1 00:00:00,200 --> 00:00:03,480 Speaker 1: Now here's a highlight from Coast to Coast am on 2 00:00:03,560 --> 00:00:07,320 Speaker 1: iHeartRadio and welcome back to Coast to Coast. Matthew Crawford 3 00:00:07,360 --> 00:00:10,680 Speaker 1: is a mechanic author of Shop Class at south Craft. 4 00:00:11,039 --> 00:00:13,480 Speaker 1: He is also author of the latest book called Why 5 00:00:13,520 --> 00:00:16,880 Speaker 1: We Drive, which is an incredible book. The latest book, 6 00:00:16,920 --> 00:00:20,400 Speaker 1: of course, is about, you know, his philosophy of the 7 00:00:20,400 --> 00:00:23,720 Speaker 1: open road. He majored in physics at UC Santa Barbara 8 00:00:23,720 --> 00:00:27,560 Speaker 1: earned a PhD in political philosophy from the University of Chicago. 9 00:00:27,880 --> 00:00:31,120 Speaker 1: And Matthew, I gotta believe you love driving cars, don't you. 10 00:00:32,040 --> 00:00:38,240 Speaker 1: I do. Thanks for having me on the show. George, Yeah, cars, motorcycles, skateboards, 11 00:00:39,520 --> 00:00:44,160 Speaker 1: name what was the first car you ever owned? First 12 00:00:44,159 --> 00:00:48,640 Speaker 1: car I had was a nineteen sixty three Beatle and 13 00:00:48,920 --> 00:00:51,360 Speaker 1: I bought it before I even had a driver's license. 14 00:00:52,040 --> 00:00:56,240 Speaker 1: I was already working at a Porsche shop, just doing 15 00:00:56,320 --> 00:01:00,000 Speaker 1: kind of menial labor, and a VW Bug was about 16 00:01:00,120 --> 00:01:01,760 Speaker 1: close as I was going to get to a Porsche. 17 00:01:02,200 --> 00:01:04,640 Speaker 1: I got a Mine was a nineteen sixty eight Ford 18 00:01:04,760 --> 00:01:08,880 Speaker 1: Mustang brand new. Dad worked at Ford Motor Company in Dearborn, 19 00:01:09,440 --> 00:01:12,240 Speaker 1: and he got a substantial discount, and he said this 20 00:01:12,319 --> 00:01:14,640 Speaker 1: is going to be for your high school graduation present, 21 00:01:15,120 --> 00:01:18,399 Speaker 1: and he buys me this beautiful blue Mustang, which I 22 00:01:18,440 --> 00:01:22,920 Speaker 1: wish I still kept. Nice. Those were fun times. Tell 23 00:01:22,920 --> 00:01:26,720 Speaker 1: me about your work and what you've been doing. Well, 24 00:01:26,760 --> 00:01:31,720 Speaker 1: I've just written this book Why We Drive, and it's 25 00:01:31,760 --> 00:01:34,520 Speaker 1: a number of things. I guess I'm just very intrigued 26 00:01:34,600 --> 00:01:38,800 Speaker 1: by driving. I think it's an interesting activity that calls 27 00:01:38,840 --> 00:01:43,560 Speaker 1: on a lot of human capacities that we don't always 28 00:01:43,600 --> 00:01:48,640 Speaker 1: think about. It just becomes kind of automatic. But I 29 00:01:48,680 --> 00:01:53,480 Speaker 1: guess what prompted the inquiry partly was this big push 30 00:01:53,520 --> 00:01:57,200 Speaker 1: for driverless car. Oh boy, I know, well you just 31 00:01:57,280 --> 00:02:00,360 Speaker 1: heard that study I just had that these dry less 32 00:02:00,400 --> 00:02:04,280 Speaker 1: cars aren't all that they're because you made up to be. Yeah, 33 00:02:04,320 --> 00:02:09,040 Speaker 1: there's been a lot of hype surrounding this, and one 34 00:02:09,040 --> 00:02:12,720 Speaker 1: thing that has become clear is that the push for 35 00:02:12,840 --> 00:02:16,960 Speaker 1: driverless cars is not a response to consumer demand. It's 36 00:02:17,000 --> 00:02:20,240 Speaker 1: not like people are clamoring for this. It's more of 37 00:02:20,280 --> 00:02:24,919 Speaker 1: a top down project. So like when Pew has asked 38 00:02:25,320 --> 00:02:29,560 Speaker 1: done surveys asking people about their attitudes, they still don't 39 00:02:29,600 --> 00:02:33,680 Speaker 1: trust the technology. Also, when you ask people if they 40 00:02:33,800 --> 00:02:37,519 Speaker 1: like to drive or thinks a chore about a third 41 00:02:37,680 --> 00:02:40,880 Speaker 1: think it's a chore, and about two thirds seem to 42 00:02:40,960 --> 00:02:44,040 Speaker 1: enjoy it. Next hour, we're gonna put up our phone lines, Matthew, 43 00:02:44,200 --> 00:02:46,480 Speaker 1: and one of the groups I'm going to ask to 44 00:02:46,600 --> 00:02:50,440 Speaker 1: call you are truck drivers, because there's also that big 45 00:02:50,480 --> 00:02:55,120 Speaker 1: movement for driverless trucks. And is this an effort to 46 00:02:55,160 --> 00:02:58,400 Speaker 1: save money? I mean, why would they even think about 47 00:02:58,560 --> 00:03:04,040 Speaker 1: driverless vehicles? What's the benefit? Well, you mentioned trucks there, 48 00:03:04,040 --> 00:03:06,360 Speaker 1: it seems like, I mean, obviously the point is to 49 00:03:06,360 --> 00:03:10,480 Speaker 1: get rid of truck drivers. Yeah, even but more broadly, 50 00:03:10,840 --> 00:03:15,000 Speaker 1: there's this premise that human beings are terrible drivers. That's 51 00:03:15,040 --> 00:03:20,600 Speaker 1: the sort of that's what you hear, and you know, 52 00:03:20,720 --> 00:03:25,600 Speaker 1: so it's a kind of technocratic project to idiot proof everything, 53 00:03:26,040 --> 00:03:30,280 Speaker 1: and they proceed by treating us like idiots. And there's 54 00:03:30,280 --> 00:03:33,160 Speaker 1: a kind of vicious circle here where the more you 55 00:03:33,240 --> 00:03:39,160 Speaker 1: automate things, the more our skills atrophy for lack of youth, 56 00:03:39,400 --> 00:03:44,720 Speaker 1: which leads to demands for further automation. So, you know, 57 00:03:44,760 --> 00:03:47,800 Speaker 1: at that endpoint of that trajectory, we're just kind of 58 00:03:47,880 --> 00:03:53,320 Speaker 1: passive and dependent creatures. Somewhere in the great unknown, somebody 59 00:03:53,360 --> 00:03:56,440 Speaker 1: came up with the initial idea for driverless vehicles. Who 60 00:03:56,520 --> 00:03:59,680 Speaker 1: might that have been? Do we know? Oh boy? I 61 00:03:59,720 --> 00:04:01,560 Speaker 1: mean you can go all the way back to like 62 00:04:01,600 --> 00:04:06,400 Speaker 1: the Jetsons cartoon, right, yeah, Well, something we've been imagining 63 00:04:06,520 --> 00:04:09,760 Speaker 1: forever and somehow we identify it with the future. What 64 00:04:09,800 --> 00:04:12,560 Speaker 1: happened to jet packs? Though I could, personally I would 65 00:04:13,400 --> 00:04:16,440 Speaker 1: those would have been fun. Yeah, I'd end up probably 66 00:04:16,480 --> 00:04:19,680 Speaker 1: burning my heinie with one of those things, But it 67 00:04:19,680 --> 00:04:21,880 Speaker 1: would be great to be able to just go show 68 00:04:22,160 --> 00:04:23,920 Speaker 1: and you're where are you going to get? But think 69 00:04:23,960 --> 00:04:26,520 Speaker 1: about if you ever got into an accident with somebody 70 00:04:26,560 --> 00:04:33,800 Speaker 1: else up there, You're gone unless you had a parachute. Yeah, yeah, yeah, 71 00:04:33,800 --> 00:04:36,599 Speaker 1: I don't think we're ready for jetpacks. Were we've become 72 00:04:36,640 --> 00:04:40,760 Speaker 1: too dumb? But I mean, I mean, is there an egon, Well, 73 00:04:41,240 --> 00:04:44,440 Speaker 1: let's push the truck drivers aside for a moment. Is 74 00:04:44,440 --> 00:04:50,840 Speaker 1: there an economic benefit to the passenger driverless cars? Well, 75 00:04:50,880 --> 00:04:52,720 Speaker 1: I mean, think about it. These cars are going to 76 00:04:52,760 --> 00:04:57,039 Speaker 1: be very expensive. Part of those costs will be a 77 00:04:57,120 --> 00:05:02,040 Speaker 1: public cost because what we're talking about is really redoing 78 00:05:02,080 --> 00:05:06,000 Speaker 1: the whole road infrastructure to accommodate these things. Won't they 79 00:05:06,040 --> 00:05:09,400 Speaker 1: need some kind of electric whole system in the pavement, Well, 80 00:05:09,440 --> 00:05:11,719 Speaker 1: there are to be a bunch of sensors in the pavement, 81 00:05:11,960 --> 00:05:14,040 Speaker 1: you know that they'll pick up as they go along. 82 00:05:14,600 --> 00:05:18,640 Speaker 1: And the thing is that all the sort of promised 83 00:05:18,880 --> 00:05:23,200 Speaker 1: gains in traffic flow, which is you know, that's a 84 00:05:23,320 --> 00:05:29,080 Speaker 1: real possibility. To realize those gains, you have to have 85 00:05:29,200 --> 00:05:32,800 Speaker 1: essentially everybody in a driverless car, because they have to 86 00:05:32,880 --> 00:05:36,600 Speaker 1: coordinate with one another, and you can't have you know, 87 00:05:37,000 --> 00:05:40,479 Speaker 1: people like you and me dashing in between them and 88 00:05:40,520 --> 00:05:44,000 Speaker 1: their Mustang and messing up the whole thing. So it 89 00:05:44,080 --> 00:05:50,240 Speaker 1: kind of pushes toward all or nothing. And there's this 90 00:05:50,320 --> 00:05:54,440 Speaker 1: in one incident where a Google car came up to 91 00:05:54,520 --> 00:05:58,880 Speaker 1: an intersection and it came to a stop. It was 92 00:05:58,920 --> 00:06:02,440 Speaker 1: a four way stop, and so it was waiting for 93 00:06:02,480 --> 00:06:04,920 Speaker 1: the other cars to come to a complete stop before 94 00:06:05,040 --> 00:06:08,480 Speaker 1: going through, because you know, it's a rule follower, it's 95 00:06:08,480 --> 00:06:12,080 Speaker 1: a robot. But of course that's not what people do. 96 00:06:13,120 --> 00:06:15,160 Speaker 1: They don't come to a complete stop. So the car 97 00:06:15,240 --> 00:06:18,600 Speaker 1: got paralyzed. It just sort of froze and melted down there. 98 00:06:19,320 --> 00:06:22,200 Speaker 1: And the head Google guy in charge, he said that 99 00:06:22,320 --> 00:06:25,200 Speaker 1: what he had learned from this is that human beings 100 00:06:25,440 --> 00:06:29,560 Speaker 1: need to be less idiotic. Oh, by which he meant 101 00:06:29,839 --> 00:06:33,920 Speaker 1: they need to act more like robots. And that's I 102 00:06:33,920 --> 00:06:36,919 Speaker 1: think that's a conclusion that comes very easily if you 103 00:06:37,040 --> 00:06:41,560 Speaker 1: regard the mind as basically an inferior version of the computer. 104 00:06:41,839 --> 00:06:44,600 Speaker 1: What about the poor woman back in March of twenty eighteen, 105 00:06:44,640 --> 00:06:47,680 Speaker 1: the forty nine year old lady from Arizona who gets 106 00:06:47,760 --> 00:06:51,320 Speaker 1: killed by a self driving uber car because it wasn't 107 00:06:51,320 --> 00:06:54,760 Speaker 1: able to recognize that the pedestrian had a jaywalk and 108 00:06:54,960 --> 00:06:58,839 Speaker 1: was you know, jaywalking, and you know, hit the lady 109 00:06:58,839 --> 00:07:01,840 Speaker 1: and killed her. Yeah, there's been a few of those incidents. 110 00:07:02,200 --> 00:07:04,680 Speaker 1: But think about how much pressure there is to be 111 00:07:04,839 --> 00:07:08,440 Speaker 1: first to market with this stuff, because whoever gets there 112 00:07:08,520 --> 00:07:11,280 Speaker 1: first is going to be basically a monopoly because it's 113 00:07:11,320 --> 00:07:14,320 Speaker 1: one of these sort of platform type Is it going 114 00:07:14,360 --> 00:07:19,480 Speaker 1: to happen, Matthew, I think it's way off, and I 115 00:07:19,520 --> 00:07:23,640 Speaker 1: think there's enough kind of skepticism building now. I think 116 00:07:23,680 --> 00:07:26,480 Speaker 1: some of the investors are starting to pull out and 117 00:07:26,520 --> 00:07:31,760 Speaker 1: we're realizing just how expensive and kind of unnecessary this is, 118 00:07:31,800 --> 00:07:35,640 Speaker 1: because in fact, you know, human beings are pretty good 119 00:07:35,640 --> 00:07:38,920 Speaker 1: at doing this. We've figured it out, and I've happened 120 00:07:38,920 --> 00:07:42,040 Speaker 1: to like getting into a car when I drive, taking 121 00:07:42,160 --> 00:07:44,640 Speaker 1: some time to think about my day's events, what I'm 122 00:07:44,640 --> 00:07:47,760 Speaker 1: going to do while I'm paying attention to traffic and 123 00:07:48,240 --> 00:07:52,640 Speaker 1: knock on wood, things have been safe. But I'd like driving. 124 00:07:52,720 --> 00:07:57,400 Speaker 1: I think it's relaxing, don't you. Yeah, and think, I mean, 125 00:07:57,440 --> 00:07:59,400 Speaker 1: think about a road trip where you may not even 126 00:08:00,320 --> 00:08:03,840 Speaker 1: have a definite destination in mind, but there's just kind 127 00:08:03,880 --> 00:08:07,720 Speaker 1: of throwing yourself out into the world. You're roaming, And 128 00:08:09,000 --> 00:08:13,040 Speaker 1: I find roaming like the best kind of antidote to 129 00:08:13,760 --> 00:08:17,920 Speaker 1: the confinement of work and family. And you know, there's 130 00:08:17,920 --> 00:08:21,000 Speaker 1: something about getting out on the road that it just 131 00:08:21,160 --> 00:08:25,679 Speaker 1: kind of rejuvenates you. Technically, Matthew, how do driverless vehicles work? 132 00:08:27,600 --> 00:08:30,840 Speaker 1: You get in it, You get in it. What happens? Well, 133 00:08:30,880 --> 00:08:37,960 Speaker 1: they've got they're bristling with sensors like a dozen cameras, lightar, 134 00:08:38,280 --> 00:08:43,480 Speaker 1: which is a form of radar, basically sound sensors. And 135 00:08:43,640 --> 00:08:46,280 Speaker 1: then each one of these has to be basically a 136 00:08:46,440 --> 00:08:51,520 Speaker 1: rolling supercomputer to process all this data in real time. 137 00:08:51,559 --> 00:08:55,199 Speaker 1: And we're talking just gobs and gobs of data. Are 138 00:08:55,240 --> 00:08:58,960 Speaker 1: they electric or gasoline? Oh? Well, they could be either. 139 00:08:59,120 --> 00:09:01,319 Speaker 1: You know. The the type of power plant they have 140 00:09:01,559 --> 00:09:06,800 Speaker 1: is sort of irrelevant to the driver list Okay, yeah, 141 00:09:07,120 --> 00:09:11,800 Speaker 1: who fills up the tank if it's got gasoline needs? Well, 142 00:09:12,000 --> 00:09:17,640 Speaker 1: the driver lists the driver. I mean, what happens we're 143 00:09:17,640 --> 00:09:21,920 Speaker 1: gonna have We're gonna have driverless gasoline stations one day too. Yeah, 144 00:09:22,120 --> 00:09:25,600 Speaker 1: A se questions like that. Um, I don't think it's 145 00:09:25,600 --> 00:09:29,560 Speaker 1: all been worked out. And how does the car start? 146 00:09:30,360 --> 00:09:32,319 Speaker 1: I mean our car? Now you've got a key or 147 00:09:32,360 --> 00:09:34,959 Speaker 1: a push button, you start your car and off you go. 148 00:09:35,080 --> 00:09:38,720 Speaker 1: I mean, how's how's the car gonna start? Yeah? Maybe 149 00:09:38,720 --> 00:09:42,120 Speaker 1: it'll be like a computer where you push the start 150 00:09:42,320 --> 00:09:45,079 Speaker 1: button both to stop it and to start it. And 151 00:09:45,200 --> 00:09:48,719 Speaker 1: who's going to start it? Yeah? Well I don't know. 152 00:09:48,880 --> 00:09:55,880 Speaker 1: Presumably the operator would have some control. What operator? I mean, 153 00:09:55,920 --> 00:09:58,600 Speaker 1: what if you have an Uber out there? Where's where's 154 00:09:58,640 --> 00:10:01,560 Speaker 1: it coming from? Who's going to start it up? Who's 155 00:10:01,600 --> 00:10:06,280 Speaker 1: going to stop it? Yeah? Well the Yeah, you're asking 156 00:10:06,320 --> 00:10:11,120 Speaker 1: the right questions. And you mentioned Uber. Um so so 157 00:10:11,400 --> 00:10:16,880 Speaker 1: one effect of Uber and the other ride hailing apps 158 00:10:17,559 --> 00:10:21,199 Speaker 1: has been a big increase in congestion because think about it, 159 00:10:21,320 --> 00:10:24,199 Speaker 1: you you you know, a car shows up within a 160 00:10:24,320 --> 00:10:27,920 Speaker 1: few minutes, almost like magic, and the only way they're 161 00:10:27,920 --> 00:10:30,599 Speaker 1: able to do that is to flood the streets with 162 00:10:31,240 --> 00:10:35,640 Speaker 1: um with cars. And in New York City from twenty 163 00:10:35,960 --> 00:10:40,160 Speaker 1: thirteen to seventeen, when the city was sort of getting uberized, 164 00:10:41,040 --> 00:10:45,200 Speaker 1: the number of four higher vehicles increased by fifty nine 165 00:10:45,280 --> 00:10:49,320 Speaker 1: percent and the number of unoccupied vehicles went up by 166 00:10:49,440 --> 00:10:53,280 Speaker 1: eighty one percent. Geez. So, so the you know, like 167 00:10:53,360 --> 00:10:59,120 Speaker 1: the New York City Transportation Department is is very upset 168 00:10:59,160 --> 00:11:02,079 Speaker 1: about this, and for reason. And then meanwhile the subway 169 00:11:02,200 --> 00:11:06,600 Speaker 1: is crumbling right for lack of investment. Has Uber killed 170 00:11:06,840 --> 00:11:09,560 Speaker 1: the cab business? I don't know what the numbers are, 171 00:11:09,679 --> 00:11:14,719 Speaker 1: but I'm just really tried. Yeah, and unless this, you know, 172 00:11:15,080 --> 00:11:18,160 Speaker 1: the various jurisdictions step up and try to offer some 173 00:11:18,400 --> 00:11:23,959 Speaker 1: kind of protection, yeah, and more sort of even competitive 174 00:11:24,840 --> 00:11:27,960 Speaker 1: playing field. And the thing about it is so ubers 175 00:11:27,960 --> 00:11:30,240 Speaker 1: are super cheap, right, They are often about half the 176 00:11:30,320 --> 00:11:33,160 Speaker 1: price of a cat, Yes, exactly. So you ask, how 177 00:11:33,280 --> 00:11:39,640 Speaker 1: is that possible? Well, a transportation consultant did a study 178 00:11:40,000 --> 00:11:46,000 Speaker 1: of Uber's economics and discovered that the only reason they 179 00:11:46,040 --> 00:11:50,360 Speaker 1: can charge such low fares is because of massive subsidies 180 00:11:51,000 --> 00:11:55,240 Speaker 1: by the early investors. So, in the words, the investors 181 00:11:55,320 --> 00:11:58,120 Speaker 1: are are paying your fare, or about half of it 182 00:11:59,200 --> 00:12:02,559 Speaker 1: and there's this it's not like Uber has discovered efficiencies 183 00:12:02,679 --> 00:12:10,440 Speaker 1: that previously eluded the taxi industry. So so later investors, 184 00:12:10,559 --> 00:12:14,520 Speaker 1: now you know, the company sort of grew exponentially, and 185 00:12:14,679 --> 00:12:20,640 Speaker 1: that attracts further investment, and so basically at that point 186 00:12:20,679 --> 00:12:25,520 Speaker 1: it becomes like a Ponzi scheme with later investors taking 187 00:12:25,559 --> 00:12:29,880 Speaker 1: out the ones that came in. Yeah, yeah, I don't know, man, 188 00:12:30,000 --> 00:12:32,520 Speaker 1: that's something else. And then you know, lift, but who 189 00:12:32,600 --> 00:12:35,240 Speaker 1: is asleep at the cab companies who should have come 190 00:12:35,360 --> 00:12:38,280 Speaker 1: up with an Uber type app for yellow cab and 191 00:12:38,400 --> 00:12:41,679 Speaker 1: places like that. Yeah, no, no, you're right, because it's 192 00:12:41,679 --> 00:12:44,400 Speaker 1: not it's not like a complicated technology. It isn't really 193 00:12:44,440 --> 00:12:48,439 Speaker 1: a technology that's doing this. It's more a form of 194 00:12:48,760 --> 00:12:53,520 Speaker 1: kind of labor arbitrage where you're taking these sort of 195 00:12:53,880 --> 00:12:59,400 Speaker 1: gig economy drivers who aren't really invested in the job. Furthermore, 196 00:12:59,679 --> 00:13:03,400 Speaker 1: there usually leasing their cars and they get tied into 197 00:13:03,480 --> 00:13:08,640 Speaker 1: these often pretty abusive lease agreements that it's very hard 198 00:13:08,679 --> 00:13:11,599 Speaker 1: to get out of. And so now you're basically like 199 00:13:11,720 --> 00:13:16,160 Speaker 1: a sharecropper working for Uber. And you know, they're often immigrants, 200 00:13:16,200 --> 00:13:19,760 Speaker 1: they're not very savvy financially, so they don't quite know 201 00:13:19,840 --> 00:13:23,120 Speaker 1: what they're getting into, right, but they need a job, 202 00:13:23,240 --> 00:13:25,679 Speaker 1: they need quick money, and it's a quick way to 203 00:13:25,760 --> 00:13:27,920 Speaker 1: do it because I'm told by some of the drivers 204 00:13:28,400 --> 00:13:31,240 Speaker 1: that Uber or Lyft just pops the money in their 205 00:13:31,320 --> 00:13:38,360 Speaker 1: bank account. That's there. Yeah, yep. Now in your book 206 00:13:38,559 --> 00:13:41,959 Speaker 1: you talk about you've traveled around to different scenes and 207 00:13:42,120 --> 00:13:45,240 Speaker 1: places like that. Well, what if you find in the 208 00:13:45,280 --> 00:13:49,160 Speaker 1: book why we drive? What was the most exciting aspect 209 00:13:49,200 --> 00:13:53,000 Speaker 1: of it for Yeah, So I went to different motorsports scenes. 210 00:13:53,080 --> 00:13:58,439 Speaker 1: It's sort of grassroots motorsports, small stuff and different kind 211 00:13:58,480 --> 00:14:03,920 Speaker 1: of automotive subculture. And one thing that was very attractive 212 00:14:04,240 --> 00:14:07,920 Speaker 1: is that um, like in this desert race they do 213 00:14:08,040 --> 00:14:11,520 Speaker 1: in Nevada, it's been going on for generations. It's the 214 00:14:11,640 --> 00:14:15,199 Speaker 1: same families come back and they manned these race checkpoints, 215 00:14:15,280 --> 00:14:19,880 Speaker 1: like the same checkpoints. Um. You know, they'll be fathers 216 00:14:19,920 --> 00:14:22,520 Speaker 1: and daughters, you know, sort of passing this on. And 217 00:14:23,880 --> 00:14:26,560 Speaker 1: they have a very keen sense of being responsible not 218 00:14:26,720 --> 00:14:29,320 Speaker 1: just for the desert, but for you know the relationship 219 00:14:29,360 --> 00:14:32,440 Speaker 1: with the townspeople and the ranchers. And it's this activity 220 00:14:32,520 --> 00:14:36,440 Speaker 1: they love and it's and it's this picture of um 221 00:14:36,840 --> 00:14:41,120 Speaker 1: of self government really because there's no bureaucracy, there's no 222 00:14:42,120 --> 00:14:45,360 Speaker 1: referee to appeal to, and you know, something goes wrong, 223 00:14:45,480 --> 00:14:50,560 Speaker 1: it's just people kind of working things out. And that 224 00:14:50,760 --> 00:14:53,000 Speaker 1: was I thought that was a nice kind of glimpse 225 00:14:53,280 --> 00:14:58,640 Speaker 1: into um, what you might call like the sort of 226 00:14:58,680 --> 00:15:03,640 Speaker 1: the nursery of the democratic character when people just learn 227 00:15:03,720 --> 00:15:07,240 Speaker 1: to cooperate and then work it out. Matthew, you've got 228 00:15:07,280 --> 00:15:09,880 Speaker 1: an issue with speed limits and red light cameras. I 229 00:15:09,880 --> 00:15:13,000 Speaker 1: don't like red light cameras, but speed limits don't bother me. 230 00:15:13,160 --> 00:15:17,040 Speaker 1: Why does it bother you? Well, not speed limits in general, 231 00:15:17,480 --> 00:15:21,720 Speaker 1: But the thing is they're often set below the sort 232 00:15:21,760 --> 00:15:25,560 Speaker 1: of reasonable speed that is dictated by the features of 233 00:15:25,640 --> 00:15:28,600 Speaker 1: the road. In fact, the former head of the National 234 00:15:28,840 --> 00:15:32,280 Speaker 1: Transportation and Safety Administration, after he quit that job, he 235 00:15:32,440 --> 00:15:35,840 Speaker 1: published a paper in which he said that most speed 236 00:15:35,920 --> 00:15:39,320 Speaker 1: limits in America are set about fifteen miles an hour 237 00:15:39,640 --> 00:15:44,640 Speaker 1: too slow. And it's interesting because the speed that people 238 00:15:44,840 --> 00:15:49,400 Speaker 1: actually drive is not very sensitive to the speed limit. 239 00:15:50,000 --> 00:15:53,280 Speaker 1: We tend to take our cues from, for example, the 240 00:15:53,360 --> 00:15:57,160 Speaker 1: width of the lanes, and there's actually a standard for 241 00:15:57,520 --> 00:15:59,880 Speaker 1: you know, if it's a fifty five mile an hour 242 00:16:00,280 --> 00:16:03,920 Speaker 1: speed limit, you have a certain lane width, and you know, 243 00:16:04,000 --> 00:16:06,000 Speaker 1: if it's narrower, you got to go slower because it's 244 00:16:06,040 --> 00:16:09,920 Speaker 1: harder to stay near the center of the lane. Well, 245 00:16:10,040 --> 00:16:15,000 Speaker 1: to take an example, the Washington George Washington Parkway in DC. 246 00:16:15,880 --> 00:16:18,640 Speaker 1: The lanes are built to the fifty five mile an 247 00:16:18,680 --> 00:16:23,320 Speaker 1: hour standard, but the speed limit is forty five, so 248 00:16:23,600 --> 00:16:27,880 Speaker 1: people are driving, you know, faster, and the speed limit 249 00:16:28,040 --> 00:16:31,800 Speaker 1: is deliberately set in order to sort of maximize infractions. 250 00:16:32,360 --> 00:16:37,119 Speaker 1: And as a notorious speed trap. We've got a situation 251 00:16:37,240 --> 00:16:41,320 Speaker 1: that because of COVID nineteen, so many people are outside 252 00:16:41,320 --> 00:16:44,680 Speaker 1: of their houses jogging and walking their dogs and stuff 253 00:16:44,720 --> 00:16:48,000 Speaker 1: because they're tired of being cooped up. But at a 254 00:16:48,120 --> 00:16:53,440 Speaker 1: certain time, going west in my neighborhood, the sun is 255 00:16:53,560 --> 00:16:57,120 Speaker 1: just notorious at four or five o'clock. And if you've 256 00:16:57,200 --> 00:17:00,880 Speaker 1: got hundreds of people out jogging and walking stuff, a 257 00:17:01,000 --> 00:17:04,040 Speaker 1: lot of them, Matthew, don't really pay attention to you, 258 00:17:04,400 --> 00:17:06,879 Speaker 1: and so they'll just walk right across the street. And 259 00:17:07,000 --> 00:17:09,320 Speaker 1: I got to tell you, with the sun hitting you 260 00:17:09,480 --> 00:17:12,000 Speaker 1: right in the eyes and all these people out there, 261 00:17:12,440 --> 00:17:15,080 Speaker 1: you've got to be really careful because you can't see 262 00:17:15,119 --> 00:17:17,840 Speaker 1: these people, not even it's and it's so easy to 263 00:17:17,960 --> 00:17:22,440 Speaker 1: hit somebody. Yeah, there's really no substitute for paying attention, 264 00:17:22,920 --> 00:17:26,159 Speaker 1: and that's kind of that's a big crisis, right, distracted 265 00:17:26,240 --> 00:17:30,359 Speaker 1: driving because once the smartphone came along, oh my god, no, 266 00:17:30,800 --> 00:17:35,159 Speaker 1: it's like this dopamine candy coming at you, and the 267 00:17:35,440 --> 00:17:38,440 Speaker 1: windshield just starts to seem like one more screen, but 268 00:17:38,600 --> 00:17:41,520 Speaker 1: it can't compete with the stuffness on your phone. So 269 00:17:42,320 --> 00:17:45,040 Speaker 1: that's a real problem. Listen to more Coast to Coast 270 00:17:45,119 --> 00:17:48,760 Speaker 1: AM every weeknight at one am Eastern, and go to 271 00:17:48,840 --> 00:17:50,920 Speaker 1: Coast to Coast am dot com for more