1 00:00:15,356 --> 00:00:22,956 Speaker 1: Pushkin. Hello everyone, I'm backed with the Visionist Histories ombusman 2 00:00:23,516 --> 00:00:28,036 Speaker 1: Mariya Kanikova. This is our third round and she's here 3 00:00:28,476 --> 00:00:30,396 Speaker 1: to grill me on the six part series we just 4 00:00:30,436 --> 00:00:33,556 Speaker 1: wrapped up on Guns in America. This is a mail 5 00:00:33,556 --> 00:00:37,036 Speaker 1: bag in the truest sense of the word. We received 6 00:00:37,036 --> 00:00:40,716 Speaker 1: an unprecedented amount of listener mail in this series, and 7 00:00:40,756 --> 00:00:44,356 Speaker 1: Maria's come prepared with a whole slew of your feedback. 8 00:00:45,356 --> 00:00:48,076 Speaker 1: Some nice, that's so nice. 9 00:00:48,196 --> 00:00:53,436 Speaker 2: Yeah, well, I am surprised at how much nice we got, 10 00:00:53,996 --> 00:00:59,156 Speaker 2: considering the subject of this particular season of Revisionist History. 11 00:00:59,396 --> 00:01:03,996 Speaker 2: To be perfectly honest, so let's start with something really 12 00:01:04,116 --> 00:01:05,156 Speaker 2: nice and positive. 13 00:01:05,316 --> 00:01:06,716 Speaker 1: Get the good stuff up takes. 14 00:01:06,556 --> 00:01:10,116 Speaker 2: Exactly exactly, you know the praise sound which, right, that's 15 00:01:10,116 --> 00:01:14,996 Speaker 2: the feedback sandwich. But you had a relatively light episode 16 00:01:14,996 --> 00:01:21,236 Speaker 2: in there about gun smoke, and someone wrote in being 17 00:01:21,316 --> 00:01:24,076 Speaker 2: a little bit worried that you got the murder rate 18 00:01:24,196 --> 00:01:29,596 Speaker 2: wrong when you calculated the murders, which I bring this, yes, 19 00:01:29,636 --> 00:01:34,596 Speaker 2: all right, So basically you had this episode where you 20 00:01:34,636 --> 00:01:37,716 Speaker 2: talked about the show that ran for how many years? 21 00:01:38,356 --> 00:01:44,836 Speaker 2: Twenty years, right, almost twenty years, and your producer Tali 22 00:01:44,876 --> 00:01:51,396 Speaker 2: Emlin actually went through several seasons of it and calculated 23 00:01:51,636 --> 00:01:54,476 Speaker 2: what the murder rate would be, and you found that 24 00:01:54,596 --> 00:01:58,516 Speaker 2: it would actually, even though it's insane, it is actually 25 00:01:58,676 --> 00:02:04,476 Speaker 2: eighty times higher than what it would be in any 26 00:02:04,796 --> 00:02:08,636 Speaker 2: city in the United States today. Yes, but it turns 27 00:02:08,676 --> 00:02:12,596 Speaker 2: out that you might have actually undercounted. According to this listener. 28 00:02:12,876 --> 00:02:16,956 Speaker 2: So here's the letter, the murder rate in Dodge City 29 00:02:17,236 --> 00:02:20,956 Speaker 2: was even worse than you calculated. You compared a season 30 00:02:20,956 --> 00:02:24,516 Speaker 2: of the show to an annual rate of modern day cities. However, 31 00:02:24,676 --> 00:02:28,116 Speaker 2: each episode probably takes place in a single day or 32 00:02:28,156 --> 00:02:32,916 Speaker 2: so the entire season probably only covered a couple months 33 00:02:32,956 --> 00:02:36,716 Speaker 2: of time. That would make the annual rate five to 34 00:02:36,916 --> 00:02:41,036 Speaker 2: six times worse than you already calculated. So what do 35 00:02:41,076 --> 00:02:41,716 Speaker 2: we think about that? 36 00:02:42,516 --> 00:02:47,356 Speaker 1: Okay, I get where this critique is coming from. I 37 00:02:47,356 --> 00:02:49,636 Speaker 1: think some merit to it. I would point out, though, 38 00:02:49,716 --> 00:02:52,236 Speaker 1: when I asked Ally about this, she says, if you 39 00:02:52,316 --> 00:02:54,796 Speaker 1: look at the first two seasons, so we have an 40 00:02:54,836 --> 00:02:57,756 Speaker 1: episode said in summer, we have one in winter, we 41 00:02:57,796 --> 00:03:01,556 Speaker 1: have one on Christmas, We've got a blizzard. So they 42 00:03:01,556 --> 00:03:05,756 Speaker 1: are kind of implying that what we're seeing unfolding in 43 00:03:05,756 --> 00:03:10,276 Speaker 1: the mythical Dodge City is real passage of time and 44 00:03:10,316 --> 00:03:13,036 Speaker 1: not a series of episodes. And also, by the way, 45 00:03:13,716 --> 00:03:18,316 Speaker 1: the actors get older, right, so you know when they 46 00:03:18,596 --> 00:03:21,356 Speaker 1: when this starts, Matt Dilan's a young man. When Gun 47 00:03:21,396 --> 00:03:23,596 Speaker 1: Smoke ins, Matt Dylan is no longer a young man. 48 00:03:24,436 --> 00:03:26,556 Speaker 1: So maybe the best way to say this is that, 49 00:03:27,996 --> 00:03:30,236 Speaker 1: you know, I think we should probably split the difference 50 00:03:30,316 --> 00:03:34,476 Speaker 1: and say that we were being excessively generous to the 51 00:03:34,476 --> 00:03:37,716 Speaker 1: fictional Dodge City in suggesting that their murder rate was 52 00:03:37,756 --> 00:03:42,836 Speaker 1: only eighty times higher than the next highest American city. 53 00:03:44,236 --> 00:03:48,956 Speaker 1: And uh, you know, maybe it should. The accurate number 54 00:03:48,956 --> 00:03:50,276 Speaker 1: is one sixty. 55 00:03:51,236 --> 00:03:54,396 Speaker 2: That is absolutely crazy. By the way, I have never 56 00:03:54,436 --> 00:03:57,756 Speaker 2: seen gun Smoke, and I had to look it up. 57 00:03:58,316 --> 00:04:01,636 Speaker 2: The first time I heard of it was on your show. 58 00:04:02,196 --> 00:04:04,636 Speaker 1: And I act you get for growing up in Russia. 59 00:04:04,676 --> 00:04:08,156 Speaker 2: This is true. But I also had this like brain 60 00:04:08,276 --> 00:04:11,676 Speaker 2: fart moment where Matt Dylan. I was like, wait, but 61 00:04:11,716 --> 00:04:13,196 Speaker 2: Matt Dylan isn't that old. 62 00:04:14,036 --> 00:04:15,236 Speaker 1: Oh you would think of the other man. 63 00:04:15,596 --> 00:04:17,796 Speaker 2: I was thinking of the actor Matt Dylan, and so 64 00:04:17,996 --> 00:04:20,396 Speaker 2: for a second I was like, wait, how is Matt 65 00:04:20,476 --> 00:04:22,996 Speaker 2: Dylan in this show gun Smoke? And it was just 66 00:04:23,036 --> 00:04:26,076 Speaker 2: like this this total fictional universe that I created in 67 00:04:26,116 --> 00:04:29,276 Speaker 2: my head before I looked up what it actually was. 68 00:04:29,476 --> 00:04:33,556 Speaker 1: Years ago, maybe thirty thirty, maybe twenty five. I'm at 69 00:04:33,596 --> 00:04:36,796 Speaker 1: a party in the West Village and I realized Matt 70 00:04:36,796 --> 00:04:39,516 Speaker 1: Dillon is there when he was really at the height 71 00:04:39,556 --> 00:04:41,236 Speaker 1: of his fame. He's still famous, but he was very 72 00:04:41,916 --> 00:04:46,596 Speaker 1: I ingratiated myself with him and spent a delightful evening. 73 00:04:46,596 --> 00:04:49,916 Speaker 1: It went well past evening, I said, I spent a 74 00:04:49,956 --> 00:04:53,276 Speaker 1: delightful evening in his company, and I can testify that 75 00:04:53,356 --> 00:04:56,116 Speaker 1: he is everybody's charming in real life as he would 76 00:04:56,556 --> 00:04:58,196 Speaker 1: as the movies was jest he would be. 77 00:04:58,396 --> 00:05:00,396 Speaker 2: That's wonderful. Was he named after the show? 78 00:05:01,076 --> 00:05:04,196 Speaker 1: Well, I think it's obvious he was, right, Yeah, because 79 00:05:04,196 --> 00:05:09,356 Speaker 1: he kind of does. He looks not unlike the the 80 00:05:09,396 --> 00:05:12,476 Speaker 1: fictional Matt Dill. Maybe his parents had a notion, but 81 00:05:12,556 --> 00:05:14,836 Speaker 1: who knows either that or like just some agent gave 82 00:05:14,876 --> 00:05:17,356 Speaker 1: it to him when he was nineteen years old. 83 00:05:17,676 --> 00:05:20,116 Speaker 2: Well, I think I think that's amazing. And you know, 84 00:05:20,156 --> 00:05:21,876 Speaker 2: to my credit, I also did not have a TV 85 00:05:21,956 --> 00:05:24,556 Speaker 2: growing up, so notice, so you know, ah, we have 86 00:05:24,596 --> 00:05:29,436 Speaker 2: that in common. So we did have this one lighthearted 87 00:05:29,596 --> 00:05:35,716 Speaker 2: reader's email, but every other email, or at least the 88 00:05:35,796 --> 00:05:38,316 Speaker 2: vast majority, were about one single episode. Do you want 89 00:05:38,316 --> 00:05:39,636 Speaker 2: to care to guess which one it was? 90 00:05:39,716 --> 00:05:41,596 Speaker 1: I'm going to guess it was the assault rifle. 91 00:05:41,316 --> 00:05:45,836 Speaker 2: Episode, and you would have guessed correctly, it's that episode. 92 00:05:46,076 --> 00:05:48,236 Speaker 1: Before you go, before you get into the let me 93 00:05:48,276 --> 00:05:52,356 Speaker 1: just say that there are things you do as journalists, 94 00:05:52,356 --> 00:05:55,596 Speaker 1: and you know this well, that are deliberate provocations. You 95 00:05:55,596 --> 00:05:58,116 Speaker 1: do them precisely because you do think you are running 96 00:05:58,516 --> 00:06:03,436 Speaker 1: counter to people's expectations and preconceptions. This would be one 97 00:06:03,476 --> 00:06:07,596 Speaker 1: of those. I was poking the bear, and I guess 98 00:06:07,636 --> 00:06:11,796 Speaker 1: the bear. The bear was postfair, was duly boked. 99 00:06:12,476 --> 00:06:15,876 Speaker 2: Mission accomplished. So let's get into some of these letters, 100 00:06:15,916 --> 00:06:19,716 Speaker 2: because when you listen to excerpts from them, you start 101 00:06:19,756 --> 00:06:24,676 Speaker 2: realizing that it's as if people listened to two different episodes, 102 00:06:24,996 --> 00:06:28,356 Speaker 2: depending on where they were coming from to begin with 103 00:06:29,036 --> 00:06:33,516 Speaker 2: their own opinions about gun control colored what they heard 104 00:06:33,596 --> 00:06:37,596 Speaker 2: you say and how they experienced your interviews to a 105 00:06:37,636 --> 00:06:40,276 Speaker 2: shocking degree. I mean, actually not shocking. I'm not at 106 00:06:40,316 --> 00:06:44,756 Speaker 2: all shocked, but it's crazy reading these and seeing just 107 00:06:45,156 --> 00:06:50,836 Speaker 2: the opposite responses. So they will write things like, let's 108 00:06:50,876 --> 00:06:53,836 Speaker 2: see the gun rights guy was more genial than the 109 00:06:53,836 --> 00:06:58,316 Speaker 2: gun control guy, but he was just as misleading. All 110 00:06:58,356 --> 00:07:01,276 Speaker 2: he did was smile while he made you look left 111 00:07:01,636 --> 00:07:04,836 Speaker 2: when you should have looked to the right. And then 112 00:07:04,836 --> 00:07:08,196 Speaker 2: they have all of these figures behind that saying that, oh, well, 113 00:07:08,196 --> 00:07:11,636 Speaker 2: they're saying that, you know, he is saying that it 114 00:07:11,676 --> 00:07:15,636 Speaker 2: only takes three seconds to do this, but mass shooters 115 00:07:16,076 --> 00:07:18,436 Speaker 2: are there's going to be so much going on and 116 00:07:18,516 --> 00:07:20,476 Speaker 2: his math is wrong and this is wrong, and that 117 00:07:20,676 --> 00:07:26,236 Speaker 2: is wrong, and they say that you were led astray. 118 00:07:26,636 --> 00:07:30,676 Speaker 2: But then you have someone saying, Malcolm, you know, I'm 119 00:07:30,756 --> 00:07:33,516 Speaker 2: so proud of you for finally seeing the light now 120 00:07:33,556 --> 00:07:36,436 Speaker 2: and now I'm quoting. Now, let's remember that the problem 121 00:07:36,516 --> 00:07:41,556 Speaker 2: in America is a murder problem, not a weapon problem. 122 00:07:42,076 --> 00:07:46,516 Speaker 2: So you have two very very different points of view, right, 123 00:07:46,836 --> 00:07:50,996 Speaker 2: and let's talk about that. How can people walk away 124 00:07:51,836 --> 00:07:55,436 Speaker 2: from the same episode, listening to the same data with 125 00:07:55,796 --> 00:07:58,356 Speaker 2: just completely opposite perspectives. 126 00:07:58,436 --> 00:08:00,676 Speaker 1: Well, I mean, it shouldn't come as a surprise that 127 00:08:02,356 --> 00:08:07,476 Speaker 1: people's when people listen to something that they feel strongly about, 128 00:08:07,556 --> 00:08:12,916 Speaker 1: they have a subjective reading, nor, you know, nor does 129 00:08:12,956 --> 00:08:16,076 Speaker 1: it surprise me now after thirty years of writing books, 130 00:08:16,476 --> 00:08:21,116 Speaker 1: that people don't read or listen to the end. You know, 131 00:08:21,156 --> 00:08:24,956 Speaker 1: I wrote a book called my second book, Blink, was 132 00:08:25,276 --> 00:08:29,716 Speaker 1: a book that looked critically at When I say critically, 133 00:08:29,796 --> 00:08:32,756 Speaker 1: the examine wrote the pros and cons of snap judgments, 134 00:08:33,356 --> 00:08:36,236 Speaker 1: But you had to keep reading. It started out on 135 00:08:36,276 --> 00:08:39,996 Speaker 1: the pros and then as I dug deeper got interested 136 00:08:39,996 --> 00:08:44,316 Speaker 1: in the cons. The number of people who either supported 137 00:08:44,796 --> 00:08:47,036 Speaker 1: or loved that book or hated that book because they 138 00:08:47,116 --> 00:08:51,796 Speaker 1: perceived it as being a book about celebrating snap judgments 139 00:08:52,156 --> 00:08:54,596 Speaker 1: was limitless. You know, anytime you tell a story that 140 00:08:54,596 --> 00:08:57,196 Speaker 1: has a twist, you're going to leave some portion of 141 00:08:57,276 --> 00:09:00,076 Speaker 1: people along the way. And I think this episode is 142 00:09:00,076 --> 00:09:03,076 Speaker 1: a proof of that. Like basically where I end up 143 00:09:03,116 --> 00:09:05,716 Speaker 1: remember is you know, is a gun is a gun 144 00:09:05,756 --> 00:09:09,396 Speaker 1: as a gun. Parsing these these distinctions between gun is 145 00:09:09,436 --> 00:09:13,596 Speaker 1: a pointless exercise that leads you away from the central issue, 146 00:09:13,636 --> 00:09:17,476 Speaker 1: which is that having lots of lethal weapons floating around 147 00:09:17,716 --> 00:09:20,636 Speaker 1: in a society is not the best idea. 148 00:09:21,276 --> 00:09:24,876 Speaker 2: Right. Obviously, when you were doing these interviews, you you 149 00:09:24,916 --> 00:09:26,436 Speaker 2: know you want to do the interview, and you never 150 00:09:26,516 --> 00:09:30,116 Speaker 2: want to You don't want to antagonize a person you're interviewing. 151 00:09:30,156 --> 00:09:32,396 Speaker 2: In the middle of the interview, especially when they're holding 152 00:09:32,396 --> 00:09:36,036 Speaker 2: a gun. But I'm actually just curious from a personal perspective, 153 00:09:36,116 --> 00:09:39,676 Speaker 2: if if you care to comment, were you kind of 154 00:09:39,716 --> 00:09:44,556 Speaker 2: were you persuaded by by these arguments so that it 155 00:09:44,716 --> 00:09:49,796 Speaker 2: actually doesn't make that much of a difference, and that 156 00:09:49,876 --> 00:09:54,676 Speaker 2: you you know that that we should that were barking 157 00:09:54,756 --> 00:09:57,076 Speaker 2: up the wrong tree when we're looking at this guy legislation. 158 00:09:57,236 --> 00:10:02,236 Speaker 1: I was there two persuasive things in the reporting a persuision. 159 00:10:02,596 --> 00:10:06,596 Speaker 1: One was with my gun expert, the guy I've shot 160 00:10:06,596 --> 00:10:10,916 Speaker 1: within North Carolina, Gregg Wallace. And what's persuasive about his 161 00:10:11,116 --> 00:10:14,996 Speaker 1: discussion is not how fast you can shoot a semi 162 00:10:15,036 --> 00:10:17,436 Speaker 1: automatic weapon versus an automatic weapon, although that is the 163 00:10:17,436 --> 00:10:19,956 Speaker 1: thing is relevant. The real core issue he was getting 164 00:10:19,996 --> 00:10:24,596 Speaker 1: at is said assault rifle bands don't ban assault rifles. 165 00:10:25,276 --> 00:10:29,516 Speaker 1: They ban a subcategory of assault rifles which qualify for 166 00:10:29,556 --> 00:10:32,196 Speaker 1: the ban not because they are more lethal, but because 167 00:10:32,236 --> 00:10:35,996 Speaker 1: they have certain cosmetic features that make them unattractive or 168 00:10:36,116 --> 00:10:40,516 Speaker 1: mean looking. Right, Really, what you're getting so's his function 169 00:10:40,716 --> 00:10:43,476 Speaker 1: in the story is to remind us that, look, this 170 00:10:43,516 --> 00:10:46,476 Speaker 1: is a bullshit exercise. You may think that an assault 171 00:10:46,516 --> 00:10:49,876 Speaker 1: rifle ban bands assault rifles it does not. Right, the 172 00:10:49,916 --> 00:10:56,756 Speaker 1: fundamental platform of the AR fifteen remains untouched by these bands, right. 173 00:10:56,796 --> 00:10:58,956 Speaker 1: You can still use the basic weapon, you just can't 174 00:10:59,036 --> 00:11:02,516 Speaker 1: use some of these accessories. That's pointing with the number 175 00:11:02,516 --> 00:11:06,156 Speaker 1: two is it is not a distinction without a difference 176 00:11:06,236 --> 00:11:09,836 Speaker 1: to point out that a semi automatic weapon is not 177 00:11:09,876 --> 00:11:13,436 Speaker 1: the same as an automatic weapon. They are fundamentally different. 178 00:11:13,476 --> 00:11:17,956 Speaker 1: And if people are under the illusion that an assault 179 00:11:18,476 --> 00:11:23,996 Speaker 1: weapon is basically like a machine gun, they're wrong, right, Yeah, 180 00:11:24,036 --> 00:11:25,636 Speaker 1: And that's not a trivial mistake. 181 00:11:26,036 --> 00:11:26,236 Speaker 2: Right. 182 00:11:27,196 --> 00:11:29,476 Speaker 1: So a lot of these as I'm reading through on 183 00:11:29,516 --> 00:11:31,876 Speaker 1: this one in this one letter, a lot of them, 184 00:11:32,036 --> 00:11:36,636 Speaker 1: you know, are fussing around in the kind of minor 185 00:11:36,716 --> 00:11:39,396 Speaker 1: details of these distinctions, and it's just like, it's not 186 00:11:39,476 --> 00:11:42,516 Speaker 1: the point. The point is like, what we're setting out 187 00:11:42,556 --> 00:11:44,356 Speaker 1: to do here is not actually what we're doing A 188 00:11:44,836 --> 00:11:47,756 Speaker 1: and B. This brings us to the second persuasive character 189 00:11:47,796 --> 00:11:50,916 Speaker 1: in that the most persuasive character in that episode was 190 00:11:50,956 --> 00:11:54,156 Speaker 1: the er doctor. Yeah, the guy in DC who had 191 00:11:54,196 --> 00:11:59,956 Speaker 1: studied mass shootings and points out that the truly lethal 192 00:11:59,996 --> 00:12:02,116 Speaker 1: weapon in the hands of a mass shooter is a 193 00:12:02,156 --> 00:12:06,396 Speaker 1: handgun and not an assault rifle. And that's because what 194 00:12:06,476 --> 00:12:10,556 Speaker 1: makes a gun lethal is not just a matter of 195 00:12:10,596 --> 00:12:14,436 Speaker 1: its ballistic properties. It's a question of how it's used. 196 00:12:14,956 --> 00:12:17,916 Speaker 1: And there are so many quote unquote advantages to a 197 00:12:17,956 --> 00:12:21,396 Speaker 1: handgun in the way it's used that it makes it, 198 00:12:21,476 --> 00:12:22,996 Speaker 1: at the end of the day, a more dangerous weapon 199 00:12:23,036 --> 00:12:25,836 Speaker 1: in a mass shooting. There is a whole kind of 200 00:12:25,956 --> 00:12:32,356 Speaker 1: really weird academic subculture devoted to the analysis of mass shootings, 201 00:12:32,436 --> 00:12:35,796 Speaker 1: and you would be surprised how divergent those findings are 202 00:12:35,876 --> 00:12:40,156 Speaker 1: from a lot of our preconceptions about what happens in 203 00:12:40,196 --> 00:12:40,836 Speaker 1: a mass shooting. 204 00:12:41,596 --> 00:12:44,556 Speaker 2: That's really interesting, and I actually saw that as a 205 00:12:44,596 --> 00:12:50,036 Speaker 2: thread throughout this entire season of Revisionist History, just how 206 00:12:50,276 --> 00:12:55,076 Speaker 2: strong identity politics and our sense of who we are 207 00:12:55,116 --> 00:12:58,196 Speaker 2: and how we define ourselves is when it comes to 208 00:12:59,036 --> 00:13:02,076 Speaker 2: parsing the world and those definitional issues. 209 00:13:02,556 --> 00:13:07,236 Speaker 1: Yeah, the other moment, you know, in the assault Rifle episode, 210 00:13:07,316 --> 00:13:12,916 Speaker 1: you know, it ends with me confronting this this anti 211 00:13:12,996 --> 00:13:19,076 Speaker 1: gun lobbyist, big time opponent of the Second Amendment in Washington, 212 00:13:19,596 --> 00:13:22,476 Speaker 1: and I think the reason he gets very upset, and 213 00:13:22,596 --> 00:13:24,796 Speaker 1: actually we didn't even use the parts of the of 214 00:13:24,836 --> 00:13:27,476 Speaker 1: the conversation where he was most upset, And I think 215 00:13:27,516 --> 00:13:29,076 Speaker 1: One of the reasons he was so upset is that 216 00:13:30,036 --> 00:13:35,236 Speaker 1: I was out flanking him on the left, and I 217 00:13:35,276 --> 00:13:37,436 Speaker 1: was taking a more anti gun position than he was. 218 00:13:37,876 --> 00:13:39,796 Speaker 1: And not only that, in order to outflank him on 219 00:13:39,836 --> 00:13:43,036 Speaker 1: the left, I was using right wing arguments or right 220 00:13:43,036 --> 00:13:46,556 Speaker 1: wing facts. You know that that episode is if you 221 00:13:46,556 --> 00:13:49,796 Speaker 1: think about it structurally, that's what it is. It's taking 222 00:13:50,036 --> 00:13:53,916 Speaker 1: arguments most commonly used on the right to draw a 223 00:13:53,996 --> 00:13:56,996 Speaker 1: highly liberal conclusion. It's just confused. It's just confusing to 224 00:13:57,036 --> 00:13:57,316 Speaker 1: do that. 225 00:13:57,836 --> 00:14:01,516 Speaker 2: Malcolm, you have come a long way from your debating fiasco. 226 00:14:04,116 --> 00:14:09,116 Speaker 1: Don't even get me started. We will be right back 227 00:14:09,196 --> 00:14:11,356 Speaker 1: back more from the mailbag. 228 00:14:27,156 --> 00:14:31,076 Speaker 2: All right, well, let's go back to guns, because I 229 00:14:31,156 --> 00:14:33,716 Speaker 2: do want to talk about some of the other episodes. 230 00:14:34,236 --> 00:14:37,356 Speaker 2: I think that one theme that we haven't touched on, 231 00:14:37,516 --> 00:14:42,156 Speaker 2: but that is, you know, deeply connected to all of everything. 232 00:14:42,236 --> 00:14:46,356 Speaker 2: We have been discussing, the racial and the socioeconomic underpinnings 233 00:14:46,396 --> 00:14:49,916 Speaker 2: of all of this, and the fact that it's kind 234 00:14:49,916 --> 00:14:55,276 Speaker 2: of woven into the fabric of the country. And you know, 235 00:14:55,476 --> 00:15:00,156 Speaker 2: you you talk about in these are different episodes. There's Chicago, 236 00:15:00,316 --> 00:15:03,996 Speaker 2: you know, there's there's DC, There's and you have you 237 00:15:04,076 --> 00:15:09,436 Speaker 2: have Alabama. You have these very different geographically arts of 238 00:15:09,436 --> 00:15:15,156 Speaker 2: the country, urban rural, and yet you have some of 239 00:15:15,196 --> 00:15:21,756 Speaker 2: the exact same reasons why we have still despite all 240 00:15:21,836 --> 00:15:27,996 Speaker 2: of the incredible medical stuff that's happened, and despite how 241 00:15:27,996 --> 00:15:30,356 Speaker 2: many lives are saved now that wouldn't have been saved 242 00:15:30,356 --> 00:15:33,636 Speaker 2: in the past, we still have these huge disparities, and 243 00:15:33,796 --> 00:15:36,836 Speaker 2: we still have people dying who shouldn't be dying because 244 00:15:37,556 --> 00:15:40,156 Speaker 2: either they're the wrong color, or they're in a place 245 00:15:40,156 --> 00:15:43,636 Speaker 2: where they seem like they're the wrong color, or they're 246 00:15:43,676 --> 00:15:48,196 Speaker 2: in a place that's so economically marginalized that you know, 247 00:15:48,236 --> 00:15:52,236 Speaker 2: they can't get to a trauma center, probably because that 248 00:15:52,356 --> 00:15:55,796 Speaker 2: area was the wrong color at some point, and it's 249 00:15:55,916 --> 00:15:59,556 Speaker 2: just it's heartbreaking, but it's still the reality. 250 00:15:59,916 --> 00:16:03,876 Speaker 1: Yeah, this reminds me of I think I'm getting this right. 251 00:16:04,276 --> 00:16:07,076 Speaker 1: Something I read years ago about what is the effact 252 00:16:07,196 --> 00:16:11,876 Speaker 1: What is the effect of reading enrichment programs on test 253 00:16:11,876 --> 00:16:16,516 Speaker 1: score gaps between black and white kids? And reading the 254 00:16:16,596 --> 00:16:20,916 Speaker 1: ritual programs increase the testcore gap. They don't decrease it, 255 00:16:20,956 --> 00:16:23,796 Speaker 1: even though they're intended to decrease it. But what they 256 00:16:23,836 --> 00:16:26,716 Speaker 1: do is if you give reading enrichment to someone who 257 00:16:26,756 --> 00:16:30,476 Speaker 1: reads a lot, they're going to reap the most of 258 00:16:30,556 --> 00:16:33,356 Speaker 1: that boost. If you give a reading enrichment to someone 259 00:16:33,436 --> 00:16:35,756 Speaker 1: doesn't read much, they're not going to get much out 260 00:16:35,756 --> 00:16:38,116 Speaker 1: of it because they're not reading to begin with. So 261 00:16:38,756 --> 00:16:41,836 Speaker 1: something that we introduced as a way to narrow the 262 00:16:41,836 --> 00:16:44,316 Speaker 1: gap ends up widening the gap, which is a reminder 263 00:16:44,356 --> 00:16:47,716 Speaker 1: that not all innovations do what we have an assumption. 264 00:16:47,836 --> 00:16:50,956 Speaker 1: Sometimes I think that the purpose of an innovation is 265 00:16:50,996 --> 00:16:53,476 Speaker 1: to shrink the gap between the haves and have nots. 266 00:16:54,036 --> 00:16:57,036 Speaker 1: This is so often violated that it's time we shelve 267 00:16:57,076 --> 00:17:01,836 Speaker 1: that notion and understand that innovations are just energy. You know, 268 00:17:02,076 --> 00:17:04,236 Speaker 1: they can be put to whatever use we want, and 269 00:17:04,276 --> 00:17:07,756 Speaker 1: sometimes what they do is just turbocharge existing inequities. And 270 00:17:07,796 --> 00:17:11,796 Speaker 1: I think Caare is an example of this exact thing. 271 00:17:12,476 --> 00:17:16,676 Speaker 1: That you can't put trauma centers everywhere too expensive. You 272 00:17:16,676 --> 00:17:19,116 Speaker 1: can only put them in places where you can justify 273 00:17:19,116 --> 00:17:22,796 Speaker 1: them economically. And what are those places, Well, those are 274 00:17:22,836 --> 00:17:25,116 Speaker 1: wealthy places. Yeah, So you put them in wealthy places, 275 00:17:25,116 --> 00:17:26,916 Speaker 1: and they have the effect of making the quality of 276 00:17:27,676 --> 00:17:30,356 Speaker 1: healthcare provided in wealthy places, which was already better than 277 00:17:30,356 --> 00:17:35,516 Speaker 1: everyone else everywhere else, even better. Right, So when everyone 278 00:17:35,596 --> 00:17:37,356 Speaker 1: who goes to a hospital gets you to for a 279 00:17:37,396 --> 00:17:41,636 Speaker 1: gun shot dies. We don't notice the difference between good 280 00:17:41,676 --> 00:17:44,556 Speaker 1: hospitals and bad hospitals. But when you put a trauma 281 00:17:44,556 --> 00:17:46,276 Speaker 1: center in one of those places and you don't have 282 00:17:46,276 --> 00:17:48,516 Speaker 1: another one, then you begin to notice it's a huge difference. 283 00:17:48,596 --> 00:17:48,836 Speaker 2: Right. 284 00:17:49,276 --> 00:17:51,596 Speaker 1: I was just at something when we were talking about AI, 285 00:17:52,516 --> 00:17:55,996 Speaker 1: and everyone's you know, we're obviously very excited about the 286 00:17:56,036 --> 00:18:00,356 Speaker 1: possibility that AI will transform all manner of things. It's 287 00:18:00,396 --> 00:18:05,116 Speaker 1: really unclear whether AI lifts all boats equally, closes the 288 00:18:05,156 --> 00:18:07,436 Speaker 1: gap between haves and have nots, or widens the gap. 289 00:18:07,476 --> 00:18:10,716 Speaker 1: Pato halves no idea. Anyone who tells you that they 290 00:18:10,756 --> 00:18:13,156 Speaker 1: know which way it'll go, doesn't you know it was 291 00:18:13,196 --> 00:18:13,636 Speaker 1: fooling you. 292 00:18:14,316 --> 00:18:17,276 Speaker 2: That's that's a very good point. And I mean, if 293 00:18:17,316 --> 00:18:19,236 Speaker 2: I had to bet on one outcome or the other, 294 00:18:19,316 --> 00:18:21,276 Speaker 2: I would say probably it's not going to lift all 295 00:18:21,316 --> 00:18:25,316 Speaker 2: boats equally, just because also who's going to have access 296 00:18:25,396 --> 00:18:28,636 Speaker 2: to AI, right, and who's going to have access to 297 00:18:28,756 --> 00:18:30,956 Speaker 2: the technologies, and who's going to have the time to 298 00:18:31,036 --> 00:18:34,876 Speaker 2: learn how to use them? Yeah, so who knows? Who knows? 299 00:18:35,076 --> 00:18:39,036 Speaker 1: On that one? I'm actually an optimist, good I'm glad. Well, 300 00:18:39,076 --> 00:18:43,316 Speaker 1: at least I'll say this that over time, I would 301 00:18:43,316 --> 00:18:49,476 Speaker 1: expect it to close the gap. Not even so quite explicitly. 302 00:18:49,876 --> 00:18:52,556 Speaker 1: It's obvious to me it lifts all boats. It's obviously 303 00:18:52,556 --> 00:18:55,436 Speaker 1: in the short term, people with access to the technology 304 00:18:55,476 --> 00:18:58,116 Speaker 1: will benefit the most. So I'm interested in making a 305 00:18:58,156 --> 00:19:00,516 Speaker 1: medium to long term I think in medium to long 306 00:19:00,596 --> 00:19:03,356 Speaker 1: term it does not merely lift all boats. If I 307 00:19:03,396 --> 00:19:06,996 Speaker 1: had to put my money on something, I would say 308 00:19:07,076 --> 00:19:12,796 Speaker 1: it would close the gap that the farmer in Bangladesh 309 00:19:13,636 --> 00:19:19,076 Speaker 1: benefits more from AI than the than the factory farmer 310 00:19:19,156 --> 00:19:21,996 Speaker 1: with fifty million dollars in equipment in Iowa. 311 00:19:22,716 --> 00:19:23,436 Speaker 2: I hope you're right. 312 00:19:23,676 --> 00:19:25,756 Speaker 1: These days, I'm only really optimistic about one thing, and 313 00:19:25,796 --> 00:19:28,076 Speaker 1: that's it. Everything else is bad. 314 00:19:28,356 --> 00:19:30,476 Speaker 2: All right, All right, well, well let's cling to that. 315 00:19:31,476 --> 00:19:35,476 Speaker 2: So now back to the optimistic news of the trauma centers. 316 00:19:36,756 --> 00:19:39,516 Speaker 2: But I was one of the things that I am 317 00:19:39,556 --> 00:19:43,276 Speaker 2: curious about is how strongly do you actually agree with 318 00:19:43,316 --> 00:19:47,836 Speaker 2: this idea of moral hazard that you raise in relation 319 00:19:47,996 --> 00:19:53,156 Speaker 2: to the improvements and care, because I don't know if 320 00:19:53,196 --> 00:19:54,196 Speaker 2: I actually buy that. 321 00:19:54,356 --> 00:19:56,876 Speaker 1: You don't buy that. No, So the argument was that 322 00:19:57,436 --> 00:20:01,036 Speaker 1: doctors have become so good at saving lives that it's 323 00:20:01,116 --> 00:20:04,356 Speaker 1: relieve the pressure on the rest of society to do 324 00:20:04,436 --> 00:20:10,676 Speaker 1: something real about the gunman. Exactly that if doctors had 325 00:20:10,716 --> 00:20:15,316 Speaker 1: done nothing over the last fifty years, this is the counterfactual, 326 00:20:15,796 --> 00:20:19,596 Speaker 1: the murder rate would be. We probably have four or 327 00:20:19,636 --> 00:20:21,756 Speaker 1: five times of spending homicides in a given year. Let's 328 00:20:21,756 --> 00:20:23,836 Speaker 1: say we we'd have one hundred thousand homicides as opposed 329 00:20:23,836 --> 00:20:28,156 Speaker 1: to twenty thousand homicides, and at one hundred thousand, the 330 00:20:28,236 --> 00:20:31,636 Speaker 1: current American policy set up, policy positions would be untenable. 331 00:20:31,996 --> 00:20:34,676 Speaker 1: We would jump up and down and say enough stuff. Now, 332 00:20:35,476 --> 00:20:39,396 Speaker 1: do I think that there is some truth in that? Yes. However, 333 00:20:40,636 --> 00:20:43,436 Speaker 1: then I thought, after I'd finished the episode and I 334 00:20:43,476 --> 00:20:46,476 Speaker 1: was writing this next book, I'm working on doing something 335 00:20:46,476 --> 00:20:49,956 Speaker 1: on the opioid crisis, and I realized, Oh, we're at 336 00:20:49,956 --> 00:20:53,916 Speaker 1: one hundred and twenty thousand opioid whatever it is, one 337 00:20:53,996 --> 00:20:57,556 Speaker 1: hundred and ten thousand opioid deaths a year and hasn't 338 00:20:58,836 --> 00:21:00,676 Speaker 1: really moved the needle. We don't even talk about it. 339 00:21:00,756 --> 00:21:00,996 Speaker 2: Yep. 340 00:21:01,756 --> 00:21:09,716 Speaker 1: So, and also, opioid deaths are not dissimilar to homicide 341 00:21:09,716 --> 00:21:12,876 Speaker 1: deaths in a sense that it's clustered in various parts 342 00:21:12,876 --> 00:21:17,876 Speaker 1: of the country, various slightly younger age groups. You know, 343 00:21:18,036 --> 00:21:19,996 Speaker 1: the fact that we spend an enormous amount of time 344 00:21:20,636 --> 00:21:23,636 Speaker 1: arguing about mass shootings when mass shootings are what, less 345 00:21:23,636 --> 00:21:26,476 Speaker 1: than one percent of total homicide deaths in a given year, 346 00:21:26,796 --> 00:21:29,356 Speaker 1: and very little time on the remaining ninety nine percent, 347 00:21:29,796 --> 00:21:32,756 Speaker 1: suggests to me that maybe it wouldn't make a difference. 348 00:21:32,836 --> 00:21:34,476 Speaker 1: Maybe the moral hazard thing is just a kind of 349 00:21:34,476 --> 00:21:40,596 Speaker 1: intellectual nicety. The opioid thing would suggest that if it's 350 00:21:40,596 --> 00:21:43,636 Speaker 1: the wrong people dying, really hard to get people upset. 351 00:21:44,236 --> 00:21:47,156 Speaker 2: Yeah, I mean, that's to be perfectly honest, that's exactly 352 00:21:47,156 --> 00:21:49,036 Speaker 2: what I was thinking when I was listening to this. 353 00:21:49,156 --> 00:21:51,516 Speaker 2: I was saying, I actually think the moral hazard argument 354 00:21:51,556 --> 00:21:55,636 Speaker 2: is bullshit, and that we wouldn't care, and that it's 355 00:21:55,756 --> 00:21:59,916 Speaker 2: just these days, we also are so immune to a 356 00:21:59,916 --> 00:22:02,516 Speaker 2: lot of this stuff where you're just like, oh, yeah, 357 00:22:02,716 --> 00:22:06,116 Speaker 2: you know, I guess more people are dying, and. 358 00:22:07,356 --> 00:22:10,036 Speaker 1: Here's the so here's the let me make a let 359 00:22:10,076 --> 00:22:13,396 Speaker 1: me return, let me do another backflip and say, okay, 360 00:22:13,436 --> 00:22:17,916 Speaker 1: here's here's here's a here's a moral hazard argument, and 361 00:22:18,116 --> 00:22:22,196 Speaker 1: maybe that it's a it's a mechanism argument. So moral 362 00:22:22,196 --> 00:22:25,876 Speaker 1: hazard is as a term is used most frequently in. 363 00:22:25,836 --> 00:22:26,996 Speaker 2: The insurance industry. 364 00:22:27,356 --> 00:22:30,196 Speaker 1: If I ensure you against a risk, I make your 365 00:22:31,596 --> 00:22:36,156 Speaker 1: motivation to avoid that risk, I diminish your class. Example 366 00:22:36,156 --> 00:22:40,236 Speaker 1: would be you live in a flood zone and I 367 00:22:40,276 --> 00:22:43,196 Speaker 1: give you flood insurance, or the federal government you know, 368 00:22:43,716 --> 00:22:48,036 Speaker 1: provides flood insurance. Nobody moves from South Beach. Yep, logically 369 00:22:48,036 --> 00:22:50,156 Speaker 1: you shouldn't live in South Peach. In fact, they're building. 370 00:22:50,436 --> 00:22:53,556 Speaker 1: They built billions of dollars in luxury house against South 371 00:22:53,596 --> 00:22:57,196 Speaker 1: Beach in the last ten years, precisely because the builders 372 00:22:57,236 --> 00:23:00,756 Speaker 1: are and the not not just builders, the purchasers of 373 00:23:00,796 --> 00:23:03,236 Speaker 1: those apartments are reasonably sure that in the event of 374 00:23:03,236 --> 00:23:06,116 Speaker 1: an environmental catastrophe, they will be bailed out by the government. 375 00:23:06,276 --> 00:23:08,236 Speaker 1: So why not why not live in paradise until you 376 00:23:08,316 --> 00:23:12,716 Speaker 1: get there? The answer to that is that just because 377 00:23:13,396 --> 00:23:17,956 Speaker 1: one institution or body insures against risk and provides a 378 00:23:17,996 --> 00:23:21,876 Speaker 1: mechanism for moral hazard doesn't mean everybody does. So what's 379 00:23:21,876 --> 00:23:26,436 Speaker 1: happening in Miami is that, sure, if the hurricane wipes 380 00:23:26,476 --> 00:23:28,996 Speaker 1: out your house, the Feds may bail you out, or 381 00:23:28,996 --> 00:23:32,116 Speaker 1: the statement bail you out, But in the meantime, no 382 00:23:32,556 --> 00:23:36,676 Speaker 1: private insurer is writing you up policy, right, So you're 383 00:23:36,716 --> 00:23:40,316 Speaker 1: other self assuring or you're naked. The cycling that's happening 384 00:23:40,836 --> 00:23:43,036 Speaker 1: that I suspect may soon happen, and there are people 385 00:23:43,436 --> 00:23:46,996 Speaker 1: talking about this now, is maybe when you buy a 386 00:23:47,036 --> 00:23:54,556 Speaker 1: house in South Beach, the mortgage rate is three points higher, 387 00:23:54,956 --> 00:23:57,356 Speaker 1: maybe it's ten percent. Maybe the bank just says, you 388 00:23:57,396 --> 00:24:01,636 Speaker 1: know what, why am I writing a mortgage for an 389 00:24:01,676 --> 00:24:05,196 Speaker 1: apartment in South Beach that's the same as an apartment 390 00:24:05,236 --> 00:24:08,796 Speaker 1: on a mountaintop in Maine when the odds that one 391 00:24:08,836 --> 00:24:12,076 Speaker 1: will be swept away in a hurricane are a thousand 392 00:24:12,116 --> 00:24:14,596 Speaker 1: times higher than the other. But really, by a quirk 393 00:24:14,676 --> 00:24:18,516 Speaker 1: of history, we have national mortgage rates. Why are mortgage 394 00:24:18,596 --> 00:24:22,716 Speaker 1: rates national if risks are not equal across what happens 395 00:24:22,756 --> 00:24:25,356 Speaker 1: when we start localizing mortgage rates. That is a way 396 00:24:25,396 --> 00:24:31,076 Speaker 1: in which moral hazard problems can be corrected by the market, right. 397 00:24:31,156 --> 00:24:33,276 Speaker 2: But it's a very different kind of moral hazard. Right. 398 00:24:33,316 --> 00:24:37,596 Speaker 2: It's actually you can't draw this then equivalence there because 399 00:24:37,676 --> 00:24:41,076 Speaker 2: one is a personal choice you're making, right, You're you're 400 00:24:41,156 --> 00:24:43,636 Speaker 2: choosing to buy a house knowing that it'll be fine 401 00:24:43,836 --> 00:24:46,516 Speaker 2: or not. The other one is the way that you're 402 00:24:46,556 --> 00:24:49,876 Speaker 2: looking at policy legislation where you don't think it applies 403 00:24:49,916 --> 00:24:54,716 Speaker 2: to you where oh, well, you know, I'm not the 404 00:24:54,756 --> 00:24:58,596 Speaker 2: one dying, or you know, I think I think it's 405 00:24:58,596 --> 00:25:02,476 Speaker 2: a it's a slightly different decision making calculus. And in 406 00:25:02,516 --> 00:25:07,116 Speaker 2: one case, you're talking about kind of discretionary spending. I 407 00:25:07,156 --> 00:25:10,276 Speaker 2: mean obviously having housing as at discretionary, but you know 408 00:25:10,276 --> 00:25:12,436 Speaker 2: what I mean buying, But buying a condown in South 409 00:25:12,476 --> 00:25:17,796 Speaker 2: Beach certainly is versus you know, life and death and 410 00:25:18,436 --> 00:25:21,436 Speaker 2: policies that are on a more. 411 00:25:22,836 --> 00:25:27,236 Speaker 1: Fundamental global basic Yes, but here my point was I 412 00:25:27,236 --> 00:25:32,556 Speaker 1: should restate my point. My point is that moral hazard 413 00:25:32,636 --> 00:25:36,916 Speaker 1: is a term that applies to any kind of policy 414 00:25:36,996 --> 00:25:42,476 Speaker 1: that removes the kind of necessary pressure for behavioral change. Sure, 415 00:25:43,276 --> 00:25:46,156 Speaker 1: my point is, using the mortgage example, was that just 416 00:25:46,196 --> 00:25:51,076 Speaker 1: because one mechanism removes pressure doesn't mean there are other 417 00:25:51,156 --> 00:25:53,636 Speaker 1: mechanisms that can't exert it. So and you can see 418 00:25:53,636 --> 00:25:56,636 Speaker 1: that with housing. What I'm wondering is, in the case 419 00:25:56,676 --> 00:26:00,276 Speaker 1: of if we had one hundred thousand homicide deaths every year, 420 00:26:00,876 --> 00:26:04,276 Speaker 1: or if we continue to have these one hundred and 421 00:26:04,316 --> 00:26:11,796 Speaker 1: whatever plus, is there another mechanism by which on a 422 00:26:12,156 --> 00:26:18,276 Speaker 1: non effected populations might be affected. So you can imagine 423 00:26:19,436 --> 00:26:24,996 Speaker 1: if you live in downtown San Francisco and you see 424 00:26:25,556 --> 00:26:27,996 Speaker 1: the results on a day to day basis of what 425 00:26:28,316 --> 00:26:32,676 Speaker 1: the opioid crisis is doing to vulnerable communities, that's the 426 00:26:32,756 --> 00:26:36,916 Speaker 1: kind of pressure. Sure, So what if what if I 427 00:26:36,916 --> 00:26:39,476 Speaker 1: imagine that you're the way you think about the opioid 428 00:26:39,516 --> 00:26:42,156 Speaker 1: crisis if you live in downtown San Francisco, it's very 429 00:26:42,156 --> 00:26:45,156 Speaker 1: different than if you lived in Marine County. So what 430 00:26:45,316 --> 00:26:49,316 Speaker 1: happens if Marine County starts to look like downtown San Francisco. 431 00:26:49,436 --> 00:26:52,636 Speaker 1: In other words, there is not it's not absolutely clear 432 00:26:52,676 --> 00:26:56,916 Speaker 1: to me that the kinds of pressures that would change 433 00:26:56,916 --> 00:27:00,236 Speaker 1: people's thinking in a place are always going to be 434 00:27:00,436 --> 00:27:04,396 Speaker 1: confined to downtown San Francisco and downtown LA And right, 435 00:27:04,836 --> 00:27:07,276 Speaker 1: there's a there could be there's a scenario where people 436 00:27:07,316 --> 00:27:12,156 Speaker 1: living in suburban enclaves begin to be confronted with the 437 00:27:12,196 --> 00:27:14,356 Speaker 1: consequences of social policies in a way that they're not 438 00:27:14,476 --> 00:27:15,396 Speaker 1: now right. 439 00:27:16,476 --> 00:27:19,676 Speaker 2: Sure, Sure, I mean I get that argument, and I 440 00:27:19,676 --> 00:27:21,916 Speaker 2: think and I think that that's actually that that's a 441 00:27:21,996 --> 00:27:24,516 Speaker 2: valid argument. But I just don't see, you know, how 442 00:27:24,516 --> 00:27:28,836 Speaker 2: we're going to get without massive horrible things happening to 443 00:27:28,916 --> 00:27:30,996 Speaker 2: the world. How we're going to get Marin County looking 444 00:27:31,036 --> 00:27:34,716 Speaker 2: like downtown San Francisco. It's just a you know, it's 445 00:27:34,756 --> 00:27:37,396 Speaker 2: a it's a nice what if exercise, but but it 446 00:27:37,436 --> 00:27:39,316 Speaker 2: doesn't seem like an actual solution. 447 00:27:42,236 --> 00:27:43,796 Speaker 1: We are going to take a little break and be 448 00:27:43,916 --> 00:27:45,396 Speaker 1: back with some final thoughts. 449 00:27:57,676 --> 00:28:00,196 Speaker 2: So so we had you know, we've talked about a 450 00:28:00,276 --> 00:28:04,196 Speaker 2: lot of problems, and so we had one letter that 451 00:28:04,436 --> 00:28:06,916 Speaker 2: finally turns to the question of okay, so what do 452 00:28:06,996 --> 00:28:10,076 Speaker 2: we do? But here's here's what this letter from South 453 00:28:10,116 --> 00:28:14,316 Speaker 2: Carolina asks. My request is this, I need help with 454 00:28:14,396 --> 00:28:17,556 Speaker 2: the So now, what if Malcolm were in charge of 455 00:28:17,556 --> 00:28:21,556 Speaker 2: this topic, what would he do? Copy Canada's rules, build 456 00:28:21,556 --> 00:28:24,076 Speaker 2: a new hospital in Chicago in a certain gun violence 457 00:28:24,116 --> 00:28:28,476 Speaker 2: prone area. Force all cities to report bullet contact injuries 458 00:28:28,476 --> 00:28:32,636 Speaker 2: and not just fatalities. So Malcolm, you're now in charge 459 00:28:32,676 --> 00:28:32,916 Speaker 2: of this. 460 00:28:33,996 --> 00:28:38,356 Speaker 1: Well all of those things. I mean, I think we 461 00:28:38,436 --> 00:28:41,316 Speaker 1: have to accept rist fall that there's no one there 462 00:28:41,396 --> 00:28:44,356 Speaker 1: is no one thing we can do here. Probably have 463 00:28:44,356 --> 00:28:49,716 Speaker 1: to do twenty things. The big my big of takeaway 464 00:28:49,716 --> 00:28:53,796 Speaker 1: from doing that series was I came away fundamentally disillusioned 465 00:28:53,876 --> 00:28:59,596 Speaker 1: in the power of conventional government approaches to solve the problem. 466 00:28:59,916 --> 00:29:02,236 Speaker 1: I don't. Actually, I was struck in talking to people 467 00:29:02,236 --> 00:29:05,476 Speaker 1: who are on the front lines of this epidemic how 468 00:29:05,636 --> 00:29:08,276 Speaker 1: infrequently people talked about gun control. I mean, I talked 469 00:29:08,276 --> 00:29:11,956 Speaker 1: about in passing, but it is just not The majority 470 00:29:11,996 --> 00:29:16,076 Speaker 1: of gun violence in this country is people to people 471 00:29:16,076 --> 00:29:18,636 Speaker 1: with the legal guns. You can change, you can pass 472 00:29:18,636 --> 00:29:21,556 Speaker 1: all the laws you want. They're not being touched by that. 473 00:29:21,836 --> 00:29:23,756 Speaker 1: I mean, there are little things Washington could do around 474 00:29:23,796 --> 00:29:28,916 Speaker 1: the margin, but just changing the conversation so that we're 475 00:29:28,916 --> 00:29:32,956 Speaker 1: not arguing in the abstract about which law does this 476 00:29:32,996 --> 00:29:35,356 Speaker 1: and which law does that. A couple of seasons ago, 477 00:29:35,436 --> 00:29:38,556 Speaker 1: I did this episode on homelessness and they spent a 478 00:29:38,596 --> 00:29:42,356 Speaker 1: lot of time in Jacksonville, Florida, which has an exemplary 479 00:29:42,356 --> 00:29:46,596 Speaker 1: homelessness program by the way, and someone involved that program said, 480 00:29:47,036 --> 00:29:49,236 Speaker 1: we had this conversation which I didn't use in the episode. 481 00:29:49,556 --> 00:29:52,916 Speaker 1: I've thought about all the time, long time since. She said, 482 00:29:52,956 --> 00:29:55,476 Speaker 1: you know, they do account of their homeless populationship, so 483 00:29:55,516 --> 00:29:57,836 Speaker 1: they have a really really accurate picture going back for years, 484 00:29:58,156 --> 00:30:01,476 Speaker 1: how their population has fluctuated over time. And she said, 485 00:30:01,516 --> 00:30:06,036 Speaker 1: you know, there aren't more homeless in Jacksonville today than 486 00:30:06,036 --> 00:30:09,636 Speaker 1: there were five years ago, in fact is less, but 487 00:30:09,716 --> 00:30:12,876 Speaker 1: they're more visible. And then she went into the long 488 00:30:12,916 --> 00:30:15,436 Speaker 1: discussion of why all the reasons why they might be 489 00:30:15,436 --> 00:30:18,996 Speaker 1: more visible, and it was really interesting to me because 490 00:30:20,076 --> 00:30:23,596 Speaker 1: we do make this mistake where we confuse the severity 491 00:30:23,636 --> 00:30:26,676 Speaker 1: of a problem with the visibility of a problem. And 492 00:30:27,556 --> 00:30:31,396 Speaker 1: the thing that causes pressure is not severity, it's visibility. 493 00:30:32,276 --> 00:30:35,516 Speaker 1: And so when the homeless are visible in Jacksonville, you 494 00:30:35,596 --> 00:30:39,356 Speaker 1: get movement behind it. So now when the problem is 495 00:30:39,516 --> 00:30:41,516 Speaker 1: it's actually small than it used to be in the past, 496 00:30:41,556 --> 00:30:44,436 Speaker 1: but there's urgency now because they're visible, and when it 497 00:30:44,436 --> 00:30:47,316 Speaker 1: was this huge problem that was hidden, there wasn't the 498 00:30:47,356 --> 00:30:51,676 Speaker 1: same kind of So like that distinction so often I 499 00:30:51,716 --> 00:30:57,036 Speaker 1: think allied that distinction between urgency and visibility. So I 500 00:30:57,076 --> 00:30:58,956 Speaker 1: think that what I hope to get from the series 501 00:30:59,076 --> 00:31:01,756 Speaker 1: is not that it pass a law or ban ar 502 00:31:01,836 --> 00:31:04,356 Speaker 1: fifteens or whatever. I think I just wanted to make 503 00:31:04,356 --> 00:31:07,756 Speaker 1: the problem more visible. The last episode is called sin 504 00:31:07,916 --> 00:31:10,276 Speaker 1: is the Failure to Bother to Kill. I'm not so 505 00:31:10,556 --> 00:31:13,356 Speaker 1: interested in what people decide to do to solve the problem, 506 00:31:13,556 --> 00:31:15,436 Speaker 1: because there's a million ways to get it. The problem. 507 00:31:15,836 --> 00:31:18,796 Speaker 1: It's not even just one problem. I'm mainly interested in 508 00:31:18,836 --> 00:31:21,876 Speaker 1: trying to get people to care and to think clearly 509 00:31:21,916 --> 00:31:23,596 Speaker 1: about what they're caring about. 510 00:31:25,516 --> 00:31:28,556 Speaker 2: On that really really happy note, thank you for an 511 00:31:28,596 --> 00:31:33,436 Speaker 2: inspiring and optimistic conversation. By the way, we're probably you know, 512 00:31:33,476 --> 00:31:36,516 Speaker 2: we don't have time. But I loved the Shockley episode. 513 00:31:36,916 --> 00:31:39,716 Speaker 2: I thought it was so much fun and I would 514 00:31:39,796 --> 00:31:42,796 Speaker 2: I hope people listen to the end that last sentence. 515 00:31:43,156 --> 00:31:48,196 Speaker 2: That just what an amazing, amazing reveal. I mean, Freud 516 00:31:48,236 --> 00:31:53,276 Speaker 2: would have just like been been there. Oh Freud's back 517 00:31:53,316 --> 00:31:55,996 Speaker 2: in a big way. Yea, but it was. It was 518 00:31:56,036 --> 00:31:58,756 Speaker 2: such a great episode. I love it. Thank you Ray, 519 00:31:59,116 --> 00:32:02,796 Speaker 2: all right, Thanks Melcom. 520 00:32:02,836 --> 00:32:06,356 Speaker 1: This episode of Revisionist History was produced by Ben A. DAPFH. Haffrey, 521 00:32:06,676 --> 00:32:10,716 Speaker 1: Tali Amlin, and Jacob Smith, editing by seraen Nix, original 522 00:32:10,716 --> 00:32:14,676 Speaker 1: scoring by Luis Kira, mastering by Jake Gorsky, and engineering 523 00:32:15,316 --> 00:32:18,396 Speaker 1: by Nina Lawrence. I'm Malcolm Claudma