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Speaker 1: Welcome to Stuff to Blow your Mind from how Stuff

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Speaker 1: Works dot com. Hey, welcome to Stuff to Blow your Mind.

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Speaker 1: My name is Robert Lamb and I'm Julie Douglas. And

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Speaker 1: as of this recording, the robots singularity has probably not occurred.

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Speaker 1: Mm hmmm as far as we know. As far as

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Speaker 1: we know, but we're not really sure how to define that, right, right,

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Speaker 1: It's kind of an evasive term. I mean, roughly, we're

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Speaker 1: talking about computers robots reaching the level where they not

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Speaker 1: only um um meet us on the same mental plane,

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Speaker 1: but they exceed us and they become greater than us,

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Speaker 1: and they and then in various scenarios could conceivably play out,

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Speaker 1: people really like to have fun with fun with the

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Speaker 1: darker images, they just leave us in the dust, like literally, yeah,

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Speaker 1: like they just they take over the world, or they

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Speaker 1: just decided to destroy all humans, or or our lives

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Speaker 1: become so robotic and so enhanced by robotics that that

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Speaker 1: the the human part of our life becomes kind of

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Speaker 1: a kind of a core to it. You know, it's

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Speaker 1: just but not a necessity of it. Well, I think

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Speaker 1: I love talking about the singularity because it does um,

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Speaker 1: it brings up so many different points of view, and

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Speaker 1: you and I have talked about it plenty and always

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Speaker 1: feel like you have like this very um positive outlook

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Speaker 1: on the Singularity, whereas sometimes I get paranoid and I think,

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Speaker 1: oh no, to be taken over says when you don't

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Speaker 1: even come into work and we have to call and

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Speaker 1: se who we are because it's the Singularity and anxiety

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Speaker 1: is getting taking over. Yes, those are the days when

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Speaker 1: I've locked myself in my bunker. Yeah. Whereas I tend

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Speaker 1: to look at it like, you know, if the if

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Speaker 1: the coffee machines become as smart as humans, then we're

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Speaker 1: just gonna have a really great coffee. I mean, that's sea.

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Speaker 1: I love that that that's the sort of positive pluck

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Speaker 1: that I'm talking about here. Um, But in that context,

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Speaker 1: you know, it does it seems Michael, Okay, this is

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Speaker 1: something that could be far away, or it could be

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Speaker 1: something that's really near. We don't know, but robots are

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Speaker 1: having a fundamental impact on our lives in myriad ways, right. Yeah.

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Speaker 1: I remember I was looking into some information about recruiting

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Speaker 1: into computing programs and they pointed out that there's virtually

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Speaker 1: no field of study anymore that does not contain programming

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Speaker 1: and uh and computerization, and it's going to get to

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Speaker 1: where there's going to be no part of of our

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Speaker 1: society that isn't touched by robotics in some way, shape

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Speaker 1: or form robotics or you know, or or really high

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Speaker 1: end programming or us even being touched by robots, right,

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Speaker 1: I mean we've talked about Roxy the sex Spot literally

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Speaker 1: touched by it. Well, I don't know if the robots

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Speaker 1: doing in this situation, the robots is being touched, I think, Oh,

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Speaker 1: but they are, I'm sure are very soon there will

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Speaker 1: be touching. Yeah, but it's very hard to argue this

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Speaker 1: consensual that's true unless it's programmed. I supposed Yeah, that's

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Speaker 1: a whole party. Um, And we will get to that definitely.

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Speaker 1: But again, thinking about robots and how they're being used

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Speaker 1: in day to day life, we actually turn to Dr

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Speaker 1: Ronald Arkin. He's the Regent's Professor in the School of

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Speaker 1: Interactive Computing and is the director of the Mobile Robot

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Speaker 1: Laboratory at the Georgia Institute Technology. Yeah, it's not a

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Speaker 1: mobile lab though. It doesn't you know, it's not like

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Speaker 1: it doesn't break away from the rest of the building

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Speaker 1: or anything. And uh, galvanting around Atlanta. No, No, but

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Speaker 1: he and his team, along with research engineer Alan Wagner,

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Speaker 1: they've blazed the way when it comes to robotics and

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Speaker 1: in particular thinking about robotic ethics, and they have created

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Speaker 1: a robot or robots that can deceive. Yeah, And it

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Speaker 1: all boils down to an algorithm, or more specifically a

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Speaker 1: cognitive deception modeling algorithm or or a series of algorithms,

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Speaker 1: and it involves not not only only giving the robot

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Speaker 1: the capacity to fool another robot or a human, but

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Speaker 1: giving it the ability to decide when to fool another human.

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Speaker 1: Because that's the important thing. We all have the ability

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Speaker 1: as humans. We all have the ability to see the

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Speaker 1: ability to lie. And one of the the the the

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Speaker 1: core things we have to decide in life is when

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Speaker 1: to tell the truth and when to lie. And if

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Speaker 1: it's if you're out of balance on that, life can

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Speaker 1: get pretty messy and nobody will want to hang out

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Speaker 1: with you either because you've never um, you never code

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Speaker 1: anything um for consumption, you never you know, dish out

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Speaker 1: a white liar two, or you just lie all the

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Speaker 1: time and are kind of a jerk. Yeah. Yeah, So

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Speaker 1: I mean we wouldn't want to create jerk robots. But

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Speaker 1: the problem is that that robots in their simple form

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Speaker 1: are they're they're robotic, they're they're they're they're not gonna

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Speaker 1: they're not gonna code anything um to make it go

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Speaker 1: down easier. Yeah. Yeah, So it is really interesting, like

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Speaker 1: how do you how do you do this? How do

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Speaker 1: you what? What is deception? Anyway, even when when you're

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Speaker 1: talking about a robot And so we actually talked to

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Speaker 1: Dr Arkin about this, and this is what he had

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Speaker 1: to say about deception and what it is defined as

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Speaker 1: in robotics. It's actually a definition that we borrowed from

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Speaker 1: cognitive science, which is a false communication that tends to

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Speaker 1: benefit the communicator. So the important thing is that you

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Speaker 1: will benefit by saying something that is untrue. Now in

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Speaker 1: the process has often been referred to as lying robots

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Speaker 1: and the like as well too. It's a false communication.

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Speaker 1: Is lying leaving a trail on the ground. I don't know,

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Speaker 1: that's a verbal act. I could argue this is more

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Speaker 1: expansive than simply lying. In this case, it's basically trying

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Speaker 1: to create a deception to make someone believe something that

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Speaker 1: isn't true and act in a way. The work that

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Speaker 1: we looked at in the military. For the military was

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Speaker 1: more a fundamental question of what deception is and how

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Speaker 1: it could be employed. So it's not soly writing up

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Speaker 1: look up tables and saying these are the sets of actions,

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Speaker 1: as I think I mentioned. If I didn't, there's an

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Speaker 1: entire field manual for the U. S. Army on deception

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Speaker 1: deceptive techniques, because it's important, it's crucially important in an

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Speaker 1: appropriate way to conduct warfare. Uh. But this isn't just

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Speaker 1: saying do this in this set of circumstances, do this

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Speaker 1: in this set of circumstances. This is I have to

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Speaker 1: understand you. I have speaking as a Roman. I have

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Speaker 1: to understand you and learn what your potential outcomes are.

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Speaker 1: And one of the other interesting factors in that paper,

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Speaker 1: which I was about to mention as well too, is

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Speaker 1: that it was observed, at least in this narrow case

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Speaker 1: that we studied, the more sensors that you have, the

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Speaker 1: more the easier it is to deceive you, which it

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Speaker 1: was not intuitively obvious. You think, gosh, you know, if

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Speaker 1: I have more ways to understand what's around me, I

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Speaker 1: would be more likely to get the right action. But

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Speaker 1: deception works in this particular, it appears due to the

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Speaker 1: fact that we can exploit multiple channels of information. You know, um,

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Speaker 1: hearing that, I can't help but be reminded of Isaac Asimov.

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Speaker 1: He of course had the classic book I Robot, which

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Speaker 1: is a series of short stories about about robots, and

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Speaker 1: they're very they're very analytical. They're all about, you know,

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Speaker 1: robots of being the three rules of robotics, and humans

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Speaker 1: trying to figure out how the robots are are are behaving.

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Speaker 1: And there's a story in there called Little Lost Robot.

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Speaker 1: And and in this a researcher loses his temper and

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Speaker 1: swears that a particular robot and tells it to get lost,

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Speaker 1: and it does so, and then the chief robo psychologist, Dr.

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Speaker 1: Susan Calvin comes in to find it. Um, So it

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Speaker 1: couldn't help it be reminded of that. It's a fairly

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Speaker 1: lighthearted tale. Yeah. Actually, that's that's interesting because just in

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Speaker 1: in the context of the experiment that Arkin and Wagner did,

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Speaker 1: they used interdependence theory and game theory to develop the

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Speaker 1: algorithms that tested the value of deception in a specific situation,

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Speaker 1: and the situation had to satisfy two key conditions. To

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Speaker 1: warrant deception. There has to be a conflict between the

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Speaker 1: deceiving robot and the seeker, and the deceiver must benefit

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Speaker 1: from the deception. So we're talking about here, is like

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Speaker 1: an elaborate hide and seek game or not so elaborate,

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Speaker 1: essentially um to test or algorithms. They ran twenty hide

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Speaker 1: and seek experiments with two autonomous robots, and they had

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Speaker 1: colored markers which they lined up along three potential pathways

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Speaker 1: to locations where the robot could hide. And so the

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Speaker 1: hider robot randomly selected a hiding location from the three

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Speaker 1: location choices and then moved toward that location, knocking down

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Speaker 1: colored markers along the way. So once it reached a

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Speaker 1: point past the markers, the robot change course and then

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Speaker 1: hid in one of the other two locations, and the

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Speaker 1: presence or the absence of standing markers indicated the hyder's

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Speaker 1: location to the seeker robot. Okay, well this is this

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Speaker 1: is like a very basic form of deception. Uh. We

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Speaker 1: see this in movies all the time where the hero

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Speaker 1: is running through an office building trying to escape somebody.

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Speaker 1: So what does he do? He runs? He or she

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Speaker 1: runs to this door at the end of the hallway,

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Speaker 1: opens it real wide, let's it shut, but then goes

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Speaker 1: off in another direction. The guys they're chasing him work

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Speaker 1: hows come around the corner and see the door slamming.

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Speaker 1: They're like, ah, they went that way, chase them. Or

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Speaker 1: it's like if you if you're in the forest and

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Speaker 1: you you're making your way past these branches, if you

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Speaker 1: started snapping branches along one direction and then backtracked and

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Speaker 1: went somewhere else to and then that your pursuers would

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Speaker 1: come through and they'd say, well, look, clearly they went

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Speaker 1: this way because this is where the branches are snapped off. Right, right,

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Speaker 1: It seems basic, right, I mean, and it is and

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Speaker 1: um in the sense the physical sense that we think of,

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Speaker 1: But think about all of that information, all that data

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Speaker 1: that you have to absorb, and then the choices that

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Speaker 1: you have to make on that that we take that

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Speaker 1: for granted right with our brains, but trying to program

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Speaker 1: program that in a robot is particularly interesting and quite

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Speaker 1: a challenge. And so what seems rudimentary now and is

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Speaker 1: rudimentary in terms of robotic we know, will become much

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Speaker 1: more nuanced later on. And so that's why a lot

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Speaker 1: of people are looking at this deception, even if it

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Speaker 1: is on this level sort of hide and seek level,

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Speaker 1: and saying wow, okay, you can do that in robots.

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Speaker 1: Now what what is that going to look like in

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Speaker 1: five years? And so um ar can actually talked a

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Speaker 1: little bit about the attention the experiment received in that

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Speaker 1: regard and how programming a robot to deceive is really

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Speaker 1: similar to thinking like a con man a significant amount

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Speaker 1: of press. I guess it's the best way to put

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Speaker 1: an attention is another way to put it, which I

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Speaker 1: would contend is probably somewhat disproportionate to the results that

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Speaker 1: we obtained, but it's it is a controversial piece of work. Nonetheless,

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Speaker 1: it was the first in depth study of the phenomena

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Speaker 1: of robot deception and the ability of a robot to

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Speaker 1: deceive other robots or potentially human beings as well. UH

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Speaker 1: and we look very closely at interdependent theory, a cognitive

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Speaker 1: science model as well as game theory as the basis

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Speaker 1: for understanding two things about robotic deception. The first is

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Speaker 1: when is it appropriate to deceive? Because you don't want

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Speaker 1: a robot to be deceiving people all the time, else

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Speaker 1: it would not have any value and we were typically

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Speaker 1: looking at in this early work or would'll all call

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Speaker 1: one shot deception trying to deceive someone just once that's

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Speaker 1: good enough, kind of like a conman. The second is

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Speaker 1: how to be able to accomplish that, And I could

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Speaker 1: talk a little bit more in depth about those, but

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Speaker 1: I should say that much of the work that was

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Speaker 1: based on some of Alan's earlier work on trust, because

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Speaker 1: as any good command knows, a precursor to deception is

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Speaker 1: the establishment of trust. But we were interested in that

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Speaker 1: particular case of learning how a robot could trust a

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Speaker 1: human being, rather than the classic case for man machine systems,

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Speaker 1: how can a human learn to trust a robot? There

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Speaker 1: are many instances such as UH nine eleven, for example,

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Speaker 1: when people act in ways that are improper to say

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Speaker 1: the least, and automation should be able to override them

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Speaker 1: when they are doing that. Machines should know when not

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Speaker 1: to trust the human being. And using the same kind

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Speaker 1: of models and the same kind of situational analysis, but

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Speaker 1: now looking at ways in which we could induce the observer,

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Speaker 1: which will call the mark in this particular case, which

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Speaker 1: is the language you would use in this UH, that

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Speaker 1: we could induce a outcome belief in the mark that

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Speaker 1: in action they would take would be more beneficial to

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Speaker 1: them then would be if they took another action, But

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Speaker 1: it actually ends up being more beneficial to the robot

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Speaker 1: in this particular case is the UH strategy that we

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Speaker 1: used to address the how imagine a military situation and

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Speaker 1: the robot has valuable information or in and of itself,

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Speaker 1: it's a valuable resource and does not want to be

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Speaker 1: captured or reverse engineered or whatever the case may be. Now, granted,

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Speaker 1: you could put self destruction capabilities in it, so it

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Speaker 1: would not be the case, but that destroys the asset

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Speaker 1: that you would want to preserve, and it may have

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Speaker 1: valuable information of its own in its own right. Uh. Strangely,

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Speaker 1: are are two D two and the original Star Wars

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Speaker 1: comes to mind. You know, get this to Obi wan Kenobi.

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Speaker 1: That wasn't our motivation? Um so what not just playing

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Speaker 1: hide and seek in the sense of some other folks

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Speaker 1: have done this with robots. Is robot finds a good

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Speaker 1: place to hide and hopes for the best. But in

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Speaker 1: this case, the robot models the pursuer using a very

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Speaker 1: crude version of what's called theory of mind, tries to

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Speaker 1: establish what would the pursuer do in these particular sets

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Speaker 1: of circumstances and leaves a as a consequence of that

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Speaker 1: leaves a false trail. It's kind of like uh, putting

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Speaker 1: mud down or tracks down and saying I'm over here,

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Speaker 1: but then backtracking and hiding in a different location. So

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Speaker 1: it is the belief that the robots belief that if

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Speaker 1: the pursuer sees that trail, the pursuer will move in

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Speaker 1: that direction. And if that is indeed the case, the

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Speaker 1: robot highs and some other location, the pursuer goes down

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Speaker 1: that trail and then the robot can escape after that.

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Speaker 1: So that's the notional aspect in that particular case. So

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Speaker 1: in a way, we're kind of talking about robot original

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Speaker 1: sin here. You know, up until this point, they've we've

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Speaker 1: just had robots doing what the programmed to do. And

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Speaker 1: if they say an industrial robot just you know potent, say,

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Speaker 1: you know, welds a man's face off, it's not doing

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Speaker 1: that with any intent to weld someone's face off. But

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Speaker 1: but in this scenario, we're we're creating a robot that

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Speaker 1: can lie and and I find it really interesting that

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Speaker 1: it's you know, we're talking about a very simple form

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Speaker 1: of lying, a very simple form of deception that will

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Speaker 1: grow into more complicated forms of behay. Here, it's it's

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Speaker 1: kind of like looking at, say the first time, like

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Speaker 1: a child lies, or even just how lies themselves have

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Speaker 1: the tendency to start very small and then and then,

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Speaker 1: if unresolved, to grow and grow and grow and to

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Speaker 1: become this greater, more complicated and complex thing. Yeah, it is,

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Speaker 1: but when you think about lies, you also know that there's, uh,

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Speaker 1: there's another side to it. That lives can be really helpful,

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Speaker 1: right they can. Actually we do it for many reasons.

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Speaker 1: But sometimes we do it to spare people's feelings, or

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Speaker 1: there might be a dangerous situation and you need to

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Speaker 1: lie about something. I don't know. Paramedics arrive on a

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Speaker 1: scene the you know, the guy asked, K, doc, am

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Speaker 1: I gonna make it that the duck's not gonna say maybe,

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Speaker 1: or you know, the duck's gonna say hanging there. We

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Speaker 1: can make it right, right, So, I mean, they're essential

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Speaker 1: to our own existence, and they're certainly essential to warfare.

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Speaker 1: And so that's when you look at something like these

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Speaker 1: what they're being called the septicons, these deceiving robots UM

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Speaker 1: that they could actually be very useful in search and

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Speaker 1: rescue mission UM. And of course there's the idea that

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Speaker 1: they could be more fully engaged in battle. But of

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Speaker 1: course the challenge is to be able to give robots

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Speaker 1: the ability to judge a situation, act accordingly and as

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Speaker 1: ethically as possible. So again that's that's where these um,

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Speaker 1: these sort of uncomfortable bits of information start to butt

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Speaker 1: up against each other because it's like, here, on the

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Speaker 1: one hand, we have this great technology that can do this.

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Speaker 1: On the other hand, you know, it's you know, work humans,

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Speaker 1: and we know that we are programmed not necessarily to

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Speaker 1: be the most altruistic beings. UM, So how can we

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Speaker 1: create something that's not necessarily in our image, but it's

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Speaker 1: better than us. H. It's an interesting proposition. So there's

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Speaker 1: a good scenario of of that sort of judgment center

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Speaker 1: that we have that we're trying to actually finance, hopefully

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Speaker 1: UH in robots. And the scenario at a robotic level

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Speaker 1: is UM what Arkin is talking about when he talks

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Speaker 1: about instilling in robins a more sophisticated He wants a

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Speaker 1: way to assess the situation and act accordingly. UH. This

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Speaker 1: is from a New York Times article. It's called a

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Speaker 1: soldier taking orders from its ethical judgment center. Uh. They

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Speaker 1: talked to Dr Arkin about this computer model, and it's

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Speaker 1: a robot pilot who flies past a cemetery in spots

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Speaker 1: a tank at the entrance, and this is the target

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Speaker 1: in this scenario. But there's a group of civilians in

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Speaker 1: this computer model, and they're gather that the cemetery and

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Speaker 1: the robot pilot considers the data and decides to keep going.

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Speaker 1: But soon it spots another tank out in the field

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Speaker 1: all alone, and it decides to fire on it. So again,

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Speaker 1: here are these different models that scientists and researchers are

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Speaker 1: trying to put together in order to you know, assemble

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Speaker 1: this sort of judgment center for robots themselves. Uh. And

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Speaker 1: there's obvious limitations to the technology right now as it stands.

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Speaker 1: This presentation is brought to you by Intel sponsors of tomorrow.

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Speaker 1: But there's the possibility that machines could one day assess

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Speaker 1: situations with the advantage of not engaging in our something

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Speaker 1: like our own confirmation by us, you know, where we

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Speaker 1: sort of perpetuate information that's faulty information because we wanted

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Speaker 1: to fit with our worldview. Um, and then also we

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Speaker 1: get impassioned about things, right, We don't always think clearly,

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Speaker 1: particularly in cases of war. Right. Yeah, So we taught

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Speaker 1: to Arkin, and we wanted to to find out why

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Speaker 1: people might be frightened of this part, this proposition where

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Speaker 1: we might have a technology that could essentially help us

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Speaker 1: one day to make better choices in in the war.

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Speaker 1: But also you know why we might be a little

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Speaker 1: bit freaked out by that. Well, I mean, the basic

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Speaker 1: prospect is making war easier to wait, like easier to

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Speaker 1: decide to wage war. I mean, that's one of the

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Speaker 1: big arguments against robotic warfare is that it becomes if

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Speaker 1: there are no human if there are fewer human lives

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Speaker 1: on on our side on the line, and fewer chances

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Speaker 1: of there being some sort of a horrible headline grabbing

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Speaker 1: scenario in terms of enemy casualties, then why not declare

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Speaker 1: war right over any little thing, over energy crisis, you

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Speaker 1: need some oil, Just declare war because the robots. You're

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Speaker 1: not gonna lose anybody. You're not gonna have grieving families

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Speaker 1: voting uh, voting against you in an upcoming election. And

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Speaker 1: if your robots can, you know, are really good at

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Speaker 1: at not um causing a whole bunch of civilian deaths.

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Speaker 1: Then uh, it's more surgical and strategic. Ah see. And

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Speaker 1: this this is what is so interesting that Arcan has

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Speaker 1: to say about this UM, particularly when you talk about

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Speaker 1: protocols of war UM. And this is what he has

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Speaker 1: to say about it. Well, we need to talk about it.

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Speaker 1: Is the most important thing is I've offered said that

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Speaker 1: the research I have done in that particular space UM

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Speaker 1: is one aspect, But the discussion that that research engenders

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Speaker 1: is as important as the research itself, at least to me.

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Speaker 1: And as such, I spent a lot of time talking

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Speaker 1: about it, not only to the media, but also at

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Speaker 1: military bases, at philosophy conferences, at the International Committee of the

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Speaker 1: the Red Cross where they developed the Geneva Conventions just

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Speaker 1: last month, a variety of different locations, ethics groups and

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Speaker 1: the like as well too too answer that very question.

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Speaker 1: So it would be really presumptuous at me to say, uh,

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Speaker 1: this is perfectly safe, don't worry about it, or the

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Speaker 1: sky is falling. The sky is falling, like some of

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Speaker 1: my colleagues are doing as well too. Uh. What I

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Speaker 1: do say is that if we are going to allow

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Speaker 1: these robots to make these life or death situations decisions.

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Speaker 1: If we're going to allow these robots to make these

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Speaker 1: life or death decisions on their own to some to rate,

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Speaker 1: I mean, they're not just going to go out and

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Speaker 1: start looking at someone and say should I go that individual.

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Speaker 1: They will be tasked by a human being in a

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Speaker 1: mission context and then make that particular decision. But if

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Speaker 1: we're going to do that, we need to understand what

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Speaker 1: it is that we're doing, what if any bounds are appropriate,

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Speaker 1: And from my perspective, if we're going to do that,

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Speaker 1: they must adhere to the existing laws of war and

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Speaker 1: the rules of engagement, as we as a society already do.

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Speaker 1: And so that's what my work is about. I have

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Speaker 1: often said that while I do believe that we can

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Speaker 1: actually do better than human beings in these situations, that

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Speaker 1: if it ended up that intelligent lethal robots were banned

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Speaker 1: from the battlefield, I'm not adverse to that, although I

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Speaker 1: still do believe that we can actually do better than

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Speaker 1: human beings and making the right decisions regarding lethal application

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Speaker 1: of force under certain circumstances. And it's really important to

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Speaker 1: understand that I am not talking about placing a soldier

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Speaker 1: with a robot. I'm talking about augmenting soldiers with robots

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Speaker 1: and using them in highly specialized missions such as building

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Speaker 1: clearing operations, counter sniper operations, things of that particular sort,

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Speaker 1: which is quite different than saying, uh, here's a terminator, uh,

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Speaker 1: and uh that's going to replace that particular soldier. Very

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Speaker 1: narrow well defined situations where something called bounded morality applies.

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Speaker 1: And that's what makes attractable, because human morality is extremely complex,

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Speaker 1: involving multiple brain systems and other aspects of that. Machine

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Speaker 1: learning deliberation, all sorts of things could be brought to

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Speaker 1: bear in applying it in that context. But what's interesting

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Speaker 1: is the lethal application of force is relatively low hanging

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Speaker 1: fruit for a person dealing with computational morality for a

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Speaker 1: couple of reasons. The primary one is that philosophers have

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Speaker 1: been thinking about it for thousands of years, under what

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Speaker 1: circumstances is it appropriate to kill someone? And we have

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Speaker 1: as a civilization, a Western civilization, uh codified the laws

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Speaker 1: of war through the Hague and Geneva Conventions and others

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Speaker 1: as well too, and said when you kill someone, this

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Speaker 1: is how you do it, and this is what you

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Speaker 1: don't do. And we tell our soldiers we don't hand

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Speaker 1: them a rifle and say figure out what the morality

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Speaker 1: is in the battlefield and say go and uh conduct

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Speaker 1: your mission. We train them and we say this is

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Speaker 1: what you do and this is what you don't do.

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Speaker 1: I also want to preface this. I have the utmost

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Speaker 1: respect for our war fighters are young men and women

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Speaker 1: in the battlefield. It's crucially important that that be understood.

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Speaker 1: But human beings, not all, but many perform outside the

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Speaker 1: bounds of what is prescribed due to reasons such as frustration, anger, fear.

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Speaker 1: Uh send a real fulfillment, which is what you were

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Speaker 1: talking about earlier, where you might believe something is going

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Speaker 1: to occur and then discard new incoming evidence of cognitive phenomena.

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Speaker 1: So how how we cope with all these different kinds

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Speaker 1: of things leads to in certain cases the Commission of

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Speaker 1: war crimes. And if you look at the Surgeon General's

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Speaker 1: report which came out in two thousand six of fire

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Speaker 1: member correctly in studying the data of the self reported

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Speaker 1: data from the soldiers in Operation Iraqi Freedom or I

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Speaker 1: think that was the one racky freedom um. The numbers

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Speaker 1: are staggering in terms of what was believed to be

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Speaker 1: unethical behavior, in terms of the performance, their inability to

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Speaker 1: report on unethical actions of their colleagues, their inability to

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Speaker 1: distinguish between insurgents and severe almost considered you're either UH

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00:25:05,119 --> 00:25:08,720
Speaker 1: an enemy or you're not uh and UH. There was

431
00:25:08,720 --> 00:25:11,359
Speaker 1: nothing in between in that case. So they didn't understand

432
00:25:11,359 --> 00:25:15,800
Speaker 1: the notion of noncombatants considered non combatants insurgents under the

433
00:25:15,800 --> 00:25:18,239
Speaker 1: success and the data went on or not, which was

434
00:25:18,560 --> 00:25:20,440
Speaker 1: that was mind blowing if you want to talk about that,

435
00:25:20,480 --> 00:25:23,400
Speaker 1: at least to me in terms of the potential room

436
00:25:23,440 --> 00:25:26,119
Speaker 1: for improvement. So he makes a really interesting case in

437
00:25:26,160 --> 00:25:30,000
Speaker 1: developing the technology, but stuffing back from it in saying

438
00:25:30,040 --> 00:25:32,160
Speaker 1: that you were at a point in history we can

439
00:25:32,200 --> 00:25:36,200
Speaker 1: actually look at it and say, you know, ethically, should

440
00:25:36,200 --> 00:25:39,679
Speaker 1: we do this, should we consider the following things? Um?

441
00:25:39,720 --> 00:25:43,280
Speaker 1: And I think that that's that's interesting because in science

442
00:25:43,320 --> 00:25:47,520
Speaker 1: we've always sort of rushed forward, right historically, because we've

443
00:25:47,520 --> 00:25:49,960
Speaker 1: been really excited about what we could make, what we

444
00:25:50,000 --> 00:25:53,119
Speaker 1: could create, what we could do, and then after the

445
00:25:53,160 --> 00:25:55,879
Speaker 1: facts step back and went, WHOA, you know, maybe maybe

446
00:25:56,280 --> 00:26:00,240
Speaker 1: this was misused or this this was a misused application. Right,

447
00:26:00,400 --> 00:26:04,280
Speaker 1: So I think it's really heartening that he is UM

448
00:26:04,320 --> 00:26:07,399
Speaker 1: someone who's at the forefront of the ethics and is

449
00:26:07,480 --> 00:26:10,560
Speaker 1: really trying to tell people like, you know, let's let's

450
00:26:10,560 --> 00:26:12,760
Speaker 1: think about this, let's be smart about this. Yeah, and

451
00:26:12,880 --> 00:26:15,760
Speaker 1: especially in informing the people that are in the position

452
00:26:15,800 --> 00:26:20,240
Speaker 1: to make decisions, who are many times a pretty pretty

453
00:26:20,320 --> 00:26:24,680
Speaker 1: big distance away from from actual understanding of of what's

454
00:26:24,680 --> 00:26:28,480
Speaker 1: possible and what's not possible in computing in robotics. So

455
00:26:28,920 --> 00:26:31,000
Speaker 1: you don't want somebody that's, you know, some politician that's

456
00:26:31,040 --> 00:26:33,520
Speaker 1: far removed from it saying, yeah, robot soldiers, that sounds great,

457
00:26:33,760 --> 00:26:36,720
Speaker 1: We're not gonna have so many soldiers die. Cool, let's

458
00:26:36,720 --> 00:26:39,159
Speaker 1: do that. But the need that, but they need to

459
00:26:39,240 --> 00:26:42,440
Speaker 1: understand on some level that what the what's at stake

460
00:26:42,600 --> 00:26:45,639
Speaker 1: ethically and what the ethical arguments are. Yeah. And what

461
00:26:45,760 --> 00:26:48,960
Speaker 1: ar Can also had pointed out to UM when he

462
00:26:48,960 --> 00:26:52,280
Speaker 1: and I talked to is that the lawmakers most of

463
00:26:52,320 --> 00:26:57,080
Speaker 1: the time aren't even really aware of what's available technologically

464
00:26:57,200 --> 00:27:00,080
Speaker 1: out there. So a lot of this is trying to

465
00:27:00,320 --> 00:27:05,159
Speaker 1: UM educate the public and policymakers and make them aware

466
00:27:05,200 --> 00:27:08,560
Speaker 1: so that they can understand what's at stake. So it's

467
00:27:08,640 --> 00:27:12,400
Speaker 1: very interesting and I have to say that again, You've

468
00:27:12,400 --> 00:27:15,440
Speaker 1: always taken attack of being more positive when it comes

469
00:27:15,480 --> 00:27:18,640
Speaker 1: to singularity, and I've always kind of been, uh, they're

470
00:27:18,640 --> 00:27:21,480
Speaker 1: going to take us over. Um, you know, I have

471
00:27:21,600 --> 00:27:24,720
Speaker 1: my days. But in talking to ark And, I thought

472
00:27:24,720 --> 00:27:29,000
Speaker 1: that he had a really interesting perspective on that as well. Um,

473
00:27:29,040 --> 00:27:33,000
Speaker 1: and something that he talks about robots in the context

474
00:27:33,080 --> 00:27:38,120
Speaker 1: of them filling an ecological niche for us. So let's

475
00:27:38,160 --> 00:27:43,280
Speaker 1: listen to this bit of information about the technological singularity,

476
00:27:43,480 --> 00:27:48,919
Speaker 1: and they lay definition is referred to as they point

477
00:27:48,960 --> 00:27:55,240
Speaker 1: where machine intelligence exceeds human intelligence? Are we there already

478
00:27:55,280 --> 00:27:57,879
Speaker 1: lots of one? And Jeffard right, so, uh, you know

479
00:27:57,920 --> 00:28:00,239
Speaker 1: it's a question of how you define these things. Uh

480
00:28:01,200 --> 00:28:05,560
Speaker 1: as well, at some levels we're already there. So is

481
00:28:05,600 --> 00:28:07,200
Speaker 1: it when we have data? You know? I don't. I

482
00:28:07,240 --> 00:28:11,600
Speaker 1: don't even understand exactly what the singularity is, um. And

483
00:28:13,560 --> 00:28:15,919
Speaker 1: I do believe the machines will get smarter and smarter.

484
00:28:16,359 --> 00:28:18,760
Speaker 1: I actually don't believe they necessarily should be compared to

485
00:28:18,840 --> 00:28:22,560
Speaker 1: human intelligence. I think robotic intelligence, just as dog intelligence

486
00:28:22,640 --> 00:28:26,720
Speaker 1: and ape intelligence and intelligence, is different than human intelligence.

487
00:28:26,760 --> 00:28:29,840
Speaker 1: I believe that robotic intelligence will be something, if allowed

488
00:28:29,880 --> 00:28:32,399
Speaker 1: to be instead of forced into the human paradigm, something

489
00:28:32,840 --> 00:28:37,560
Speaker 1: different than human intelligence, and they feel what are referred

490
00:28:37,560 --> 00:28:40,760
Speaker 1: to as ecological niches, places within the world where they

491
00:28:40,760 --> 00:28:43,560
Speaker 1: can survive and prosper and grow. And why on Earth

492
00:28:43,560 --> 00:28:45,480
Speaker 1: would we want or in space for that matter, where

493
00:28:45,480 --> 00:28:47,800
Speaker 1: I anywhere would we want to create something that is

494
00:28:48,120 --> 00:28:51,160
Speaker 1: completely and utterly competing with us in the same ecological

495
00:28:51,240 --> 00:28:53,640
Speaker 1: niche that can lead to extinction in that case where

496
00:28:53,640 --> 00:28:56,120
Speaker 1: you will be displaced. I don't think that's the Wines

497
00:28:56,160 --> 00:28:59,880
Speaker 1: idea personally, but that doesn't mean we shouldn't do robotics.

498
00:28:59,880 --> 00:29:02,640
Speaker 1: We just need to do the right kind whatever that

499
00:29:03,280 --> 00:29:07,640
Speaker 1: happens to be. We can't all go off in to

500
00:29:07,800 --> 00:29:11,640
Speaker 1: our corner, raise our flag and say yes, yes, no,

501
00:29:11,760 --> 00:29:14,240
Speaker 1: no uh. We have to talk with each other and

502
00:29:14,360 --> 00:29:17,080
Speaker 1: understand and by each other. I don't mean a bunch

503
00:29:17,120 --> 00:29:21,080
Speaker 1: of roboticist, I mean policymakers. I mean roboticists, I mean

504
00:29:21,120 --> 00:29:25,560
Speaker 1: the military, I mean civilian populations, I mean theologians. I

505
00:29:25,560 --> 00:29:29,040
Speaker 1: mean stakeholders, is what they're referred to. All the stakeholders

506
00:29:29,040 --> 00:29:33,240
Speaker 1: have to get together and come to grips with what

507
00:29:33,280 --> 00:29:37,360
Speaker 1: it is that we're creating and start to think, first

508
00:29:37,400 --> 00:29:40,800
Speaker 1: of all, what needs to be regulated, and once that

509
00:29:40,960 --> 00:29:44,640
Speaker 1: is determined, how much regulation is appropriate under these sets

510
00:29:44,640 --> 00:29:47,280
Speaker 1: of circumstances. And this is an ongoing process. It's not

511
00:29:48,120 --> 00:29:49,960
Speaker 1: going to be a set of commandments. It says this

512
00:29:50,040 --> 00:29:51,440
Speaker 1: is it, this is the way it will always be.

513
00:29:51,760 --> 00:29:53,520
Speaker 1: It's a living documents in the right and some of

514
00:29:53,520 --> 00:29:56,200
Speaker 1: my colleagues are doing that in other spaces as well.

515
00:29:56,240 --> 00:30:01,240
Speaker 1: But I've been very pleased with attraction that robot ethics

516
00:30:01,520 --> 00:30:06,080
Speaker 1: is beginning to get uh. It was it felt a

517
00:30:06,080 --> 00:30:07,960
Speaker 1: little bit of times in the early days of a

518
00:30:08,080 --> 00:30:12,440
Speaker 1: voice crying in the wilderness, but more and more people

519
00:30:12,960 --> 00:30:16,719
Speaker 1: are getting involved. There's a new special issue on robot

520
00:30:16,720 --> 00:30:20,120
Speaker 1: ethics coming out in the elect Tripoli magazine and Robotics

521
00:30:20,200 --> 00:30:23,880
Speaker 1: and Automation. So I see many of my colleagues starting

522
00:30:24,240 --> 00:30:27,600
Speaker 1: to say things about it and to take it seriously

523
00:30:27,680 --> 00:30:30,520
Speaker 1: and to speak their minds as to what they think

524
00:30:30,600 --> 00:30:34,120
Speaker 1: is right as opposed to what I as a scientist

525
00:30:34,240 --> 00:30:37,160
Speaker 1: myself when I was a bench chemist, or whether I

526
00:30:37,280 --> 00:30:42,520
Speaker 1: was a roboticist. We're driven purely by curiosity driven research

527
00:30:42,640 --> 00:30:45,720
Speaker 1: where we just want to understand something, whether it's a

528
00:30:46,240 --> 00:30:50,800
Speaker 1: how to make a better UH molecule, or whether it's

529
00:30:50,800 --> 00:30:53,960
Speaker 1: how to understand that principles of intelligence and view them

530
00:30:53,960 --> 00:31:00,240
Speaker 1: in the machine. Concurrently, we need to understand how what

531
00:31:00,400 --> 00:31:04,960
Speaker 1: the consequences of that are. That is uh, and once

532
00:31:05,040 --> 00:31:09,040
Speaker 1: we do that, I think we can truly call ourselves

533
00:31:09,080 --> 00:31:11,800
Speaker 1: responsible scientists. Okay, so how do you feel about that?

534
00:31:11,920 --> 00:31:14,360
Speaker 1: To make you feel a little easier about the robots

535
00:31:15,160 --> 00:31:19,200
Speaker 1: gaining power? Or or yeah, actually did it made me

536
00:31:19,680 --> 00:31:23,120
Speaker 1: understand it more in the context of Okay, well, you know,

537
00:31:23,760 --> 00:31:26,400
Speaker 1: it would be really and we've said this before, really

538
00:31:26,400 --> 00:31:28,719
Speaker 1: stupid for us to create something that destroys us. But

539
00:31:28,760 --> 00:31:34,520
Speaker 1: I mean it's not. It's not. Yeah, yeah, we could

540
00:31:34,520 --> 00:31:37,880
Speaker 1: do it. But knowing that the discussion is going on

541
00:31:38,200 --> 00:31:44,360
Speaker 1: and hearing or can talk about um robots really enhancing

542
00:31:44,520 --> 00:31:48,560
Speaker 1: our intelligence or even making us rethink or intelligence is

543
00:31:48,720 --> 00:31:52,000
Speaker 1: for me sort of a paradigm shift, and that you know,

544
00:31:52,480 --> 00:31:56,560
Speaker 1: humans don't become the other, um, but the other in

545
00:31:56,600 --> 00:31:59,000
Speaker 1: the sense that you know, this is perhaps some sort

546
00:31:59,000 --> 00:32:02,920
Speaker 1: of technology that can continue to help us evolve, not

547
00:32:02,960 --> 00:32:06,800
Speaker 1: necessarily be trampled upon and then become human servants to

548
00:32:06,880 --> 00:32:11,040
Speaker 1: our robot overlords. Yeah, I guess, I guess people fear

549
00:32:11,080 --> 00:32:14,640
Speaker 1: it in a way. It reminds me when I when

550
00:32:14,640 --> 00:32:16,600
Speaker 1: as a kid and used to live in in Tennessee,

551
00:32:16,680 --> 00:32:18,920
Speaker 1: and there was this, um, there's this trailer. We would

552
00:32:18,960 --> 00:32:21,040
Speaker 1: drive by, and it started as a single trailer, and

553
00:32:21,040 --> 00:32:22,720
Speaker 1: then they built onto the side of it like a

554
00:32:22,720 --> 00:32:24,440
Speaker 1: big room here in a big room there, and then

555
00:32:24,480 --> 00:32:26,440
Speaker 1: there was there was more and more, until you couldn't

556
00:32:26,440 --> 00:32:28,960
Speaker 1: see the trailer anymore. And then one day they pulled

557
00:32:28,960 --> 00:32:31,320
Speaker 1: the trailer out of the middle of it and uh,

558
00:32:31,320 --> 00:32:34,120
Speaker 1: and I guess filled it in uh and just made

559
00:32:34,120 --> 00:32:37,920
Speaker 1: it a house. So I guess one could fear what

560
00:32:37,960 --> 00:32:40,560
Speaker 1: if we were the trailer in this scenario where we

561
00:32:40,760 --> 00:32:45,120
Speaker 1: continually augment human life and the human experience and in

562
00:32:45,160 --> 00:32:48,840
Speaker 1: our an entire culture here on Earth and beyond, and

563
00:32:48,880 --> 00:32:51,560
Speaker 1: then we reached the point to where the trailer is

564
00:32:51,560 --> 00:32:55,000
Speaker 1: no longer necessary part of the equation. But I'm not

565
00:32:55,040 --> 00:32:57,600
Speaker 1: saying I share that idea, but I like that idea.

566
00:32:57,640 --> 00:32:59,160
Speaker 1: I thought you were going to start off with some

567
00:32:59,320 --> 00:33:02,480
Speaker 1: sort of boo rat lay story there as as perhaps

568
00:33:02,840 --> 00:33:06,120
Speaker 1: embodying the the robot, and we just didn't know the

569
00:33:06,200 --> 00:33:09,280
Speaker 1: robots well enough yet. You know, No, growing up, we

570
00:33:09,320 --> 00:33:13,400
Speaker 1: did have the town robot, but it was largely um.

571
00:33:13,840 --> 00:33:16,080
Speaker 1: It's its main duties were just cleaning the streets and

572
00:33:16,560 --> 00:33:19,360
Speaker 1: apprehending straight criminals. You know, I see, but I mean

573
00:33:19,360 --> 00:33:24,040
Speaker 1: that's everybody's small town experience, of course. Yeah's Paris, Texas

574
00:33:24,280 --> 00:33:29,680
Speaker 1: best robots ever. Um, Well, this was really interesting to

575
00:33:29,680 --> 00:33:32,320
Speaker 1: to talk to Dr Arkin, and we actually have a

576
00:33:32,320 --> 00:33:36,840
Speaker 1: lot of other information, um that he shared with us

577
00:33:37,000 --> 00:33:40,520
Speaker 1: so very generously. He talks about robot ethics in the

578
00:33:40,560 --> 00:33:43,240
Speaker 1: context of the class that he teaches, which is Robots

579
00:33:43,240 --> 00:33:46,800
Speaker 1: in Society, and he talks UM with his students about

580
00:33:46,920 --> 00:33:51,480
Speaker 1: human students, his human students, about actual human relations with robots,

581
00:33:51,560 --> 00:33:54,960
Speaker 1: which we've talked about before, sex with spots. Um. That's

582
00:33:54,960 --> 00:33:59,280
Speaker 1: not his entire class, um. There are many other ethical

583
00:34:00,200 --> 00:34:03,360
Speaker 1: situations that he talks about, but we will definitely do

584
00:34:03,440 --> 00:34:06,320
Speaker 1: some follow up with Dr Arkin and some other topics.

585
00:34:06,400 --> 00:34:08,920
Speaker 1: It was really fascinating to to learn more about what

586
00:34:08,960 --> 00:34:12,479
Speaker 1: he's doing here in Atlanta at Georgia Tech, and we'd

587
00:34:12,520 --> 00:34:14,160
Speaker 1: like to thank him for taking the time to speak

588
00:34:14,200 --> 00:34:16,439
Speaker 1: with us. UM. And just so you know a little

589
00:34:16,480 --> 00:34:19,160
Speaker 1: bit more about Dr Arkan, he served as a founding

590
00:34:19,200 --> 00:34:22,840
Speaker 1: co chair of the Triple E Robotics and Automation Society

591
00:34:23,360 --> 00:34:27,120
Speaker 1: Technical Committee on Robotic Ethics from two thousand four and

592
00:34:27,120 --> 00:34:29,640
Speaker 1: two nine and is the co chair of the Society's

593
00:34:29,680 --> 00:34:33,480
Speaker 1: Human Rights and Ethics Committee, as well as the Triple

594
00:34:33,640 --> 00:34:37,000
Speaker 1: E r a s Liaison to the Society on Social

595
00:34:37,000 --> 00:34:41,080
Speaker 1: Implications of Technology. Well, hey, we have some listener mail,

596
00:34:42,120 --> 00:34:44,120
Speaker 1: so I think I'm gonna jump into that. Um. Of

597
00:34:44,160 --> 00:34:46,440
Speaker 1: all the bits that I have here are actually a

598
00:34:46,440 --> 00:34:50,120
Speaker 1: follow up to our Pope on a Cosmic Rope episode, Yes,

599
00:34:50,400 --> 00:34:54,200
Speaker 1: which we received a number of comments about UM and

600
00:34:54,360 --> 00:34:55,879
Speaker 1: UH and seemed to get a lot of people thinking.

601
00:34:55,880 --> 00:34:58,319
Speaker 1: And oddly enough, I don't think we received any hate

602
00:34:58,320 --> 00:35:00,680
Speaker 1: mail over that. I mean, not that actually that we

603
00:35:00,680 --> 00:35:03,160
Speaker 1: were fishing for it, but no, I mean, yeah, after all,

604
00:35:03,200 --> 00:35:05,120
Speaker 1: we did sort of hint that they might be wearing

605
00:35:05,440 --> 00:35:08,759
Speaker 1: skinny jeans under their vestments. Yes, but sure someone would

606
00:35:08,760 --> 00:35:11,000
Speaker 1: strike out at us against that. But you know, but

607
00:35:11,280 --> 00:35:14,640
Speaker 1: you know, I think, you know, obviously, people people of

608
00:35:14,719 --> 00:35:16,480
Speaker 1: faith have a sense of humor and uh, and we

609
00:35:16,480 --> 00:35:18,480
Speaker 1: actually I heard from a few of them here as

610
00:35:18,520 --> 00:35:22,319
Speaker 1: well as UH. One person who just has a reading recommendation.

611
00:35:22,640 --> 00:35:25,920
Speaker 1: Our listener, Albert writes in and says, enjoyed your podcast.

612
00:35:25,920 --> 00:35:29,440
Speaker 1: I was reminded of a book by Maria Doria Russell.

613
00:35:29,800 --> 00:35:33,600
Speaker 1: The Sparrow, which fits into your theme space exploration funded

614
00:35:33,600 --> 00:35:37,080
Speaker 1: by the Vatican, encounters Aliens. That's a bare bones description.

615
00:35:37,160 --> 00:35:40,520
Speaker 1: It's dark and deals with complex, they logical issues. That

616
00:35:40,560 --> 00:35:42,040
Speaker 1: sounds good, all right, I may have to add that

617
00:35:42,120 --> 00:35:46,799
Speaker 1: to the list of things to read. The next one

618
00:35:46,880 --> 00:35:50,880
Speaker 1: comes from Matthew Um who is a scientist from New Jersey,

619
00:35:51,360 --> 00:35:53,799
Speaker 1: and Matthew writes to Robert and Juley. A great fan

620
00:35:53,840 --> 00:35:55,680
Speaker 1: of the podcast, but when I heard your pope on

621
00:35:55,719 --> 00:35:58,800
Speaker 1: a cosmic rope, I cringed a little on your idea

622
00:35:58,840 --> 00:36:01,759
Speaker 1: of the Catholic Church. The Catholic Church is not a democracy,

623
00:36:02,160 --> 00:36:05,440
Speaker 1: so what's popular or in style doesn't change the doctrines.

624
00:36:05,560 --> 00:36:08,720
Speaker 1: I can assure you. No great principles get changed without

625
00:36:08,760 --> 00:36:12,520
Speaker 1: careful religious deliberations. And in fact, extraterrestrial life has never

626
00:36:12,600 --> 00:36:16,719
Speaker 1: been contradictory to Catholicism. Thanks for reading my input and

627
00:36:16,800 --> 00:36:20,680
Speaker 1: keep up the good work. All right. Well cool, what, Robert,

628
00:36:20,680 --> 00:36:22,719
Speaker 1: you haven't said a thing about the hair shirt that

629
00:36:22,760 --> 00:36:27,040
Speaker 1: I'm wearing. Oh well, if go ahead and talk about

630
00:36:27,040 --> 00:36:29,920
Speaker 1: the hair shirt. I had been just being polited about it. Well,

631
00:36:29,960 --> 00:36:31,799
Speaker 1: I know, and I thank you for that. You're very

632
00:36:31,800 --> 00:36:34,839
Speaker 1: sensitive but um, it is probably the second or third

633
00:36:34,880 --> 00:36:37,040
Speaker 1: time I've been wearing this hair shirt. But now I'm

634
00:36:37,040 --> 00:36:41,040
Speaker 1: wearing it because I believe that it was me who

635
00:36:41,080 --> 00:36:46,840
Speaker 1: called the clostridium officially a virus when it is indeed bacteria.

636
00:36:47,360 --> 00:36:52,200
Speaker 1: Did the bacteria itself right in it? Did it'? I

637
00:36:52,280 --> 00:36:55,440
Speaker 1: know that's awful when the actual bacteria writes in and

638
00:36:55,480 --> 00:36:59,239
Speaker 1: says I am no virus um, and I would like

639
00:36:59,320 --> 00:37:01,720
Speaker 1: for you to go ahead and and make the world

640
00:37:01,880 --> 00:37:05,359
Speaker 1: know that that's the case. And so I apologize to deff.

641
00:37:06,920 --> 00:37:10,719
Speaker 1: All right, Well, hopefully that will that will appease any uh,

642
00:37:11,280 --> 00:37:14,880
Speaker 1: both virus and bacteria that are listening to us. Uh.

643
00:37:15,000 --> 00:37:17,720
Speaker 1: One more bit of listener mail, this one from listener

644
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Speaker 1: um Ophelia from Devon, United Kingdom. Uh. Where I think

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00:37:22,320 --> 00:37:25,040
Speaker 1: I've actually been. Um, it's like I think it's on

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00:37:25,080 --> 00:37:29,120
Speaker 1: the on one of the canals or something. Yeah. Anyway,

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Speaker 1: if it's the talent I thinking about, it's really really

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Speaker 1: cool little town. Anyway, She writes in and says, I

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Speaker 1: really enjoyed your podcast on the relationship between science and

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Speaker 1: the Catholic Church. I've wondered since I was a little

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00:37:39,280 --> 00:37:41,560
Speaker 1: kid what Catholics would do if aliens were discovered, so

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Speaker 1: I really got to kick out of the topic. I'man

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00:37:43,360 --> 00:37:46,719
Speaker 1: about Catholic studying archaeology, so the conflict between the Church

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00:37:46,760 --> 00:37:49,960
Speaker 1: and science is an important one to me, especially concerning evolution.

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00:37:50,680 --> 00:37:53,480
Speaker 1: It's really encouraging to hear about people like Guy counsil

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00:37:53,520 --> 00:37:57,799
Speaker 1: Mango who are passionate about both religion and science. And

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00:37:57,840 --> 00:38:00,839
Speaker 1: what he said about fundamentalist was excellent and act. While

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00:38:00,960 --> 00:38:02,640
Speaker 1: they have certainly been that way in the past, the

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00:38:02,680 --> 00:38:04,880
Speaker 1: modern Catholic Church is not nearly so harsh about its

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00:38:04,960 --> 00:38:06,960
Speaker 1: views as a lot of people seem to think. They

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Speaker 1: have been okay with and even encouraged the old stem

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00:38:09,120 --> 00:38:11,600
Speaker 1: cell research for many years, and Pope on Paul's second

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00:38:11,840 --> 00:38:15,920
Speaker 1: published an encyclical stating that much of evolution area theory

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Speaker 1: is not indirect contradiction with the views of the Church.

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Speaker 1: So I'm really glad to hear that the Church has

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Speaker 1: been making efforts to make their views better known. I

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00:38:22,800 --> 00:38:24,960
Speaker 1: hope they continue with this because it would make me

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00:38:25,040 --> 00:38:28,239
Speaker 1: feel much more confident in being a Catholic archaeologist. Keep

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Speaker 1: going with the great podcasts. I always enjoy them when

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00:38:30,480 --> 00:38:32,200
Speaker 1: I'm taking a break from work or going to bed.

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00:38:32,600 --> 00:38:34,919
Speaker 1: And I like how I get to learn something new

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Speaker 1: even when I'm relaxing. Cheers, cheers to you, Ohilia, thank

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00:38:39,080 --> 00:38:41,799
Speaker 1: you for writing. Yes. And if anybody else out there

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Speaker 1: has stuff you want to share with us, I encourage

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00:38:44,120 --> 00:38:46,879
Speaker 1: you to visit Facebook and Twitter. We're blow the Mind

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00:38:46,920 --> 00:38:51,360
Speaker 1: on both of those. Uh, find us on Facebook, push

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00:38:51,440 --> 00:38:54,120
Speaker 1: like to join us, follow us, and so who we're

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00:38:54,160 --> 00:38:57,600
Speaker 1: up to. And on Twitter, I encourage you to share

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00:38:57,640 --> 00:39:00,320
Speaker 1: a cool links that you may find are cool acts

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00:39:00,360 --> 00:39:03,319
Speaker 1: that that worm their way into your life by just

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00:39:03,360 --> 00:39:06,320
Speaker 1: throwing it up on Twitter with the hashtag blew my mind.

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00:39:06,440 --> 00:39:10,600
Speaker 1: One word the hashtag hash blew my mind and uh,

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00:39:10,640 --> 00:39:12,200
Speaker 1: and then we'll see it and we'll get to share

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00:39:12,239 --> 00:39:14,360
Speaker 1: it and uh, because I think that's a hashtag we

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00:39:14,400 --> 00:39:17,879
Speaker 1: really can reclaim as listeners. That's right. We can find

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Speaker 1: some very cool mind blowing stuff to share with each other.

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00:39:21,520 --> 00:39:23,719
Speaker 1: And if you would like to share some other mind

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00:39:23,719 --> 00:39:26,000
Speaker 1: blowing stuff with us, you can always do so via

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00:39:26,160 --> 00:39:33,400
Speaker 1: email at Blow the Mind at how stuff works dot com.

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Speaker 1: For more on this and thousands of other topics, visit

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Speaker 1: how stuff works dot com. To learn more about the podcast,

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Speaker 1: click on the podcast icon in the upper right corner.

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