1 00:00:01,560 --> 00:00:04,760 Speaker 1: Welcome to Stuff from the Science Lab from how stuff 2 00:00:04,760 --> 00:00:16,400 Speaker 1: works dot com. Hey guys, this is Alice not Am 3 00:00:16,560 --> 00:00:18,400 Speaker 1: with the science editor at how stuff works dot com. 4 00:00:18,560 --> 00:00:21,079 Speaker 1: This is Robert Lamb's science writer at how stuff works 5 00:00:21,079 --> 00:00:26,480 Speaker 1: dot com. And uh, this podcast, we're talking about robots 6 00:00:26,720 --> 00:00:29,560 Speaker 1: and then they're not there alive? Yeah, big question? Are 7 00:00:29,800 --> 00:00:32,239 Speaker 1: robots alive? So you just got into this question when 8 00:00:32,280 --> 00:00:36,160 Speaker 1: you wrote the similarly named article for Discovery News, right, Yes, yeah, 9 00:00:36,159 --> 00:00:39,000 Speaker 1: we've been doing a bunch of these big questions for 10 00:00:39,080 --> 00:00:42,040 Speaker 1: Discovery News. Um, and we've been doing some big questions 11 00:00:42,040 --> 00:00:44,520 Speaker 1: for How stuff Works as well. Just you know, our 12 00:00:44,640 --> 00:00:49,120 Speaker 1: robots alive? Um. You know what are some other ones 13 00:00:49,360 --> 00:00:52,199 Speaker 1: Strickland wrote about it too. Yeah, Strickland wrote one about 14 00:00:53,040 --> 00:00:56,680 Speaker 1: robot consciousness and all, and it's a very related issue. 15 00:00:56,680 --> 00:00:58,720 Speaker 1: We're not going to get in as much into consciousness, 16 00:00:59,000 --> 00:01:03,040 Speaker 1: but deal more of with definitions of life and how 17 00:01:03,200 --> 00:01:07,160 Speaker 1: robots may or may not meet that criteria. Yes, I 18 00:01:07,200 --> 00:01:09,080 Speaker 1: believe it or not, there are quite a few definitions 19 00:01:09,120 --> 00:01:11,520 Speaker 1: of life out there, So let's get onto one of 20 00:01:11,520 --> 00:01:14,959 Speaker 1: the more scientific definitions of life, and that is one 21 00:01:14,959 --> 00:01:19,280 Speaker 1: in which proteins and nucleic acids interacting ways that allow 22 00:01:19,360 --> 00:01:22,240 Speaker 1: a structure to grow and reproduce. Yeah, I think pretty 23 00:01:22,240 --> 00:01:28,559 Speaker 1: obvious robots is not going to meet that particular criteria, right, So, yeah, 24 00:01:28,720 --> 00:01:32,240 Speaker 1: that's a that's a that this is definitely um describing life, 25 00:01:32,440 --> 00:01:36,000 Speaker 1: defining life as organic um in a very particular manner 26 00:01:36,040 --> 00:01:39,000 Speaker 1: that applies to us, definitely, So so no go on 27 00:01:39,160 --> 00:01:42,880 Speaker 1: robots for that one. However, there's another definition that life 28 00:01:42,920 --> 00:01:46,640 Speaker 1: is a system that's capable of Darwinian evolution, all right. 29 00:01:46,680 --> 00:01:48,760 Speaker 1: To meet this criteria, robot would have to be able 30 00:01:48,800 --> 00:01:51,880 Speaker 1: to reproduce and make more of itself, and it would 31 00:01:51,920 --> 00:01:55,680 Speaker 1: also need a source of variation, so right, so that 32 00:01:55,720 --> 00:01:58,360 Speaker 1: all of the new generation wouldn't be identical to the 33 00:01:58,400 --> 00:02:00,760 Speaker 1: previous and that all the sub links would be varied 34 00:02:00,800 --> 00:02:05,080 Speaker 1: as well. So then natural selection could take place because 35 00:02:05,120 --> 00:02:09,560 Speaker 1: when obviously when humans reproduce or or or any animal, uh, 36 00:02:09,600 --> 00:02:13,280 Speaker 1: they're not creating exact um you know, replicants of themselves 37 00:02:13,280 --> 00:02:17,080 Speaker 1: and that creating clones. They're creating variations. And the whole ideas, 38 00:02:17,240 --> 00:02:20,680 Speaker 1: you know, the whole idea is that that we're going 39 00:02:20,720 --> 00:02:23,840 Speaker 1: to create a lot of different variations on this successful model, 40 00:02:23,919 --> 00:02:26,520 Speaker 1: and we'll see if an even more successful model will 41 00:02:26,560 --> 00:02:28,600 Speaker 1: come out of it, or if there's a variation that 42 00:02:28,600 --> 00:02:31,080 Speaker 1: will be more adapt for the you know, for the 43 00:02:31,120 --> 00:02:36,720 Speaker 1: current situation, right mutation as the spice of life exactly. So, um, yeah, 44 00:02:36,760 --> 00:02:39,040 Speaker 1: I can robots do that. A couple of people have 45 00:02:39,040 --> 00:02:42,359 Speaker 1: taken a shot at this, right Yeah. Yeah, the more 46 00:02:42,400 --> 00:02:43,800 Speaker 1: more than a couple. But there are a couple of 47 00:02:43,880 --> 00:02:46,239 Speaker 1: that are that are rather interesting to look at. There's 48 00:02:46,280 --> 00:02:49,679 Speaker 1: a Cornell team that built they built this robot, and 49 00:02:49,720 --> 00:02:52,240 Speaker 1: these are robots. This particular robot especially is one that 50 00:02:52,440 --> 00:02:56,840 Speaker 1: was designed only to replicate itself in a very simple manner, 51 00:02:56,880 --> 00:02:59,240 Speaker 1: so it's not it's not like it's doing other things 52 00:02:59,280 --> 00:03:03,600 Speaker 1: and then on the side it's making more of itself. Um. Basically, 53 00:03:04,040 --> 00:03:06,280 Speaker 1: this one is made up of a series of modular cubes, 54 00:03:06,280 --> 00:03:09,160 Speaker 1: and each cube has all the like you know. Basically, 55 00:03:09,280 --> 00:03:12,400 Speaker 1: it's kind of like a block robot. Imagine little little 56 00:03:12,440 --> 00:03:14,920 Speaker 1: cubes and all in the cubes contain the robotics, if 57 00:03:14,960 --> 00:03:17,440 Speaker 1: you will. This is no crepf right, and it sort 58 00:03:17,480 --> 00:03:19,240 Speaker 1: of builds itself out of these blocks, and then it 59 00:03:19,280 --> 00:03:22,640 Speaker 1: can build another of itself out of other blocks. But 60 00:03:22,680 --> 00:03:24,560 Speaker 1: the blocks are already built. But it's it's so it's 61 00:03:24,639 --> 00:03:28,000 Speaker 1: very rudimentory. Right, So there's that one and there's the 62 00:03:28,000 --> 00:03:30,840 Speaker 1: English guys right out of the University of Bath. Yeah. 63 00:03:30,919 --> 00:03:33,519 Speaker 1: What's it called rep wrap, which I like a lot, 64 00:03:33,919 --> 00:03:37,760 Speaker 1: and that's short for replicating rapid prototyper. So with this 65 00:03:37,840 --> 00:03:40,640 Speaker 1: particular bot is concerned with, is it prints out these 66 00:03:40,680 --> 00:03:44,680 Speaker 1: thin layers of molten biodegradable plastic and those layers can 67 00:03:44,720 --> 00:03:46,480 Speaker 1: then be used to create its own three D parts. 68 00:03:47,200 --> 00:03:50,320 Speaker 1: It can also make sandals, no way. Yeah, yeah, they 69 00:03:50,320 --> 00:03:52,440 Speaker 1: had like it's it's basically yeah, it's like, you know, 70 00:03:52,480 --> 00:03:54,200 Speaker 1: it's like almost like a router, you know, it's just 71 00:03:54,240 --> 00:03:59,040 Speaker 1: making little shape fils for for humans. Yeah, are you serious? Yeah, 72 00:03:59,120 --> 00:04:01,440 Speaker 1: it's like basically it's like I said, these are very 73 00:04:01,480 --> 00:04:03,720 Speaker 1: simple robots. It's kind of you know, it's just making 74 00:04:05,360 --> 00:04:07,840 Speaker 1: remarkable thing that it can make it well anyway, like 75 00:04:07,880 --> 00:04:10,240 Speaker 1: these are just the baby steps towards you know, the 76 00:04:10,280 --> 00:04:12,480 Speaker 1: sort of the very sci fi ideas that you might 77 00:04:12,520 --> 00:04:16,320 Speaker 1: see and say Stanislaw Limbs The Invisible or Philip K. 78 00:04:16,440 --> 00:04:19,640 Speaker 1: Dick's Second Variety, you know, or um, I guess Terminators 79 00:04:19,680 --> 00:04:23,000 Speaker 1: were Terminator um movie nine, you know who? You have 80 00:04:23,120 --> 00:04:26,520 Speaker 1: robots that are making more of themselves. You know, this 81 00:04:26,600 --> 00:04:28,760 Speaker 1: is this is how it begins, except hopefully it doesn't 82 00:04:28,920 --> 00:04:32,479 Speaker 1: end quite as dismally. Yeah. So, one interesting question that 83 00:04:32,520 --> 00:04:34,760 Speaker 1: came up when you're researching this was the question of 84 00:04:34,760 --> 00:04:38,200 Speaker 1: whether computer viruses are alive. Yeah. A lot of people 85 00:04:38,240 --> 00:04:41,880 Speaker 1: make the argument that they are UM, including Stephen Hawking. 86 00:04:42,320 --> 00:04:46,400 Speaker 1: But remember, yeah, and I'm one of those documentaries that 87 00:04:46,480 --> 00:04:48,960 Speaker 1: are getting so much media coverage right now on Discovery 88 00:04:49,040 --> 00:04:55,800 Speaker 1: Channel Into the Universe. Yeah, for the web presence for it. Um. 89 00:04:55,880 --> 00:04:59,000 Speaker 1: So yeah, our computer viruses alive. Well. One thing to 90 00:04:59,080 --> 00:05:01,119 Speaker 1: keep in mind is that y ular viruses are tricky 91 00:05:01,200 --> 00:05:04,640 Speaker 1: enough to define um depending on who you ask. That 92 00:05:04,680 --> 00:05:08,119 Speaker 1: kind of occupy a gray area the viruses and again 93 00:05:08,160 --> 00:05:10,960 Speaker 1: with these organic viruses, like most of the internal structure 94 00:05:10,960 --> 00:05:15,600 Speaker 1: and machinery that characterize many definitions of life, including the 95 00:05:15,760 --> 00:05:19,839 Speaker 1: biosynthetic machinery that is necessary for reproduction. In order for 96 00:05:19,839 --> 00:05:22,720 Speaker 1: a virus to replicate, it has to infect a host cell. 97 00:05:23,760 --> 00:05:26,159 Speaker 1: But computer viruses, on the other end, have this sort 98 00:05:26,160 --> 00:05:30,039 Speaker 1: of partially automated ability to reproduce. But the virus itself, 99 00:05:30,320 --> 00:05:32,760 Speaker 1: this is an important distinction, is not the agent of reproduction. 100 00:05:32,760 --> 00:05:35,360 Speaker 1: The computer is. Yeah, I ran across a great analogy 101 00:05:35,400 --> 00:05:39,080 Speaker 1: for this, uh in Eugene HS. Stafford's Computer Viruses as 102 00:05:39,160 --> 00:05:41,599 Speaker 1: Artificial Life, which is a great read. You can find 103 00:05:41,600 --> 00:05:44,400 Speaker 1: it online and pdf form. Yeah, he points out that 104 00:05:44,400 --> 00:05:47,680 Speaker 1: the virus is not the agent of reproduction, the computer is. 105 00:05:48,400 --> 00:05:51,479 Speaker 1: He said, so if he argues in this that or 106 00:05:51,520 --> 00:05:55,719 Speaker 1: he makes the analogy. So so yeah, he uh, he 107 00:05:55,800 --> 00:05:58,760 Speaker 1: makes the analogy that if if that is life, then 108 00:05:59,279 --> 00:06:03,480 Speaker 1: printed out prints of a for a Xerox machine or life, right, 109 00:06:03,520 --> 00:06:05,080 Speaker 1: like a big stack of papers that have all the 110 00:06:05,080 --> 00:06:08,400 Speaker 1: plans for the zero Well, okay, so I I give 111 00:06:08,440 --> 00:06:11,320 Speaker 1: that these plans to you, right, and then you could 112 00:06:11,320 --> 00:06:14,599 Speaker 1: technically use those plans to make a Xerox machine correct, 113 00:06:15,400 --> 00:06:17,680 Speaker 1: And then you could take those plans put them through 114 00:06:17,720 --> 00:06:21,040 Speaker 1: the Xerox machine, and then you have a new copy 115 00:06:21,120 --> 00:06:24,240 Speaker 1: and a replica of the Then you have two stacks 116 00:06:24,240 --> 00:06:28,120 Speaker 1: of Xerox plans, Stack A and Stack B, and then 117 00:06:28,120 --> 00:06:30,520 Speaker 1: you could take Stack B and I could read them, 118 00:06:30,839 --> 00:06:34,320 Speaker 1: build a Xerox machine and then run Stack B through 119 00:06:34,360 --> 00:06:37,360 Speaker 1: the zero new Xerox machine and create Stack C. That's 120 00:06:37,360 --> 00:06:40,520 Speaker 1: really interesting. Yeah, but you know so, But obviously the 121 00:06:40,839 --> 00:06:43,160 Speaker 1: stack of papers just to stack of paper with information 122 00:06:43,200 --> 00:06:48,240 Speaker 1: on them, so, so I found that particularly interesting. Of course, 123 00:06:48,240 --> 00:06:51,600 Speaker 1: the other question would be can a computer virus evolve? Um? 124 00:06:51,640 --> 00:06:55,880 Speaker 1: That's another problem. According to Stafford, While a complex computer 125 00:06:56,000 --> 00:06:59,280 Speaker 1: virus might be able to adapt and evolve, um, you know, 126 00:06:59,320 --> 00:07:01,720 Speaker 1: he argues that this kind of virus would be larger 127 00:07:01,760 --> 00:07:05,080 Speaker 1: than most host programs and possibly larger than the host 128 00:07:05,080 --> 00:07:08,880 Speaker 1: system as well. Um, virus is out there and on 129 00:07:08,920 --> 00:07:11,880 Speaker 1: the Internet. They do evolve, but generally, but in the 130 00:07:11,920 --> 00:07:14,560 Speaker 1: sense that there's an author out there who is who 131 00:07:14,600 --> 00:07:17,800 Speaker 1: tweaks them and uh, and it makes them adapt m 132 00:07:17,920 --> 00:07:22,200 Speaker 1: so that they can, you know, better, screw with your browser. Right. 133 00:07:22,280 --> 00:07:24,160 Speaker 1: So then if you if you look at it that way, 134 00:07:24,200 --> 00:07:27,600 Speaker 1: you wouldn't necessarily call it computer virus alive, right, because 135 00:07:27,600 --> 00:07:31,080 Speaker 1: the agent of change here is, you know, some guy 136 00:07:31,080 --> 00:07:35,600 Speaker 1: in Korea on a PC putting Korean there. Well, I 137 00:07:35,600 --> 00:07:37,720 Speaker 1: thought there seems like there was a big story where 138 00:07:37,720 --> 00:07:40,280 Speaker 1: they were certain they were like, I mean, they're everywhere 139 00:07:41,200 --> 00:07:44,400 Speaker 1: saying that all computer virus authors are in Korea by 140 00:07:44,400 --> 00:07:48,720 Speaker 1: any means. So let's let's talk about the difference between 141 00:07:48,880 --> 00:07:53,160 Speaker 1: automatons and actual robots. Um. Yeah, this is something important 142 00:07:53,400 --> 00:07:56,480 Speaker 1: to keep in mind and something that came out of 143 00:07:56,480 --> 00:08:02,280 Speaker 1: a conversation I had with Idaho National Laboratory roboticist Derek Wadsworth. Um. 144 00:08:02,400 --> 00:08:05,160 Speaker 1: He said that you, on one hand, you have an 145 00:08:05,160 --> 00:08:08,160 Speaker 1: automaton and this is like a mechanical manipulator on the 146 00:08:08,440 --> 00:08:10,720 Speaker 1: vehicle assembly line. Right. Have you seen some of the 147 00:08:10,720 --> 00:08:13,960 Speaker 1: pictures of the robots on vehicle assembly lines are pretty amazing. Yeah. 148 00:08:14,000 --> 00:08:17,920 Speaker 1: I've not only seen pictures, I've seen moving pictures of them. Excellent. Yeah, 149 00:08:17,960 --> 00:08:19,880 Speaker 1: I seetimes. They used to show them on Sesame Street, 150 00:08:19,880 --> 00:08:23,120 Speaker 1: didn't they. I've never seen that. You've never seen Sesame Street. No, 151 00:08:23,240 --> 00:08:26,040 Speaker 1: I've never seen a particular part of the robot version 152 00:08:26,080 --> 00:08:30,560 Speaker 1: of Sesame Street. It's just auto assembly line machines. Um. 153 00:08:30,600 --> 00:08:33,400 Speaker 1: So okay. So they have the ability, these robot arms 154 00:08:33,400 --> 00:08:35,080 Speaker 1: that are putting together cars, they have the ability to 155 00:08:35,120 --> 00:08:38,079 Speaker 1: sense and act um like a vehicle frame advances on 156 00:08:38,120 --> 00:08:40,920 Speaker 1: a conveyor belt, the manipulator since is its presence and 157 00:08:40,920 --> 00:08:45,120 Speaker 1: then installs a windshield. A true robot applies an extra 158 00:08:45,120 --> 00:08:48,400 Speaker 1: step in this process, and that's reason. It analyzes the 159 00:08:48,440 --> 00:08:51,679 Speaker 1: sense data and then acts based on its computations. And 160 00:08:51,720 --> 00:08:54,520 Speaker 1: the cool thing is that is humans we have those capabilities, 161 00:08:54,920 --> 00:08:58,120 Speaker 1: so and everything we do. We're constantly processing our environment 162 00:08:58,200 --> 00:09:03,280 Speaker 1: where you know, smelling what's cooking, analyzing um, what that 163 00:09:03,320 --> 00:09:05,439 Speaker 1: smell means to us, and then we're producing an action. 164 00:09:05,520 --> 00:09:08,280 Speaker 1: You know, we're going to the kitchen to you know, 165 00:09:08,320 --> 00:09:10,200 Speaker 1: sniff out an extra donut that somebody left in the 166 00:09:10,200 --> 00:09:13,199 Speaker 1: break room. Yeah, but that's one of the things that 167 00:09:13,240 --> 00:09:16,000 Speaker 1: there's so many little bits of since data that we 168 00:09:16,040 --> 00:09:18,280 Speaker 1: absorbed and we don't even realize we're absorbing them and 169 00:09:18,360 --> 00:09:21,200 Speaker 1: just you know, it's it's happening subconsciously. And then where 170 00:09:21,440 --> 00:09:25,920 Speaker 1: we're computing that with like past life experiences, you know, 171 00:09:26,000 --> 00:09:28,040 Speaker 1: some of which may you know a lot of data 172 00:09:28,280 --> 00:09:31,400 Speaker 1: from the past, et cetera. Gets it gets so complicated 173 00:09:31,440 --> 00:09:33,480 Speaker 1: that we're not even aware of most of what's going on. 174 00:09:34,200 --> 00:09:36,600 Speaker 1: So to apply this to robots according to Watts, where 175 00:09:36,600 --> 00:09:39,280 Speaker 1: if they're alive in the sense that, yes, some robots 176 00:09:39,280 --> 00:09:43,120 Speaker 1: do in fact have the abilities to sense, reason and act. 177 00:09:44,000 --> 00:09:47,560 Speaker 1: So I'd say I'd score one point for robots being alive. Yeah, yeah, 178 00:09:47,600 --> 00:09:51,199 Speaker 1: that sounds pretty good. In fact, one of the robots 179 00:09:51,240 --> 00:09:53,600 Speaker 1: that you can make a case for being alive actually 180 00:09:53,600 --> 00:09:55,599 Speaker 1: lives in my house and probably a lot of a 181 00:09:55,679 --> 00:09:57,520 Speaker 1: lot of listeners have I'm so jealous of this. I 182 00:09:57,559 --> 00:10:00,000 Speaker 1: totally want to remove although I just got a really, really, 183 00:10:00,120 --> 00:10:02,520 Speaker 1: really great vacuum, which I'm very excited about. Yeah, but 184 00:10:02,559 --> 00:10:05,560 Speaker 1: who's the who's the agent of vacuuming in in that scenario, 185 00:10:05,760 --> 00:10:08,400 Speaker 1: that's true, I am the Asian vacuuming those kids. Give 186 00:10:08,440 --> 00:10:10,520 Speaker 1: those those kids to work vacuuming, and we are not 187 00:10:10,559 --> 00:10:12,800 Speaker 1: let them touch money vacuum. We'll see that. That's the 188 00:10:13,040 --> 00:10:14,520 Speaker 1: great thing about the room. But it's the room. But 189 00:10:15,080 --> 00:10:18,200 Speaker 1: is vacuuming obviously, And it's not just it's easy. If 190 00:10:18,240 --> 00:10:21,880 Speaker 1: you if you've never played with one of these before, UM, 191 00:10:21,920 --> 00:10:23,440 Speaker 1: you know it's it's it's great because it's not just 192 00:10:23,440 --> 00:10:26,760 Speaker 1: bouncing off the walls and just randomly vacuating the whole house. 193 00:10:26,880 --> 00:10:30,880 Speaker 1: You know, it's um you know, it's actually measuring, you 194 00:10:30,880 --> 00:10:33,719 Speaker 1: know where it is. It's it's reacting to the environment 195 00:10:34,160 --> 00:10:37,040 Speaker 1: and and like creating this map of where things are, 196 00:10:37,520 --> 00:10:40,320 Speaker 1: UM so that the next time it comes into your 197 00:10:41,320 --> 00:10:44,599 Speaker 1: kitchen and remembers that, oh gosh, the trash can is 198 00:10:44,640 --> 00:10:46,280 Speaker 1: situated in the corner. And I'm not going to go 199 00:10:46,320 --> 00:10:48,600 Speaker 1: in this direction. Well, I'm not sure about the more 200 00:10:48,679 --> 00:10:50,880 Speaker 1: advanced models. Another one we have it. It's like it 201 00:10:50,880 --> 00:10:52,760 Speaker 1: seems like each time you turn it on, it's like 202 00:10:52,800 --> 00:10:56,120 Speaker 1: it's it's a new learning experience. But during that run, 203 00:10:56,160 --> 00:10:58,920 Speaker 1: it'll you know, it'll get smarter as it goes. Um, 204 00:10:58,960 --> 00:11:01,760 Speaker 1: how does your cat feel about They don't get along 205 00:11:01,800 --> 00:11:03,520 Speaker 1: all that? Well, they don't hate each other, but they 206 00:11:03,559 --> 00:11:06,640 Speaker 1: don't like to hang out. Um, and uh, you know, 207 00:11:06,720 --> 00:11:08,960 Speaker 1: and then the room, bob, you know, it's you still 208 00:11:08,960 --> 00:11:11,040 Speaker 1: have to actually clean it and things like that. It's 209 00:11:11,040 --> 00:11:12,599 Speaker 1: not that's the thing the problem. Some people get the 210 00:11:12,640 --> 00:11:14,880 Speaker 1: room and they're light. You're like, hooray, I never have 211 00:11:15,000 --> 00:11:17,559 Speaker 1: to mess with a vacuum cleaner again. And that's wrong 212 00:11:17,600 --> 00:11:20,559 Speaker 1: and actually need to clean it out. Um. Can I 213 00:11:20,559 --> 00:11:22,720 Speaker 1: ask you a personal question? Go for it? How often 214 00:11:22,760 --> 00:11:26,800 Speaker 1: do you vacuum? Um? Or you or your partner? Um, 215 00:11:26,960 --> 00:11:29,600 Speaker 1: we turn on the room, but I don't know, maybe once. 216 00:11:29,640 --> 00:11:31,880 Speaker 1: So it depends on the room. And the cat actually 217 00:11:31,880 --> 00:11:34,400 Speaker 1: plays a big role in this because there's like one 218 00:11:34,440 --> 00:11:37,840 Speaker 1: carpet that the cat likes to to roll around on 219 00:11:38,200 --> 00:11:40,439 Speaker 1: and so she sheds a lot on that carpet. So 220 00:11:40,480 --> 00:11:43,000 Speaker 1: then the room but has to go in and suck 221 00:11:43,080 --> 00:11:44,600 Speaker 1: up all the hair. So actually the cat in the room. 222 00:11:44,640 --> 00:11:49,160 Speaker 1: But I really have a very close relationship in that sense. Um, 223 00:11:49,280 --> 00:11:51,120 Speaker 1: the big thing to keep in mind with with any 224 00:11:51,200 --> 00:11:53,680 Speaker 1: room but though is don't let it taste human blood, 225 00:11:54,520 --> 00:11:57,040 Speaker 1: because then it's then it's all over. They become man 226 00:11:57,120 --> 00:11:59,800 Speaker 1: killers and they have to be put down. But then, anyway, 227 00:12:00,120 --> 00:12:04,040 Speaker 1: to the point is that you can make a very 228 00:12:04,080 --> 00:12:06,800 Speaker 1: good argument that the room but is alive. It's uh, 229 00:12:07,880 --> 00:12:09,920 Speaker 1: it's it gets to what it's expecting a wall, it's 230 00:12:09,920 --> 00:12:12,640 Speaker 1: expecting some some sort of obstacle in the way, and 231 00:12:12,679 --> 00:12:14,520 Speaker 1: it forms the map of the room so it doesn't 232 00:12:14,559 --> 00:12:18,800 Speaker 1: need to run into those objects anymore. So again, in 233 00:12:18,840 --> 00:12:23,000 Speaker 1: the automanton robot division, it's it's all about defining what 234 00:12:23,160 --> 00:12:25,480 Speaker 1: is a robot. And you know earlier we're talking about 235 00:12:25,520 --> 00:12:29,400 Speaker 1: what is life. There are other there are other robotists 236 00:12:29,440 --> 00:12:31,680 Speaker 1: who go as far as to say, hey, um, you know, 237 00:12:31,760 --> 00:12:35,400 Speaker 1: technically are cars or robots? You know, they have all 238 00:12:35,400 --> 00:12:38,600 Speaker 1: these different integrated computer systems I think upwards like a 239 00:12:38,640 --> 00:12:41,080 Speaker 1: dozen in some of the price here automobiles. Yeah, I 240 00:12:41,120 --> 00:12:43,880 Speaker 1: don't know what you're driving, but my car does not 241 00:12:43,960 --> 00:12:47,360 Speaker 1: qualify for that category. Really, Yeah, my CD player doesn't 242 00:12:47,360 --> 00:12:49,240 Speaker 1: even work. It's busted. But but here's the thing. Do 243 00:12:49,280 --> 00:12:53,360 Speaker 1: you think your car is alive? I don't really think 244 00:12:53,360 --> 00:12:55,840 Speaker 1: of it as such, although I did give it a name. Yeah, 245 00:12:55,880 --> 00:12:59,760 Speaker 1: would you name your car M Francis for see you 246 00:13:00,040 --> 00:13:01,680 Speaker 1: see your car? Then in a since your car is 247 00:13:01,679 --> 00:13:04,199 Speaker 1: more alive in my car, which has no name, mine's 248 00:13:04,240 --> 00:13:06,439 Speaker 1: just the car. I can't I generally can't even remember 249 00:13:06,480 --> 00:13:08,959 Speaker 1: what make a model it is much. I know what 250 00:13:09,000 --> 00:13:11,640 Speaker 1: makes a model it is? Yeah, yeah, mine cool? Because 251 00:13:11,679 --> 00:13:14,000 Speaker 1: we used to park at that same mortestation. Oh did we? 252 00:13:14,080 --> 00:13:19,720 Speaker 1: And you were coming in like messing with my car? No, no, no, 253 00:13:19,760 --> 00:13:22,560 Speaker 1: I would never do that. Well not, and that's your 254 00:13:22,600 --> 00:13:25,760 Speaker 1: car at least. But but but I actually underlined something 255 00:13:25,840 --> 00:13:28,920 Speaker 1: important about the whole issue of like robots and whether 256 00:13:28,960 --> 00:13:30,200 Speaker 1: they're alive or not. I mean, a lot of it 257 00:13:30,200 --> 00:13:32,920 Speaker 1: comes down to our It comes on to our perception 258 00:13:33,160 --> 00:13:34,520 Speaker 1: a lot of the times. You know, it's like the 259 00:13:34,720 --> 00:13:38,200 Speaker 1: more robots seems to be alive, the more you know 260 00:13:38,240 --> 00:13:41,760 Speaker 1: it is alive, at least to us. But then that's 261 00:13:41,840 --> 00:13:44,040 Speaker 1: that's kind of our failings as human. Like you draw 262 00:13:44,360 --> 00:13:47,320 Speaker 1: anything that kind of looks like a smiley face, and 263 00:13:47,559 --> 00:13:53,400 Speaker 1: we instantly begin to yeah, we anthro morpie. Everything that's true, 264 00:13:53,440 --> 00:13:58,240 Speaker 1: we do. So what what what mean for for robots 265 00:13:58,360 --> 00:14:02,360 Speaker 1: if they reach the point where they are definitely alive? Sure? 266 00:14:02,440 --> 00:14:04,480 Speaker 1: Do they have rights? Yeah? Do they have rights? Can 267 00:14:04,520 --> 00:14:08,240 Speaker 1: they marry? Um? I read an interesting argument about whether 268 00:14:08,280 --> 00:14:10,120 Speaker 1: or not it's a good idea to send them off 269 00:14:10,160 --> 00:14:14,480 Speaker 1: into space, because self replicating intelligent robots would be great 270 00:14:14,520 --> 00:14:17,280 Speaker 1: for exploring the universe. You know, just send them out, 271 00:14:17,360 --> 00:14:20,120 Speaker 1: let them harvest new resources as they go. But is 272 00:14:20,160 --> 00:14:23,520 Speaker 1: that ethical to send an army of robots to another 273 00:14:24,040 --> 00:14:26,200 Speaker 1: you know, to just an exoplanet to eat it and 274 00:14:26,240 --> 00:14:29,440 Speaker 1: make more of themselves. Right, we know already that robots 275 00:14:29,480 --> 00:14:33,880 Speaker 1: gets some of the less attractive jobs. Let's say, Yeah, 276 00:14:34,080 --> 00:14:36,760 Speaker 1: like at my house, like I get to do the 277 00:14:36,920 --> 00:14:40,440 Speaker 1: you know, the cool things like move things into the attic. Right, 278 00:14:40,480 --> 00:14:42,280 Speaker 1: I assume you're not down on the floor. Second up 279 00:14:42,360 --> 00:14:43,960 Speaker 1: cat hair. Yeah, I mean that's the whole thing. It's like, 280 00:14:44,000 --> 00:14:46,160 Speaker 1: we have a robot, we don't have to vacuum anymore. 281 00:14:46,160 --> 00:14:47,960 Speaker 1: And you know, or even in the case of the 282 00:14:48,000 --> 00:14:50,960 Speaker 1: recent oil spill that's messing with the Gulf coast right now. 283 00:14:51,440 --> 00:14:53,360 Speaker 1: I mean, what's the first thing people say, Well, sending 284 00:14:53,400 --> 00:14:55,280 Speaker 1: the robots to see if they can set off or 285 00:14:55,320 --> 00:14:57,960 Speaker 1: turn off that massive week. I'm kidding. I think robots 286 00:14:57,960 --> 00:15:00,280 Speaker 1: should obviously do a lot of these crazy job ups 287 00:15:00,280 --> 00:15:03,080 Speaker 1: and we shouldn't put humans at risk, but they do 288 00:15:03,240 --> 00:15:05,760 Speaker 1: get a lot of really bad jobs. Yeah, there's a 289 00:15:05,800 --> 00:15:08,960 Speaker 1: there's a great moment on a Futurama where Bender the 290 00:15:09,000 --> 00:15:11,800 Speaker 1: right here for watch Futurama. Yeah, Bender the robot. You know, 291 00:15:11,880 --> 00:15:14,400 Speaker 1: he gets all up in arms when somebody at a 292 00:15:14,480 --> 00:15:17,960 Speaker 1: ballgame like breaks a beer bottle and like a little 293 00:15:18,000 --> 00:15:19,960 Speaker 1: robot comes up and cleans it out, cleans it up, 294 00:15:20,000 --> 00:15:22,520 Speaker 1: and he's and he makes a big outcry about all 295 00:15:22,560 --> 00:15:24,240 Speaker 1: I look at and they're not not the human child 296 00:15:24,280 --> 00:15:26,680 Speaker 1: who has to clean up the mess. It's true. We 297 00:15:27,160 --> 00:15:29,560 Speaker 1: put the robots to work, and if they end up 298 00:15:29,600 --> 00:15:31,920 Speaker 1: with rights someday, then you know, maybe they'll have to 299 00:15:32,120 --> 00:15:34,480 Speaker 1: uh have to have some robotic from an in action. 300 00:15:34,520 --> 00:15:37,360 Speaker 1: I don't know. So let us know what you think. 301 00:15:37,400 --> 00:15:39,080 Speaker 1: Do you think robots are alive? Do you think they 302 00:15:39,120 --> 00:15:42,800 Speaker 1: will become alive? Do you think Robert is a robot? Cars? 303 00:15:43,440 --> 00:15:46,600 Speaker 1: Did Alison key my car? Yeah? If you have an 304 00:15:46,640 --> 00:15:48,680 Speaker 1: opinion on any of these things, send us an email 305 00:15:48,680 --> 00:15:51,720 Speaker 1: at Science Stuff at has Differ Dot com, so come 306 00:15:51,800 --> 00:15:54,080 Speaker 1: check out the blog. You can access it off the 307 00:15:54,120 --> 00:15:58,000 Speaker 1: home page. We also have a Facebook account which you 308 00:15:58,000 --> 00:16:00,560 Speaker 1: can just search for stuff from the side Fence Lab 309 00:16:00,760 --> 00:16:02,240 Speaker 1: and then I'll lead you right to it, and you 310 00:16:02,240 --> 00:16:04,640 Speaker 1: can check us out on Twitter. We are lab stuff 311 00:16:05,240 --> 00:16:08,680 Speaker 1: and we're constantly updating that thing. So yeah, we're all 312 00:16:08,720 --> 00:16:12,080 Speaker 1: over the web. We're tweeting, breakining, mad science. That's what 313 00:16:12,080 --> 00:16:22,400 Speaker 1: we do. So thanks for listening, guys. For more on 314 00:16:22,480 --> 00:16:24,960 Speaker 1: this and thousands of other topics, is it how stuff 315 00:16:24,960 --> 00:16:28,520 Speaker 1: works dot com. Want more how stuff works, check out 316 00:16:28,520 --> 00:16:31,080 Speaker 1: our blogs on the house stuff works dot com home page.