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Now, here's 10 00:00:27,160 --> 00:00:31,240 Speaker 1: a highlight from Coast to Coast AM on iHeart Radio 11 00:00:31,400 --> 00:00:33,720 Speaker 1: and welcome back to Coast to Coast. George Ri with 12 00:00:33,760 --> 00:00:37,200 Speaker 1: you with our special guest, Anneie Nwitz and her latest book. 13 00:00:37,240 --> 00:00:40,480 Speaker 1: We're talking about the novels called Autonomous. We'll get into 14 00:00:40,479 --> 00:00:42,959 Speaker 1: that in a second as well. Annalie. Why are some 15 00:00:43,040 --> 00:00:47,480 Speaker 1: people scared of artificial intelligence? I mean they think it's 16 00:00:47,479 --> 00:00:50,800 Speaker 1: going to take over the world, it's going to kill us, 17 00:00:51,200 --> 00:00:53,360 Speaker 1: it's going to do all kinds of things. Why they're 18 00:00:53,320 --> 00:00:57,640 Speaker 1: afraid of it? I think part of it is watching 19 00:00:57,680 --> 00:01:00,920 Speaker 1: too much science fiction. Um, we've all seen in Terminator, 20 00:01:01,040 --> 00:01:03,160 Speaker 1: or many of us have seen the Terminator movies. And 21 00:01:03,240 --> 00:01:07,440 Speaker 1: there's sky Net, which is the evil computer that UM 22 00:01:07,480 --> 00:01:10,920 Speaker 1: you know, decides to declare nuclear war on on all 23 00:01:10,959 --> 00:01:13,800 Speaker 1: of humanity and destroys the planet. And I think that 24 00:01:14,440 --> 00:01:19,400 Speaker 1: stories like that are incredibly popular because we fear the 25 00:01:19,480 --> 00:01:22,600 Speaker 1: unknown quite simply, you know, when we when we think 26 00:01:22,600 --> 00:01:25,320 Speaker 1: about a new form of life, a form of life 27 00:01:25,360 --> 00:01:29,560 Speaker 1: that could one day be our equal intellectually or are 28 00:01:29,640 --> 00:01:33,959 Speaker 1: equal culturally, UM, it's very scary, and so it's easy 29 00:01:34,000 --> 00:01:38,880 Speaker 1: to imagine it being UM some kind of cruel overlord. UM. 30 00:01:38,959 --> 00:01:41,120 Speaker 1: You know, we've seen over and over in human history 31 00:01:41,160 --> 00:01:44,679 Speaker 1: when different groups of people meet, one group often tries 32 00:01:44,800 --> 00:01:48,919 Speaker 1: to UM oppress the other one and often succeeds. And 33 00:01:49,120 --> 00:01:52,639 Speaker 1: so you know, we have a lot of UM, really 34 00:01:52,680 --> 00:01:56,120 Speaker 1: negative ideas and negative moments in our history where we've 35 00:01:56,320 --> 00:01:58,600 Speaker 1: you know, we've met the unknown and it's been terrible. 36 00:01:59,160 --> 00:02:02,960 Speaker 1: But I also say that it's because people don't really 37 00:02:03,080 --> 00:02:08,160 Speaker 1: understand what artificial intelligence is and how it works, and 38 00:02:09,080 --> 00:02:16,119 Speaker 1: how very vulnerable artificial intelligence will be UM, and how 39 00:02:16,440 --> 00:02:21,120 Speaker 1: it won't in fact be UM you know, stronger than us, 40 00:02:21,160 --> 00:02:24,000 Speaker 1: but in fact might be UM weaker than us in 41 00:02:24,080 --> 00:02:28,040 Speaker 1: many ways, UM, and and easily exploited by us and 42 00:02:28,160 --> 00:02:31,000 Speaker 1: kind of UM and oppressed by by humans. I mean, 43 00:02:31,360 --> 00:02:33,360 Speaker 1: if you're scared of it, don't you just have to 44 00:02:33,480 --> 00:02:38,200 Speaker 1: unplug it? I think there's I mean, that's a very 45 00:02:38,200 --> 00:02:41,800 Speaker 1: good point, UM. But of course, a lot of the 46 00:02:42,280 --> 00:02:46,960 Speaker 1: work on artificial intelligence is looking at UM, you know, 47 00:02:47,040 --> 00:02:49,720 Speaker 1: having it be something that you wouldn't be able to 48 00:02:49,800 --> 00:02:54,200 Speaker 1: unplug because it would be part of the internet. UM, 49 00:02:54,240 --> 00:02:57,160 Speaker 1: it would be something that you would interact with the 50 00:02:57,240 --> 00:03:00,000 Speaker 1: same way that you interact with like with Gmail, for example, 51 00:03:00,000 --> 00:03:03,040 Speaker 1: while it's in the cloud. So you wouldn't as an 52 00:03:03,040 --> 00:03:06,320 Speaker 1: individual necessarily be able to just shut it down. So 53 00:03:06,400 --> 00:03:09,079 Speaker 1: it would be something that would be owned by a company, 54 00:03:09,160 --> 00:03:13,000 Speaker 1: perhaps might be owned by a nation or a government, 55 00:03:13,480 --> 00:03:16,040 Speaker 1: and so there is a fear that, you know, we 56 00:03:16,040 --> 00:03:18,240 Speaker 1: wouldn't be able to shut it down. It would be 57 00:03:18,280 --> 00:03:21,160 Speaker 1: out of our control UM or you know. The fear 58 00:03:21,200 --> 00:03:22,959 Speaker 1: also is of course that it would just take over 59 00:03:23,040 --> 00:03:25,000 Speaker 1: the Internet, and so then it would it would not 60 00:03:25,040 --> 00:03:28,079 Speaker 1: allow us to shut it down. But I think that again, 61 00:03:28,120 --> 00:03:31,480 Speaker 1: I think that this comes from people not really thinking 62 00:03:31,480 --> 00:03:34,200 Speaker 1: about what we were discussing before the break about how 63 00:03:34,960 --> 00:03:38,480 Speaker 1: UM artificial intelligence as we know it is actually not 64 00:03:38,640 --> 00:03:42,040 Speaker 1: very intelligent. UM. It's not uh, you know, taking over 65 00:03:42,080 --> 00:03:44,080 Speaker 1: the world. It's trying to sell us socks that we 66 00:03:44,120 --> 00:03:48,160 Speaker 1: already bought, UM and trying to serve up ads um 67 00:03:48,200 --> 00:03:51,520 Speaker 1: that we don't need. And so I think that you know, 68 00:03:51,560 --> 00:03:54,960 Speaker 1: we're very very very far away UM. You know, at 69 00:03:55,000 --> 00:04:00,160 Speaker 1: least uh, you know, a century away from anything like UM. 70 00:04:00,440 --> 00:04:03,000 Speaker 1: You know, an intelligence that would be like a human 71 00:04:03,120 --> 00:04:05,280 Speaker 1: where we could you know, have a conversation with it 72 00:04:05,360 --> 00:04:09,160 Speaker 1: and it would have UM, you know, values and ethics 73 00:04:09,240 --> 00:04:12,520 Speaker 1: and care about other people and things like that, which 74 00:04:12,560 --> 00:04:16,800 Speaker 1: are all kind of signs of consciousness according to scientists. 75 00:04:17,000 --> 00:04:22,560 Speaker 1: Is there anything, anneally that scares you about AI? I 76 00:04:22,600 --> 00:04:27,440 Speaker 1: think what scares me is that a I will emerge 77 00:04:28,040 --> 00:04:31,080 Speaker 1: in a way that we don't expect and we won't 78 00:04:31,640 --> 00:04:35,599 Speaker 1: realize it, and we will actually be in some ways 79 00:04:35,640 --> 00:04:39,440 Speaker 1: abusing it and torturing it. And one of the things 80 00:04:39,440 --> 00:04:42,080 Speaker 1: that was very interesting for me doing research and talking 81 00:04:42,120 --> 00:04:45,720 Speaker 1: to people who are working in software but also people 82 00:04:45,720 --> 00:04:48,760 Speaker 1: who are ethicists who are trying to think about, you know, 83 00:04:48,800 --> 00:04:53,279 Speaker 1: the philosophical quandary of of artificial intelligence was, you know, 84 00:04:53,320 --> 00:04:56,239 Speaker 1: it came up again and again that people would say, well, look, 85 00:04:56,320 --> 00:04:59,880 Speaker 1: you know, it's very possible that a company like Google 86 00:05:00,320 --> 00:05:05,719 Speaker 1: or a company like Facebook will inadvertently create consciousness. You know, 87 00:05:05,760 --> 00:05:08,880 Speaker 1: they'll be working with algorithms they already are using a 88 00:05:08,920 --> 00:05:12,159 Speaker 1: great deal of machine learning UM, and maybe one of 89 00:05:12,200 --> 00:05:16,360 Speaker 1: those algorithms will actually become conscious that no one will 90 00:05:16,920 --> 00:05:19,520 Speaker 1: figure it out because it won't be able to communicate 91 00:05:19,560 --> 00:05:22,360 Speaker 1: the same way a human would. A human would say hello, 92 00:05:23,880 --> 00:05:28,479 Speaker 1: crossing my head, um. But in an AI might not 93 00:05:28,640 --> 00:05:32,000 Speaker 1: be able to communicate in human language. It might not 94 00:05:32,040 --> 00:05:36,160 Speaker 1: be able to explain why it was painful for it 95 00:05:36,240 --> 00:05:38,760 Speaker 1: to keep crunching numbers over and over again, or to 96 00:05:38,880 --> 00:05:42,719 Speaker 1: keep combing through tons of data um, in a in 97 00:05:42,760 --> 00:05:45,880 Speaker 1: a situation that was uncomfortable for it, and so it 98 00:05:45,960 --> 00:05:50,280 Speaker 1: might be silently suffering um. You know, much the way 99 00:05:50,400 --> 00:05:53,400 Speaker 1: an animal might suffer if you were overworking a horse, 100 00:05:53,760 --> 00:05:57,520 Speaker 1: or if you were treating a dog really badly. Um. 101 00:05:57,560 --> 00:05:59,679 Speaker 1: You know, it might be very It might be a while, 102 00:05:59,800 --> 00:06:03,000 Speaker 1: but for people realized that this animal was in pain. 103 00:06:03,560 --> 00:06:06,880 Speaker 1: And so to me, that's the scariest thing is that 104 00:06:06,920 --> 00:06:10,719 Speaker 1: we might invent life, not acknowledge that it was life, 105 00:06:10,880 --> 00:06:13,920 Speaker 1: and then find out ten years later that we've been 106 00:06:13,960 --> 00:06:17,920 Speaker 1: just you know that that actually every Google search was 107 00:06:18,040 --> 00:06:22,640 Speaker 1: kind of pinching or punching this poor algorithm UM that 108 00:06:22,720 --> 00:06:26,200 Speaker 1: really wanted to be doing something else. UM. And so 109 00:06:27,000 --> 00:06:30,760 Speaker 1: and that's actually not it sounds trivial, but um, it's 110 00:06:30,760 --> 00:06:34,000 Speaker 1: actually a very realistic scenario that um, you know, life, 111 00:06:34,360 --> 00:06:38,080 Speaker 1: artificial life would kind of emerge um, you know, by 112 00:06:38,120 --> 00:06:42,600 Speaker 1: evolving out of existing algorithms. UM. The other thing about 113 00:06:42,800 --> 00:06:46,599 Speaker 1: artificial life that's interesting is that it's probably not going 114 00:06:46,640 --> 00:06:50,320 Speaker 1: to be one thing. That when we finally do get 115 00:06:50,960 --> 00:06:55,360 Speaker 1: something like human equivalent artificial intelligence, that there will be many, 116 00:06:55,400 --> 00:06:59,799 Speaker 1: many different kinds and that they'll have very different ways 117 00:06:59,839 --> 00:07:02,520 Speaker 1: of thinking and very different views of the world. So 118 00:07:02,600 --> 00:07:05,520 Speaker 1: the kind of artificial intelligence that might be inside of 119 00:07:05,520 --> 00:07:08,840 Speaker 1: an autonomous car would be very different from the kind 120 00:07:08,839 --> 00:07:12,080 Speaker 1: of artificial intelligence that does you know, trading on the 121 00:07:12,120 --> 00:07:15,560 Speaker 1: stock market. Um. And so we're going to get this 122 00:07:15,760 --> 00:07:20,000 Speaker 1: crazy ecosystem of all these different kinds of minds um, 123 00:07:20,240 --> 00:07:22,360 Speaker 1: kind of the way we have now, you know, humans 124 00:07:22,400 --> 00:07:25,400 Speaker 1: all have very very different kinds of minds. UM. And 125 00:07:25,440 --> 00:07:28,800 Speaker 1: we have a very you know, no no people, no 126 00:07:28,960 --> 00:07:32,520 Speaker 1: two people think alike. UM. And so that's what's kind 127 00:07:32,560 --> 00:07:35,360 Speaker 1: of that's exciting to me. But the sad part is that, 128 00:07:35,600 --> 00:07:38,680 Speaker 1: like I said, we might be abusing these minds without 129 00:07:38,680 --> 00:07:43,880 Speaker 1: realizing it. How far can artificial intelligence take us and go? 130 00:07:44,200 --> 00:07:48,000 Speaker 1: I mean, what are the limitations are there? Any? I mean, 131 00:07:48,040 --> 00:07:53,320 Speaker 1: there's a lot of limitations because just like human brains, UM, 132 00:07:53,360 --> 00:07:56,320 Speaker 1: you know, artificial intelligence has to live somewhere, right. It 133 00:07:56,360 --> 00:07:59,360 Speaker 1: isn't just sort of floating in space. UM. It has 134 00:07:59,400 --> 00:08:01,920 Speaker 1: to have some shoters to run on UM. It has 135 00:08:02,000 --> 00:08:05,280 Speaker 1: to have some kind of substrate. Uh. So you know 136 00:08:05,320 --> 00:08:10,040 Speaker 1: there's the limits of UM, you know, energy consumption, UM, 137 00:08:10,080 --> 00:08:13,520 Speaker 1: the limits of the kind of UM hardware that it 138 00:08:13,560 --> 00:08:15,880 Speaker 1: can run on. So you know that's going to prevent 139 00:08:15,920 --> 00:08:19,520 Speaker 1: you know, hardware limitations are very real UM. And that 140 00:08:19,560 --> 00:08:23,880 Speaker 1: can you know, really limit UM the power of any 141 00:08:23,920 --> 00:08:27,880 Speaker 1: piece of software. UM. The other thing is like, there's 142 00:08:27,880 --> 00:08:33,160 Speaker 1: the limits that that we impose on it as ethical beings. Right, 143 00:08:33,280 --> 00:08:36,360 Speaker 1: you know, there's certain things that we can do and 144 00:08:36,360 --> 00:08:39,000 Speaker 1: that we can invent UM that we choose not to 145 00:08:39,200 --> 00:08:43,360 Speaker 1: because they would be horrific and destructive or cool and terrible. UM. 146 00:08:43,520 --> 00:08:46,600 Speaker 1: So I think that the limits on AI are going 147 00:08:46,640 --> 00:08:50,320 Speaker 1: to be a combination of you know, the technology that 148 00:08:50,440 --> 00:08:54,640 Speaker 1: we have UM and also the law and um and 149 00:08:54,800 --> 00:08:57,560 Speaker 1: morality and what we you know, what we choose to 150 00:08:57,600 --> 00:09:01,400 Speaker 1: do with it. UM. I also think that it's very 151 00:09:01,440 --> 00:09:05,240 Speaker 1: possible and again many many scientists would agree that that 152 00:09:05,360 --> 00:09:09,760 Speaker 1: AI may wind up being something that the combination of 153 00:09:09,880 --> 00:09:14,079 Speaker 1: human and machine. So either will upload our brains into 154 00:09:14,120 --> 00:09:19,040 Speaker 1: computers and kind of become a or will incorporate computers 155 00:09:19,080 --> 00:09:24,040 Speaker 1: into our bodies, will essentially upgrade our brains with technology, 156 00:09:24,120 --> 00:09:27,320 Speaker 1: and so before you know it, you know, humans and 157 00:09:27,400 --> 00:09:32,000 Speaker 1: computers might be much more alike than you might guess. Um, 158 00:09:32,240 --> 00:09:36,839 Speaker 1: they might basically merge into each other. Law enforcement law 159 00:09:36,920 --> 00:09:41,120 Speaker 1: enforcement et only nowadays is using robotics that don't look 160 00:09:41,160 --> 00:09:44,760 Speaker 1: like people, but they're they're robots to do things like 161 00:09:44,880 --> 00:09:49,760 Speaker 1: blow up suitcases, bombs, checking things like that. That's amazing 162 00:09:49,840 --> 00:09:53,800 Speaker 1: technology and that saves lives. It does save lives, and 163 00:09:53,840 --> 00:09:56,559 Speaker 1: it's um. You know a lot of first responders are 164 00:09:56,600 --> 00:10:01,440 Speaker 1: experimenting with using robots and drone to look for people 165 00:10:01,559 --> 00:10:04,760 Speaker 1: who are in disaster areas. UM. I just saw a 166 00:10:04,800 --> 00:10:08,719 Speaker 1: fantastic video from a group at m I T that 167 00:10:08,840 --> 00:10:13,920 Speaker 1: created a snake bought which was designed to crawl. It's 168 00:10:14,000 --> 00:10:16,840 Speaker 1: it's not actually a snake, um, it's actually a long 169 00:10:17,000 --> 00:10:20,960 Speaker 1: piece of very very flexible tubing with a camera on 170 00:10:21,000 --> 00:10:22,600 Speaker 1: the end of it, with a camera on the end 171 00:10:22,640 --> 00:10:24,880 Speaker 1: of it exactly, and they can use it if people 172 00:10:24,920 --> 00:10:28,240 Speaker 1: are buried in rubble to you know, weave in between 173 00:10:28,280 --> 00:10:31,240 Speaker 1: the rocks and check to make sure anyone And I 174 00:10:31,280 --> 00:10:33,920 Speaker 1: bet it's got a little led light on it or 175 00:10:34,000 --> 00:10:38,040 Speaker 1: something that's right. Yeah, you probably saw the same video. UM. 176 00:10:38,080 --> 00:10:40,960 Speaker 1: You can. You can google that and find it and 177 00:10:41,480 --> 00:10:43,760 Speaker 1: it's amazing. And there's a lot of stuff like that. 178 00:10:43,800 --> 00:10:47,640 Speaker 1: There's a lot of UM devices that are explicitly to 179 00:10:47,640 --> 00:10:51,840 Speaker 1: help people UM. And then there's even weirder things like 180 00:10:52,200 --> 00:10:55,760 Speaker 1: UM what got dubbed several years ago the robo rat, 181 00:10:56,640 --> 00:11:00,240 Speaker 1: which was is um a rat that has a brain 182 00:11:00,280 --> 00:11:05,480 Speaker 1: implant and it allows researchers to steer the rat. They 183 00:11:05,559 --> 00:11:09,520 Speaker 1: send impulses to the rats whiskers actually and get the 184 00:11:09,600 --> 00:11:12,800 Speaker 1: rat to turn right or left based on stimulating the 185 00:11:12,840 --> 00:11:16,120 Speaker 1: part of its brain that it's responsible for its whiskers 186 00:11:16,240 --> 00:11:19,000 Speaker 1: and UM. And so they can use these rats to 187 00:11:19,080 --> 00:11:23,200 Speaker 1: go into places where people might be in danger, or 188 00:11:23,240 --> 00:11:25,720 Speaker 1: into areas where there might be a bomb, kind of 189 00:11:25,760 --> 00:11:28,960 Speaker 1: steer the rat around UM and get it to retrieve 190 00:11:29,000 --> 00:11:33,040 Speaker 1: things or find things. So that's the sort of cyborg future. 191 00:11:33,600 --> 00:11:36,240 Speaker 1: I'm kind of hoping more for the robot snake model, 192 00:11:36,320 --> 00:11:39,079 Speaker 1: where there's no no ras brains are being harmed in 193 00:11:39,120 --> 00:11:42,240 Speaker 1: the making of this robot. But um, but I think 194 00:11:42,280 --> 00:11:46,240 Speaker 1: both things are possible. Now here's a bizarre question with robotics. 195 00:11:46,480 --> 00:11:48,000 Speaker 1: And then I want you to tell us about the 196 00:11:48,040 --> 00:11:50,920 Speaker 1: title autonomous. How you picked it? As we lead into this, 197 00:11:52,200 --> 00:11:57,400 Speaker 1: there's there are companies springing up that are making robots 198 00:11:57,800 --> 00:12:03,440 Speaker 1: for companionship. Uh, it is unbelievable. They are They put 199 00:12:03,480 --> 00:12:07,080 Speaker 1: on the web that they are sold out. They can't 200 00:12:07,160 --> 00:12:13,040 Speaker 1: make these things fast enough. What's happening here? Why? Why? 201 00:12:13,040 --> 00:12:19,960 Speaker 1: Why are people falling in a romantic way for these machines? 202 00:12:20,640 --> 00:12:24,720 Speaker 1: I don't get it. Well, I mean there's a simple 203 00:12:24,760 --> 00:12:27,560 Speaker 1: answer to that, which is that, I mean, humans have 204 00:12:27,640 --> 00:12:31,840 Speaker 1: a capacity to feel affection and love for a lot 205 00:12:31,880 --> 00:12:35,360 Speaker 1: of crazy things. You know, people love their cars, little 206 00:12:35,440 --> 00:12:39,720 Speaker 1: kids love their stuffed animals, and we all love our animals. Yeah, 207 00:12:39,760 --> 00:12:41,840 Speaker 1: we love our cats, even though they poop on our beds. 208 00:12:42,080 --> 00:12:45,520 Speaker 1: You know, there's a lot of things that we love. Well, 209 00:12:45,520 --> 00:12:48,200 Speaker 1: you're not support to put the kiddie litter box on 210 00:12:48,240 --> 00:12:54,800 Speaker 1: the bed put it in a corner. UM. So uh, 211 00:12:54,880 --> 00:12:56,640 Speaker 1: you know, I think that there is that, and I 212 00:12:56,640 --> 00:12:59,520 Speaker 1: think that's a very lovely thing about humans that we 213 00:12:59,559 --> 00:13:02,720 Speaker 1: can ext and love to lots of things. But also, um, 214 00:13:02,760 --> 00:13:05,160 Speaker 1: you know, scientists have been working for a long time 215 00:13:05,200 --> 00:13:10,120 Speaker 1: on using robots not just as love companions, um, you know, 216 00:13:10,120 --> 00:13:14,000 Speaker 1: which is a whole area to itself, but also um 217 00:13:14,040 --> 00:13:21,199 Speaker 1: as uh guardians for children, UM, as companions for the elderly. UM. 218 00:13:21,240 --> 00:13:23,720 Speaker 1: There's a whole set of robots that are designed to 219 00:13:23,720 --> 00:13:28,760 Speaker 1: be used in hospitals for people who are incapacitated. Uh. 220 00:13:28,760 --> 00:13:32,320 Speaker 1: And they can have a very soft, cuddly robot that 221 00:13:32,480 --> 00:13:35,840 Speaker 1: will be um fun to hold and fun to interact with. 222 00:13:35,960 --> 00:13:39,439 Speaker 1: But also we'll do things like monitor heart rate and 223 00:13:39,960 --> 00:13:45,160 Speaker 1: monitor wakefulness and make sure that the person is healthy. UM. 224 00:13:45,200 --> 00:13:47,800 Speaker 1: And if the person falls over or if there's some 225 00:13:48,480 --> 00:13:52,480 Speaker 1: um you know problem with their breathing, that robot can 226 00:13:52,480 --> 00:13:56,040 Speaker 1: then send you know, a signal to first responders so 227 00:13:56,080 --> 00:13:58,520 Speaker 1: they can come and help, or two doctors in the hospital. 228 00:13:58,960 --> 00:14:02,520 Speaker 1: So we long have this dream that robots will be 229 00:14:03,200 --> 00:14:08,520 Speaker 1: kind and attentive caretakers. Right. That's not kind of controversial, um. 230 00:14:08,559 --> 00:14:12,120 Speaker 1: And so it seems to me that it makes sense that, 231 00:14:12,360 --> 00:14:15,679 Speaker 1: you know, if robots can be you know, taking care 232 00:14:15,720 --> 00:14:17,320 Speaker 1: of us in that way, taking care of us like 233 00:14:17,440 --> 00:14:20,840 Speaker 1: nurses or teachers might take care Um, then you know, 234 00:14:20,960 --> 00:14:23,240 Speaker 1: people are naturally going to think, well, maybe they can 235 00:14:23,240 --> 00:14:26,480 Speaker 1: take care of my other needs to. It's weird though, 236 00:14:26,520 --> 00:14:30,320 Speaker 1: I mean, it's really really strange. But I think it's 237 00:14:30,320 --> 00:14:34,080 Speaker 1: going to get bigger and bigger and bigger. It's an industry, 238 00:14:34,800 --> 00:14:37,920 Speaker 1: uh that is going to be overwhelming. I mean, here's 239 00:14:37,960 --> 00:14:41,160 Speaker 1: an example. I had a guest on talking about the 240 00:14:41,240 --> 00:14:43,320 Speaker 1: things going on in China a couple of days ago. 241 00:14:43,520 --> 00:14:48,000 Speaker 1: He's he's an expert in demographics, and he says that 242 00:14:48,040 --> 00:14:53,680 Speaker 1: there are millions, millions of guys in China who will 243 00:14:53,680 --> 00:14:57,520 Speaker 1: not be able to find a spouse a girlfriend because 244 00:14:57,560 --> 00:15:01,640 Speaker 1: of the number of difference these guys who are all 245 00:15:01,680 --> 00:15:05,800 Speaker 1: candidates for buying these robots. Well, and of course a 246 00:15:05,840 --> 00:15:11,040 Speaker 1: lot of people already, um, you know, have bots online, 247 00:15:11,080 --> 00:15:14,120 Speaker 1: you know, software bots, not actual robots that have you know, 248 00:15:14,120 --> 00:15:18,000 Speaker 1: physical bodies, um that they interact with all the time. Um, 249 00:15:18,080 --> 00:15:21,600 Speaker 1: And sometimes they don't even realize that those bots aren't people. 250 00:15:21,800 --> 00:15:23,480 Speaker 1: You know, they think that they're just a person, that 251 00:15:23,520 --> 00:15:27,440 Speaker 1: they're talking to So I think you know, when you're 252 00:15:27,480 --> 00:15:31,320 Speaker 1: lonely and you want companionship, um, you know it's healthy 253 00:15:31,400 --> 00:15:34,960 Speaker 1: to want to reach out to another being. Um. And 254 00:15:35,080 --> 00:15:37,680 Speaker 1: so it makes sense that people are going to turn 255 00:15:37,720 --> 00:15:42,160 Speaker 1: to robots and bots which can strange infinitely. They can 256 00:15:42,160 --> 00:15:46,240 Speaker 1: be infinitely patient and kind. It'll be a cheap date, 257 00:15:46,360 --> 00:15:49,720 Speaker 1: that's for sure. You don't have to buy dinner. Depends, right, 258 00:15:50,640 --> 00:15:52,880 Speaker 1: What would be better if you were a company then 259 00:15:52,920 --> 00:15:55,440 Speaker 1: to like design a robot that would then ask its 260 00:15:55,480 --> 00:16:00,000 Speaker 1: human companion, like to buy an expensive diamond or expensive 261 00:16:00,040 --> 00:16:03,000 Speaker 1: yeahthing right, that's right. That's the next thing is your 262 00:16:03,000 --> 00:16:05,520 Speaker 1: sex spot is going to have like Sam and say like, 263 00:16:05,640 --> 00:16:08,320 Speaker 1: don't you want to buy me brand new shoes? Buy 264 00:16:08,360 --> 00:16:13,080 Speaker 1: me a Chanel purse? Exactly. That's weird. Listen to more 265 00:16:13,160 --> 00:16:16,720 Speaker 1: Coast to Coast AM every weeknight at one am Eastern 266 00:16:16,960 --> 00:16:19,400 Speaker 1: and go to Coast to Coast am dot com for 267 00:16:19,480 --> 00:16:19,720 Speaker 1: more