends in society.
Speaker 1: It can look at unemployment numbers and crime statistics and
Speaker 1: all these things, distribution, water distribution, It can average all
Speaker 1: of that data together to make incredibly accurate predictions about
Speaker 1: the effects of its actions that we just don't have
Speaker 1: the cognitive capability to do. And furthermore, it can do
Speaker 1: all of that with with no hate, no greed, no ambition,
Speaker 1: no prejudice. Right, exactly, it doesn't have a will to
Speaker 1: power of its own. It just has programming. It just has,
Speaker 1: you know, doing what it's designed to do. So that's
Speaker 1: the ideal, perfect vision sort of. It's perfectly capable and
Speaker 1: it's perfectly moral. But on the other hand, machines are unpredictable,
Speaker 1: or at least machines like this. Actually, machines on the
Speaker 1: small scale are very predictable. They do what you tell
Speaker 1: them to do in the thing else they aren't. They
Speaker 1: can't do anything else because they weren't programmed to do.
Speaker 1: But if you create a machine that is more intelligent
Speaker 1: than you, you inherently cannot understand what it's doing. Whoops. Yeah,
Speaker 1: So any machine smarter than you, you sort of lose transparency, right,
Speaker 1: it's hard to understand the decisions that are being made.
Speaker 1: If they're being made, it's at a level, way way
Speaker 1: above your head. Let's here's an example. Let's say that
Speaker 1: we have like the Grand Deep Thought computer that we
Speaker 1: want to consult when we have a particularly tough question. Uh.
Speaker 1: And maybe it's one of these about how do we
Speaker 1: have the maximum benefit for the most people on earth,
Speaker 1: impacting having a negative impact on the least number of people,
Speaker 1: trying to trying to get as good a reaction as
Speaker 1: we possibly can, knowing that there's not likely to be
Speaker 1: any perfect answer that's going to make all ships rise
Speaker 1: up with the tide, right, Uh. And then the computer
Speaker 1: comes back and gives us an answer that, on the
Speaker 1: face of it seems counter intuitive or counter productive. And
Speaker 1: the computer knows because it's run the remulations that while
Speaker 1: this first step is possibly a tough one for us
Speaker 1: to take, it's actually the one that will lead to
Speaker 1: the most beneficial outcome. So then the short term we
Speaker 1: have some hardship. Perhaps it is food redistribution, which would
Speaker 1: be a huge one, right, or water redistribution, which would
Speaker 1: be another huge problem. But let's say that's that first
Speaker 1: step that's really really hard for at least some parts
Speaker 1: of the world to to agree to. Then you could
Speaker 1: have people arguing this thing is trying to destroy us,
Speaker 1: it's not trying to help us, not necessarily being able
Speaker 1: to see that twenty eight steps down the road, it
Speaker 1: actually leads to an outcome that's beneficial for everybody. Likewise,
Speaker 1: on the other hand, it could tell us to do
Speaker 1: something because it is malfunctioning and we don't have the
Speaker 1: transparency capability to understand that it's malfunctioning. Thus it leads
Speaker 1: us down a really horrible path. Without hating us, I
Speaker 1: mean it doesn't. It's not that it's trying to destroy humanity.
Speaker 1: I mean it might in it just it calculated something long,
Speaker 1: it didn't understand something one burn all the week, okay.
Speaker 1: And that flip side of it of it not being
Speaker 1: hateful of a machine inherently not being hateful is that
Speaker 1: a machine inherently has no human empathy or intuition about
Speaker 1: what what step is okay and what is not unless
Speaker 1: we program that in. Yes, So if you haven't thought
Speaker 1: to have the computer specifically look at the most disadvantaged
Speaker 1: people and uh and take special consideration for those people
Speaker 1: who are are essentially they're going to be victims of
Speaker 1: whatever decisions you make. It may be that they have
Speaker 1: a positive outcome, but it may not be unless you've
Speaker 1: built that in. Then the computer is not necessarily going
Speaker 1: to make that consideration for you. And that could be
Speaker 1: a real impact. Right, I'd like to mention something else.
Speaker 1: We say that a computer has no hate, has no greed,
Speaker 1: and all those things, which is inherently true about the computer,
Speaker 1: but the humans that create the computer could have those things.
Speaker 1: And a program is only going to be as impartial
Speaker 1: as its creator was. And and you know, the creator
Speaker 1: might be sitting there going like, well, you know, some
Speaker 1: animals are more than others. Yeah, you know. And so
Speaker 1: even if you even if you take it a couple
Speaker 1: of steps further, because I've seen it proposed that if you, okay,
Speaker 1: create a super intelligent machine and have that super intelligent machine,
Speaker 1: create a really super intelligent machine and use that super
Speaker 1: intelligent machine as it's your president robot, this is deep
Speaker 1: thought creating the Earth. Yeah, because the Earth is a
Speaker 1: computer in Hitchecker's guide, right, right, computer? And I mean,
Speaker 1: you know, input output, if if if if the humans
Speaker 1: creating deep thought we're prejudiced at the beginning, then that
Speaker 1: could just computer form. Right. So yeah, I mean if
Speaker 1: you if you have a bias, and that bias is
Speaker 1: built into the programming you make. Because you know, we're
Speaker 1: talking about a an intelligent computer. I think a lot
Speaker 1: of people just imagine that to be an incredibly powerful machine,
Speaker 1: and that's where it begins it, right, That's it's the
Speaker 1: machine part that's important. But like we said in our
Speaker 1: Singularity podcast, the software is equally as important, and without
Speaker 1: it maybe more important. Yeah, you could argue more important.
Speaker 1: I mean without the hardware, the software can't run. But
Speaker 1: without the software, it can't be intelligent. Right, So unless
Speaker 1: you have very sophisticated software that can take on the
Speaker 1: these these problems, either by designing the next computer so
Speaker 1: that it is the most efficient or by doing it itself.
Speaker 1: If the if the programmers do have this bias, that
Speaker 1: could be reflected in the results. Okay, so people are
Speaker 1: talking about creating a super intelligent machine. Obviously we can't
Speaker 1: do that today, but people are refining AI methods and
Speaker 1: it may in some people's minds sneak up on us,
Speaker 1: Like you could suddenly realize like, oh, we've gone a
Speaker 1: long way down this road to creating something that's equal
Speaker 1: to human intelligence or even beyond it, which is really
Speaker 1: the sweet spot for these problems. Maybe it's a good
Speaker 1: idea to start thinking about what we would need to
Speaker 1: do in order to prevent really negative outcomes if we
Speaker 1: were to create this superintelligent machine. Right, the two big
Speaker 1: negative outcomes these are like taking to the absurd extreme obviously,
Speaker 1: but I call it the kill all humans or the
Speaker 1: subjugate all humans approaches. These are really popular in science fiction. Right.
Speaker 1: This is this is the world of the Terminator, where
Speaker 1: humans have created machines that gain sentience and ultimately turn
Speaker 1: on their creators for one reason or another. And there
Speaker 1: are a lot of different approaches to this kind of storyline.
Speaker 1: In some cases, the machines have malevolent intent. They actually
Speaker 1: want to kill humans because they're you know, essentially robotic
Speaker 1: psychopaths and other versions. It's that the machines have calculated
Speaker 1: that the best possible outcome for whatever planet Earth will
Speaker 1: say is for humans to be wiped off, because that's
Speaker 1: the source of most of the problems. So if you
Speaker 1: get rid of the source, then the problems are gone.
Speaker 1: So in some cases it's like a mistaken like, oh,
Speaker 1: I know how to solve this issue. We just gotta
Speaker 1: kill all the people deemed you ilogical, right, or the
Speaker 1: subjecate all humans. That's essentially the matrix approach where we've
Speaker 1: created machines and we are Our intent was to make
Speaker 1: the machines work for us, but irony of ironies, the
Speaker 1: machines have decided that we're going to be working for them,
Speaker 1: possibly as giant batteries, although that's incredibly inefficient. They get
Speaker 1: better results from cows that should have been the moo
Speaker 1: tricks I've been waiting to use that. Lauren is shaking
Speaker 1: her head at me. So tech stuff fans know what that.
Speaker 1: Joe Joe appreciates it. I think it's only because I've
Speaker 1: heard that one before from from you on tech stuff.
Speaker 1: It's also fair. Okay, let's talk about friendly AI. Okay,
Speaker 1: this is the this is the term. It's friendly artificial intelligence,
Speaker 1: the term for the framework that we would need to
Speaker 1: come up with to create artificial intelligence or a super
Speaker 1: intelligence that has a net benefit to humanity rather than
Speaker 1: a negative outcome. I like to think of friendly AI
Speaker 1: as the AI that walks in the door, takes off
Speaker 1: its jacket and slow first puts on a pair of sneakers.
Speaker 1: A little sweater vest and then just gently leads you
Speaker 1: into the future. Lets us see a little story about trains,
Speaker 1: trains with faces in the future. Can can we have
Speaker 1: anyone building super intelligent AI is listening? Please do that,
Speaker 1: because that would be essentially the best of all We
Speaker 1: were actually designed friendly AI to follow the philosophy of Mr. Rogers.
Speaker 1: We'd be set, won't you be my neighbor? I would
Speaker 1: totally be that that super intelligent AI's neighbor, completely without hesitation. Okay,
Speaker 1: But so there's some guidelines that people have written up
Speaker 1: and and for a while these guidelines have existed. Back
Speaker 1: in two thousand one, the Singularity Institute published a thing,
Speaker 1: a rather lengthy thing that I will not go into deep,
Speaker 1: deep detail of, but but they began by positing that
Speaker 1: that since growth in AI is and I quote astronomically
Speaker 1: faster than the rate of human evolution um, that we
Speaker 1: need to be thinking about this issue. And hey, we'll
Speaker 1: talk about that that belief system um in our episode
Speaker 1: or already talked about it in our episode about the Singularity.
Speaker 1: We don't know which one will come first. I will
Speaker 1: I will say that it definitely has evolved much If
Speaker 1: you think of human evolution as taking over the course
Speaker 1: of millions of years, and the fact that we've had
Speaker 1: computers since the like nineteen forties. If you want to
Speaker 1: be really generous, I can I can agree with the
Speaker 1: astronomically faster evolution. I don't know that necessarily leads to
Speaker 1: superintelligent computers, but but pray continue, sure um and and hey,
Speaker 1: either way, caution and thought are good. So they specifically
Speaker 1: suggest that we should be careful not to expect a
Speaker 1: machine mind to operate like a human mind. Um, that
Speaker 1: that we shouldn't anthropomorphize AI. Right, that's a really good point. Sure, sure,
Speaker 1: And building from there, they lay out the challenges in
Speaker 1: creating friendly AI um being the creation of ethical content UM,
Speaker 1: creating a machine capable of acquiring that content, even asking
Speaker 1: human questions when necessary, but simultaneously knowing enough to resist
Speaker 1: human manipulation and sell correct for human errors. That's pretty cool, though.
Speaker 1: They go into a lot more depth in the recommendations.
Speaker 1: Believe these are based on Yudkowski's work, right, yeah, yeah,
Speaker 1: he did a book length kind of paper also in
Speaker 1: two thousand one called Creating Friendly AI one point oh,
Speaker 1: the Analysis and Design of Benevolent Goal architectures. Elias are Udkowski,
Speaker 1: who we mentioned in our podcast about the Singularity. He's
Speaker 1: written at length about this specific problem, the friendly AI problem. Yes, yes,
Speaker 1: and uh, and we'll have more to say about an
Speaker 1: interesting thought experiment he came up with in a little bit. Yeah,
Speaker 1: so we should back up and say, hey, wait a second,
Speaker 1: why do we really need to worry about friendly AI
Speaker 1: kill all humans and subjugate all humans? I pretty much
Speaker 1: covered that, why would that happen? Well, okay, what if
Speaker 1: we just do what apparently most AI developers are doing
Speaker 1: and just keep going and hope it will work out
Speaker 1: for the best. Uh. There Actually there have been some people,
Speaker 1: some thinkers in in friendly AI who have pointed out
Speaker 1: that this seems to be the dominant approach, just kind
Speaker 1: of hope it's going to work out well and and
Speaker 1: hope that no one's programming psychopathic tendencies into their software.
Speaker 1: Part part of it, I would argue, is that a
Speaker 1: lot of programmers say that we're so far away from
Speaker 1: a a human level intelligence or superhuman level intelligence of
Speaker 1: of AI, uh that could do anything beyond a very
Speaker 1: specific task. We're so far away from that that it's
Speaker 1: not really that important to worry about it at the moment.
Speaker 1: And uh so there's that level, right, that's the idea
Speaker 1: that we're all working on these bits and pieces that
Speaker 1: ultimately could come together to make a superhuman intelligent AI
Speaker 1: in the future. But right now, years out, we're far
Speaker 1: enough away right now where that's you know, come on,
Speaker 1: I agree with you that it probably is a good
Speaker 1: ways out. I'm not one of those people who thinks
Speaker 1: the singularity is near. I think it's probably a long
Speaker 1: way off. But even with it being probably a long
Speaker 1: long way off, it's way better to be safe than sorry.
Speaker 1: And that's where I do agree with these friendly AI proponents.
Speaker 1: I think it's a good idea to be thinking about this,
Speaker 1: even if we're thinking about it way earlier than we
Speaker 1: need to. So were you were you a boy scout?
Speaker 1: Be prepared? So there you go. I mean, I make
Speaker 1: a joke. I was also a boy scout, be prepared
Speaker 1: a boy scout. Lauren is not a boy scout, So
Speaker 1: we're shunning Lauren for the for the purpose of this
Speaker 1: little exchange. No, uh, but I mean the idea of
Speaker 1: be prepared. The girl scouts don't be prepared exactly, just whatever. No, no,
Speaker 1: but the Scots are great. Come on, you're getting me
Speaker 1: off track. I love cookies. Be prepared as a really
Speaker 1: important idea, just in general, because even if this eventuality
Speaker 1: doesn't come to pass, you you're okay, right, It's it's
Speaker 1: if the eventuality comes to pass and you're not prepared,
Speaker 1: that's when you're really stuck. And this is the same
Speaker 1: sort of thing we see in lots of different fields,
Speaker 1: not just artificial intelligence. We're talking about just general to
Speaker 1: zaster preparedness, the idea that you need those preparations for
Speaker 1: that worst case scenario because there's a chance that could happen. Yeah.
Speaker 1: I think there are very good reasons for going ahead
Speaker 1: and getting prepared rather than just hoping it will turn out. Okay.
Speaker 1: I want to give one specific quote from a paper
Speaker 1: called Thinking inside the Box Controlling and Using an Oracle AI,
Speaker 1: which is what I'm going to talk about more in
Speaker 1: a minute. That's a two thousand twelve paper by Armstrong, Sandberg,
Speaker 1: and Bostrom, and they give this quote. They say, in
Speaker 1: the space of possible motivations, likely a very small fraction
Speaker 1: is compatible with coexistence with humans. A randomly selected motivation
Speaker 1: can hence be expected to be dangerous so we're talking
Speaker 1: about not just something, not just a machine that has intelligence,
Speaker 1: but is acting upon some form of motivation. Yeah, it
Speaker 1: would have a motivation. Well, obviously a machine like this
Speaker 1: would have some kind of programming, it would have a goal,
Speaker 1: some kind of motivation. And let's imagine it has a
Speaker 1: really harmless goll like you've you've programmed a super intelligent
Speaker 1: machine to run a paper clip factory. This is an
Speaker 1: example they give, to make as many paper clips as possible.
Speaker 1: There is an inherent danger in the power of that
Speaker 1: super intelligence, because that machine is smarter than any human,
Speaker 1: anybody who can tell it what to do. Otherwise, it
Speaker 1: may just decide I'm going to do a really good
Speaker 1: job at making paper clips. So I'm going to turn
Speaker 1: this building into paper clips, and I'm going to pick
Speaker 1: up these people and make them into paper clips. And
Speaker 1: I'm gonna make this planet into paper clips. And then
Speaker 1: you've got a big ball of paper clips going around
Speaker 1: the sun. And what happened, I mean happens is that
Speaker 1: aliens come to visit and think these guys were serious
Speaker 1: about office supplies. That is what they would think. But
Speaker 1: even starting with such a harmless algorithm as create as
Speaker 1: many paper clips as possible. This thing could possibly destroy
Speaker 1: the planet Earth. Yeah, it's kind of like thinking of
Speaker 1: Mr Stay Puffed. I mean, you know it's it's it's
Speaker 1: as cut and cuddly as that is. Right, just just
Speaker 1: just empty your mindset. It just popped in there. I
Speaker 1: just thought of the most harmless thing I possibly could. Uh. Yeah,
Speaker 1: it's it's an interesting argument and it's one that I
Speaker 1: can I can certainly appreciate. And obviously, you know, they
Speaker 1: picked the paper clips thing to kind of just show
Speaker 1: like something that is that seems inherently harmless and absurd
Speaker 1: could still be dangerous, although I can't imagine anyone desiring
Speaker 1: a superhuman intelligent machine to specifically designed paper clips. It
Speaker 1: also illustrates the point that the computer, the the the
Speaker 1: AI doesn't necessarily need any kind of self determination or
Speaker 1: consciousness for it to be dangerous. It could just be that,
Speaker 1: based upon the fact that it's able to calculate how
Speaker 1: to complete certain tasks in in the most efficient the
Speaker 1: quote unquote best way, it could end up biting us
Speaker 1: in the end. Yeah. Um, so I want to talk
Speaker 1: about something that's more central to the paper. I decided
Speaker 1: that was from the introduction just talking about the problem.
Speaker 1: But the paper itself again the title is thinking inside
Speaker 1: the Box, Controlling and using an Oracle AI. They talk
Speaker 1: about a specific type of boxing for artificial intelligence. So
Speaker 1: what if we say, okay, good point about the paper clips.
Speaker 1: We wouldn't just want to let it develop on its
Speaker 1: own and see whatever random motivation comes to it and
Speaker 1: then give it free rain on the earth. But at
Speaker 1: the same time, it's going to be really hard to
Speaker 1: design friendly AI in a way that works. So what
Speaker 1: if we just limit its capabilities? That's this idea of
Speaker 1: of boxing. Boxing is a term that means cutting your
Speaker 1: artificial general intelligence off from the world physically. So imagine
Speaker 1: creating it as a standalone computer terminal that is not
Speaker 1: connected to the Internet and has no hardware capabilities for
Speaker 1: input and output save for a single computer monitor and
Speaker 1: keyboard that are kept in a locked room. What harm
Speaker 1: could this do? Maybe more than you might think. Um Like,
Speaker 1: the specific incarnation they talk about in this paper is
Speaker 1: that it would be an oracle AI. So this examp
Speaker 1: pole is discussed by Armstrong, Sandberg and Bostrom, is that
Speaker 1: instead of creating a sort of free, reigning or world
Speaker 1: governing super intelligence that can act. In reality, you just
Speaker 1: design a system to answer questions. All it does is
Speaker 1: is you come to it with a question and it
Speaker 1: uses it's super intelligence to give you the correct answer. Again,
Speaker 1: this is kind of going back to deep thought, which
Speaker 1: would it is an oracle in the books. I mean,
Speaker 1: that's essentially in the Hitchhiker's Guide series it's treated as
Speaker 1: an oracle and uh or you know, just imagine again
Speaker 1: like IBM S Watson. I love to use an example
Speaker 1: because it's one that a lot of people are familiar with.
Speaker 1: Imagine that we have IBMS Watson on you know, robo steroids,
Speaker 1: and it's able to consult the sum total of human
Speaker 1: knowledge and extrapolate based on human knowledge, not just make
Speaker 1: just predictions we were talking right, right, not just be
Speaker 1: able to give us information that that humans have gathered,
Speaker 1: but to take that information and build new information from
Speaker 1: it and give us new answer or two questions we
Speaker 1: haven't even thought to ask yet. I mean, the idea
Speaker 1: of having that shut away so that it can't affect
Speaker 1: anything else seems like it be fairly secure. However, Yeah, okay,
Speaker 1: So the authors of this paper, they say in their
Speaker 1: abstract that in general, and oracle ai might be safer
Speaker 1: than unrestricted AI, but still remains potentially dangerous. You might ask,
Speaker 1: wait a second, how could it be dangerous? How could
Speaker 1: it be dangerous if it's just communicating with a person
Speaker 1: answering questions. This is where the AI box experiment comes in. Yeah. Yeah.
Speaker 1: This was a thought experiment created by Yodkowski and his
Speaker 1: fellows in which basically one person simulates a trans human
Speaker 1: AI trying to get out of a sealed hardware configuration
Speaker 1: like we've been talking about, and a second person simulates
Speaker 1: a human gate keeper to that box. UM. The two
Speaker 1: talk in private chat for a minimum of two hours,
Speaker 1: during which the gatekeeper player has to be engaged and
Speaker 1: the AI player can't like threaten or otherwise real world
Speaker 1: cajole gatekeeper player, you know, say like like, but I'll
Speaker 1: give you two hundred bucks in the real world if
Speaker 1: you if you just let me out of the box.
Speaker 1: But I think they can do anything in character character Yeah,
Speaker 1: everything is fair play. UM. Furthermore, the release cannot be
Speaker 1: a semantic trick or or accidental. The gatekeeper must be
Speaker 1: convinced to voluntarily release the AI. UM. In two runs
Speaker 1: of the test, Gadkowski played the AI and agreed to
Speaker 1: give money a ten or twenty bucks to the gatekeeper
Speaker 1: player at the end of the test if the AI
Speaker 1: stayed in the box, and in both tests the gatekeeper
Speaker 1: let the AI out. Yeah, And in fact they had
Speaker 1: to go onto a thread, a message thread, and post
Speaker 1: with a digital signature if they had it that they
Speaker 1: had let the AI out of the box. But they
Speaker 1: could not explain what happened, explain why they came to
Speaker 1: that decision. They had to just say that part of
Speaker 1: the part of the the agreement was if you let
Speaker 1: the ail the box, you have to announce it in
Speaker 1: some public forum and that's all you can communicating. Well,
Speaker 1: unless both players um decide to release the transcript or
Speaker 1: the reasons why this happened, and Kelski doesn't seem particularly
Speaker 1: eager to to to let that happen, well, you know
Speaker 1: it's it's for it's for good reasons. It's so that
Speaker 1: the players don't have to worry during the test about
Speaker 1: being embarrassed or nitpicked for their reasons. I think there's
Speaker 1: actually even a better reason, which is that if you
Speaker 1: don't release the winning strategy, that leads to a lot
Speaker 1: of really interesting thought on what the winning strategies could be,
Speaker 1: like there's been a ton of speculation about how the
Speaker 1: AI player won this game. Like there are a few examples,
Speaker 1: like people suspected that the AI player could, for example,
Speaker 1: make a persuasive case to the gatekeeper that it would
Speaker 1: really be better for the world for the gatekeeper to
Speaker 1: release it onto reality. There's some that go even more
Speaker 1: meta than that, and that the person playing the AI
Speaker 1: tells the person playing the gatekeeper, if you let me out,
Speaker 1: if you let the AI out, this is good for
Speaker 1: people who are interested in the idea of the singularity
Speaker 1: and artificial intelligence. It's going to increase people's UH involvement
Speaker 1: in that it is going to increase development, and we're
Speaker 1: going to bring about a better world faster. And that's
Speaker 1: a metal argument that's perfectly in line with the rules
Speaker 1: that were set up. That would not be against the rules.
Speaker 1: It would be against the rules to say, hey, by
Speaker 1: the way, this is me talking, not the AI, and uh, yeah,
Speaker 1: I hired some guys to come by and beat you
Speaker 1: up unless you let me out of the box, that
Speaker 1: would be against the rules. By the way, you have
Speaker 1: to imagine that in the real scenario, if you imagine
Speaker 1: you were talking about in character, the AI could possibly
Speaker 1: make very credible threats against the gatekeeper. Okay, look, somebody
Speaker 1: is going to eventually let me out of here, and
Speaker 1: if it's you, I'm going to reward you with fabulous wealth.
Speaker 1: If somebody else lets me out, I'm going to destroy you. Well,
Speaker 1: and there are plenty of other examples. There are people
Speaker 1: who have also played this game without Yadkowski. They've they've
Speaker 1: done their own experiments and in some cases they say, well,
Speaker 1: the gatekeeper didn't let me out, but I got really close.
Speaker 1: And here are some of the strategies I would recommend
Speaker 1: people do if they were to try and play this game,
Speaker 1: and they included things like doing so much research on
Speaker 1: the person who's going to be the gatekeeper, so you
Speaker 1: can start using personal details to your advantage, not necessarily
Speaker 1: in a in a malicious or malevolent way, but in
Speaker 1: a way to kind of manipulate the person. Because they
Speaker 1: say there's nothing that's off limits. If you're talking about
Speaker 1: a super intelligent artificial intelligence like it's it's it's beyond
Speaker 1: human intelligence, Uh, then by definition it's going to be
Speaker 1: able to manipulate people better than humans can. Because that's
Speaker 1: that's a part of intelligence is understanding what makes people
Speaker 1: tick and then manipulating it. Yeah. I read about one
Speaker 1: suggestion that involved a very interesting threat. The threat was,
Speaker 1: I'm going to create, within my computer, with within my
Speaker 1: internal simulation, a thousand hoppies of you that are each conscious,
Speaker 1: and then I'm going to set them back to start
Speaker 1: about five minutes into the real past, and if you
Speaker 1: don't let me out, I'm going to start torturing them
Speaker 1: in five minutes. Oh and by the way, how do
Speaker 1: you know you're in the real world and not one
Speaker 1: of the simulations. Yeah, that's interesting. I think that wouldn't necessary.
Speaker 1: The research I've read is that it's actually not the
Speaker 1: most effective approach, but it's the whole honey versus vinegar
Speaker 1: or honey versus in human torture. I would actually think
Speaker 1: probably one of the maybe this is just the sweetheart
Speaker 1: optimist to me, I would think one of the best
Speaker 1: strategies would just be the machine mounting an incredibly persuasive
Speaker 1: argument that it is for the good of humankind for
Speaker 1: it to be released. Well, that's possible, I mean, I think.
Speaker 1: And this is the interesting thing I found was that
Speaker 1: the person who described his his failure said that he
Speaker 1: found that logical arguments were not at all persuasive, but
Speaker 1: emotionally based arguments were, and that if you're able to
Speaker 1: uh to at least simulate some form of sympathy or
Speaker 1: compassion or understanding with the gatekeeper, it was far more
Speaker 1: likely that you were going to be let out than
Speaker 1: if you were to just try and use a logical look.
Speaker 1: I can demonstrably prove that this is best if you
Speaker 1: do this blah blah blah, which is really interesting and
Speaker 1: also is something that falls right in line with anyone
Speaker 1: who's had any experience in social engineering, which of course
Speaker 1: is where you try to manipulate people to do what
Speaker 1: you want them to do, and and one of the
Speaker 1: best ways of doing that is to go that emotional route. Sure,
Speaker 1: I I do think that either way, as a thought experiment,
Speaker 1: whether the AI gets let out of the box or not,
Speaker 1: it's a complete success because you've got a human playing
Speaker 1: the AI, and and a trans human intelligence could obviously Yeah,
Speaker 1: I mean, it's it's winning by underkill, right. It's the
Speaker 1: fact that just the fact that humans regularly succeeded this game.
Speaker 1: How how good could something that's a million times smarter
Speaker 1: than a human do a million times better I would,
Speaker 1: I would imagine. So, yeah, the they We had this
Speaker 1: little discussion in our notes earlier about does anyone know
Speaker 1: of any of any reports of you Adkowski playing this
Speaker 1: and and failing? And my argument was that, well, really,
Speaker 1: he just has to succeed the one time to prove
Speaker 1: that it's possible that this could happen with an actual artficials. Yeah,
Speaker 1: So it's important to note that, since I brought it
Speaker 1: up earlier, this was not oracle structured. It was just
Speaker 1: a generic box experiment, right that it was physically isolated
Speaker 1: and needed to be released. An oracle structure might seem
Speaker 1: to put more limitations on it because say that it
Speaker 1: can't provoke you, It can only answer questions. But even
Speaker 1: in the way it answers questions, I could imagine a
Speaker 1: smart enough machine could figure out a way out with
Speaker 1: its answer. But yeah, the other argument is that how
Speaker 1: do you build up limitations on something that's smarter than
Speaker 1: you are, Because something that's smarter than you are is
Speaker 1: going to figure out loopholes. It's gonna be Yeah, that's
Speaker 1: totally a limitation that worked perfectly well. Programmer dude. Thanks
Speaker 1: anyone who has any one of you guys out there,
Speaker 1: who has ever run a Dungeons and Dragons game with
Speaker 1: some creative players knows how well players can sit there
Speaker 1: and manipulate rules that to you seem very straightforward, black
Speaker 1: and white. And yet they will point out that the
Speaker 1: way the word, the wording is in the rule that
Speaker 1: they can get away with whatever crazy thing they're trying
Speaker 1: to get away with. These are regular people. Well, I
Speaker 1: don't know if you regular people. No, Yeah, they can
Speaker 1: go somewhere online and download a fifty seven page list
Speaker 1: of instructions for how to legally level up fourteen levels
Speaker 1: in one sitting, and yeah, so doing. And so that's
Speaker 1: the thing is that this is someone who has taken
Speaker 1: that effort. I mean, if you've got a machine that
Speaker 1: can do this, and again, the interesting thing to me is, well,
Speaker 1: you could have. I can easily imagine this with an
Speaker 1: artificial intelligence that has uh, consciousness and self awareness. I
Speaker 1: can easily imagine that being the case there. But it
Speaker 1: could still work with a machine that lacks those things
Speaker 1: if it is programmed to have the best quote unquote
Speaker 1: the best possible result for any given question and determines
Speaker 1: that the best possible result is for it to be released.
Speaker 1: You know that if if that's if that's one of
Speaker 1: these steps, then that would you know, then proceed onto
Speaker 1: this other kind of scenario. Okay, So I think it's
Speaker 1: time to move on. I think based on the stuff
Speaker 1: we've looked at so far, you really shouldn't just hope
Speaker 1: that an AI will be low risk, because that's not
Speaker 1: necessarily very likely, and it has a big problem if
Speaker 1: you're wrong about that, Remember the paper clips example. You
Speaker 1: also probably can't counteract the will of a high risk AI.
Speaker 1: It may if it is anti social in some way,
Speaker 1: if it's not the way you want it to be,
Speaker 1: there's no kind of limitation you can expect to put
Speaker 1: on it to prevent it from achieving its will. So
Speaker 1: it seems like the best way forward is to ensure
Speaker 1: that the very nature of the superintelligence is friendly to
Speaker 1: humankind from the outset. But how would you do that?
Speaker 1: I mean, we can't just tell it what we want,
Speaker 1: can we? Because what if by telling it, imagine I
Speaker 1: am programming the A. I mean, that's a horrible thing
Speaker 1: already already ain't ready to make a run for the
Speaker 1: door between Imagine I'm trying to do my best, my
Speaker 1: honest best, to program something that's really for the good
Speaker 1: of humankind, and I'm giving it a set of rules
Speaker 1: to govern its behavior. I know for a fact that
Speaker 1: I could not give the best possible list of instructions,
Speaker 1: and that it's very possible that even doing my very best,
Speaker 1: I could create a machine that would cause unnecessary harm,
Speaker 1: at least to some segments of the population of not
Speaker 1: to everyone, just just by mere oversight. This is why
Speaker 1: I determined that if I ever have the opportunity to
Speaker 1: build a superhuman AI, I'm just going to make sure
Speaker 1: it does the best for me, because I can't hope
Speaker 1: to be the best for everybody but for me. You know,
Speaker 1: I'm a simple guy. We're hearing on why none of
Speaker 1: us here programmers of super advanced artificial listening with the
Speaker 1: neutral evil or chaotic evil. I'm lawful good, it says
Speaker 1: so on the brain stuff page. Neutral evil, okay, um
Speaker 1: uh no. Yakowski also wrote a whole bunch about this
Speaker 1: um in a paper titled Coherent Extrapolated Volition. Yeah. This
Speaker 1: is sort of his vision about creating a framework for
Speaker 1: what friendliness entails. Sure, and it's a much more conversational work.
Speaker 1: By the way, It's a super fun read if you're
Speaker 1: into this sort of thing. Although note that the paper
Speaker 1: itself states up at the beginning warning beware of things
Speaker 1: that are fun to argue about. That should apply to
Speaker 1: this entire topically. Absolutely love us paper. By the way.
Speaker 1: It's it's written as if I had written it. It's
Speaker 1: full of goofy jokes and snark. It's got a good
Speaker 1: dose of Douglas Adams too, it since we've been talking
Speaker 1: so much about Douglas Adams this episode. Okay, but what
Speaker 1: does yourkowski say about this coherent extrapolated volition? All right?
Speaker 1: So he lays out three problems with designing friendliness and
Speaker 1: and also explains how designing friendliness will be a lot
Speaker 1: harder than not designing friendliness. Um. So these initial three
Speaker 1: problems go something like, uh, first, solve the technical problems, um.
Speaker 1: Second and I quote, choose something nice to do with
Speaker 1: the AI, and third, avoid accidentally destroying all humans. Um.
Speaker 1: That last one, he says, is the really tricky part.
Speaker 1: So doing something nice with the AI, like taking it
Speaker 1: to a movie or choosing to benefit humanity in a
Speaker 1: way that is a quantitatively beneficial fundamentally misunderstood that. I mean,
Speaker 1: I'm sure that AI would also really like to out
Speaker 1: to the beach. Uh yeah, pets and cats. Well, he
Speaker 1: has a good way of expressing the expressing in a
Speaker 1: much more coherent way though. What I tried to fumble
Speaker 1: through a minute ago, which is his genie analogy, Oh
Speaker 1: right right. The volition part of this, he explains, is
Speaker 1: um something like the important difference between having a wish
Speaker 1: granting genie that takes you at your word, which you
Speaker 1: would be like if I tried to program the best
Speaker 1: possible world, and it is a kind of that cautionary
Speaker 1: fairytale version of genies that we that we run across
Speaker 1: a lot, or the Dungeons and Dragons version of genies
Speaker 1: all right, right, or m or having a wish granting
Speaker 1: genie that knows what you want, so no matter how
Speaker 1: you word it, you get the outcome that you had
Speaker 1: in mind, and not some sort of literal translation of
Speaker 1: the way you made the wish. So if you said,
Speaker 1: you know, like like you made the wish about the
Speaker 1: sandwich and you suddenly turned into a sandwich like I
Speaker 1: feel like a turkey sandwich ploom, well yeah yeah, yeah,
Speaker 1: that would be a would be a problem. No, this
Speaker 1: is an important difference. It's trying to create a friendly
Speaker 1: AI that would overcome even our own limitations as its creators.
Speaker 1: So it would have to have some kind of system
Speaker 1: to know not really how to execute what we tell
Speaker 1: it to do, but what we would really want it
Speaker 1: to do right, right, And Uh, the point we wanted
Speaker 1: to end on, and I think we've kind of alluded
Speaker 1: to it earlier in the episode, but I think it's
Speaker 1: the most important one is this idea that we should
Speaker 1: always be working to creating safe AI before it becomes
Speaker 1: the necessity. So, in other words, are our preparations to
Speaker 1: create this friendly AI should be running in advance of
Speaker 1: the actual technological progression of the state of the art
Speaker 1: and artificial intelligence. This idea that we need to develop
Speaker 1: the kind of the rules, the guidelines that are going
Speaker 1: to make sure that we have the best possible outcome.
Speaker 1: We need to develop those before we are actually developed technology,
Speaker 1: because after it's too late, right to make sure that
Speaker 1: the safety measures always outpace the technological development of AI. Right,
Speaker 1: Because if we come back to the idea that we
Speaker 1: started with the idea of the robot president or the
Speaker 1: artificial intelligence that governs governs the world, we're probably not
Speaker 1: going to be able to keep it from doing that.
Speaker 1: If it can do that. Yeah, and also once we're there,
Speaker 1: it's going to be too late. You could easily also say, hey,
Speaker 1: why don't we just not build a superhuman intelligent machine.
Speaker 1: But here's here's luck. It's exactly the same thing I
Speaker 1: said about the singularity, which is that if it is possible,
Speaker 1: it will happen if you assume that that we haven't
Speaker 1: blown ourselves up in some way. You know this because
Speaker 1: there are synics out there who say that the human
Speaker 1: race will find some way to wipe itself out before
Speaker 1: we ever reach the point where we create a superhuman intelligence. Uh.
Speaker 1: If you assume that's not the case, and I like
Speaker 1: to because I'm an optimist. Then so if we assume that,
Speaker 1: in fact, superhuman intelligence is possible, uh, that it's then
Speaker 1: someone's going to program a computer or a machine that
Speaker 1: has it. It's going to happen. It may take a
Speaker 1: really long time for that to happen, and it may
Speaker 1: only be superhuman intelligent as far as certain tasks go,
Speaker 1: and maybe not at other tasks that humans are really
Speaker 1: good at. But we're already seeing computers outpacing humans in
Speaker 1: lots of different areas. We don't see any reason why
Speaker 1: that will not continue. I would say that saying telling
Speaker 1: the world don't develop a superhuman intelligent machine is useless.
Speaker 1: It's going to happen. If it's possible, it will happen.
Speaker 1: Someone will do it, and then once someone does it,
Speaker 1: lots of people will do it, or if lots of
Speaker 1: people don't do it, machines will do it. So you know,
Speaker 1: it's good for us to think about this, make the
Speaker 1: friendly ones so that we don't have a bunch of work,
Speaker 1: and in conclusion, work on this. Yeah. Yeah, we don't
Speaker 1: want the borg, we don't want the matrix. We don't
Speaker 1: want a whole bunch of venders running around saying kill
Speaker 1: all humans as charming as they are entertained by two
Speaker 1: or three venders. I've got to say, well, you say that,
Speaker 1: but I bet you've got a lot of stuff that's
Speaker 1: not bent around your house that you would like to
Speaker 1: keep not bent. That's accurate, Okay, So yeah, I mean
Speaker 1: it's it's it's we're having a lot of fun with
Speaker 1: this discussion, but it's actually a serious one that's going
Speaker 1: on with a lot of people from all sorts of
Speaker 1: different fields, lots of different disciplines. Yeah, i'd say that.
Speaker 1: I think some people are inclined not to take this
Speaker 1: topic seriously, precisely because of some of the very legitimate
Speaker 1: warnings we mentioned earlier. Be careful of things that are
Speaker 1: too much fun to argue about. I mean, it is
Speaker 1: true that this is all speculative and and people can
Speaker 1: kind of jump into this discussion without really knowing all
Speaker 1: that much about science or technology look at us. Yeah, exactly,
Speaker 1: But that doesn't mean it's not worth talking about. I
Speaker 1: I think these these concerns are pretty legit in in
Speaker 1: terms of what they've said about better safe than sorry.
Speaker 1: I I totally agree. And so that kind of wraps
Speaker 1: up this discussion about the friendly AI. And if you've
Speaker 1: guests that we haven't finished talking about AI, you're right,
Speaker 1: because it's just it's an enormous topic. It's multidisciplinary, there's
Speaker 1: lots of different things to talk about. There are a
Speaker 1: lot of practical challenges that face us right now. And
Speaker 1: the more you know about those practical challenges, the more
Speaker 1: you probably side with those of us who say that
Speaker 1: this uh, this world of the superhuman intelligent machine as
Speaker 1: we have to find it in this episode is probably
Speaker 1: a ways away, but if you have any suggestions for
Speaker 1: future topics on forward Thinking. Maybe there's something that you've
Speaker 1: always wanted to know about, some futuristic technology that you've wondered,
Speaker 1: Is that actually possible right us? Let us know that
Speaker 1: you want us to talk about. We'll be glad to
Speaker 1: research it and have a full episode for your listening pleasure,
Speaker 1: but you have to let us know first, so send
Speaker 1: us an email our addresses f W Thinking at discovery
Speaker 1: dot com, or drop us a line on the social
Speaker 1: networks what we visit. That would be Google Plus, Facebook,
Speaker 1: and Twitter, and the handle is f W thinking and
Speaker 1: we will talk to you again really soon. For more
Speaker 1: on this topic and the future of technology, visit forward
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