1 00:00:01,720 --> 00:00:05,200 Speaker 1: Welcome to Crash Course, a podcast about business, political, and 2 00:00:05,240 --> 00:00:08,800 Speaker 1: social disruption and what we can learn from it. I'm 3 00:00:08,840 --> 00:00:14,480 Speaker 1: Tim O'Brien. Today's Crash Course, our year in review. It's 4 00:00:14,520 --> 00:00:17,079 Speaker 1: been one year since Crash Course launched in your favorite 5 00:00:17,120 --> 00:00:20,800 Speaker 1: podcast feed, and what a year it's been. From Trump 6 00:00:20,960 --> 00:00:26,600 Speaker 1: to putin, climate change, to artificial intelligence SVB to SBF 7 00:00:27,360 --> 00:00:31,600 Speaker 1: Florida to Gaza, the Supreme Court to Barbie and so 8 00:00:31,720 --> 00:00:34,280 Speaker 1: much more. We covered a lot of ground this year, 9 00:00:34,800 --> 00:00:37,040 Speaker 1: and we learned a lot. Because that's a key part 10 00:00:37,040 --> 00:00:39,560 Speaker 1: of Crash Course. We want to learn something new in 11 00:00:39,640 --> 00:00:42,680 Speaker 1: every episode and share that with you. So to mark 12 00:00:42,720 --> 00:00:45,320 Speaker 1: our one year anniversary, I wanted to listen back through 13 00:00:45,320 --> 00:00:47,760 Speaker 1: the tape and remember some of the key learnings from 14 00:00:47,760 --> 00:00:51,559 Speaker 1: the past year. We'll remember the people, conflicts, and cultural 15 00:00:51,560 --> 00:00:53,880 Speaker 1: moments that made this year one for the history books, 16 00:00:54,560 --> 00:00:56,600 Speaker 1: and we'll link to all of those episodes in the 17 00:00:56,640 --> 00:01:01,400 Speaker 1: show notes so you can listen to each episode in full. 18 00:01:01,520 --> 00:01:03,360 Speaker 1: Let's start with some of the big names we've heard 19 00:01:03,400 --> 00:01:06,840 Speaker 1: about this year, beginning with Elon Musk at Twitter. Our 20 00:01:06,920 --> 00:01:09,559 Speaker 1: very first episode ever was just a few months after 21 00:01:09,640 --> 00:01:12,840 Speaker 1: Musk took over at Twitter, so we called up Kurt Wagner. 22 00:01:13,480 --> 00:01:16,920 Speaker 1: He's a Bloomberg News reporter who spent years covering social media, 23 00:01:17,640 --> 00:01:21,280 Speaker 1: especially Twitter. Here's Kurt's lesson from last January. 24 00:01:22,280 --> 00:01:22,800 Speaker 2: I think that. 25 00:01:22,800 --> 00:01:28,120 Speaker 3: I've just grown a greater appreciation for what can happen 26 00:01:28,600 --> 00:01:31,440 Speaker 3: when someone is very rich and powerful in terms of 27 00:01:31,640 --> 00:01:35,440 Speaker 3: sort of like forcing things that you wouldn't think would 28 00:01:35,480 --> 00:01:38,440 Speaker 3: be possible, and not all good things right, like we've seen, 29 00:01:39,040 --> 00:01:44,200 Speaker 3: for example, he's just sort of ignoring regulatory requirements. He 30 00:01:44,640 --> 00:01:46,720 Speaker 3: signed an agreement to buy this company and then just 31 00:01:46,720 --> 00:01:48,520 Speaker 3: simply said I'm not going to buy it, Like that 32 00:01:48,600 --> 00:01:50,920 Speaker 3: is not something that could normally happen. But he is 33 00:01:51,400 --> 00:01:54,720 Speaker 3: elon Musk, he has infinite resources. He seems to have 34 00:01:54,800 --> 00:01:58,360 Speaker 3: no regard for kind of general rules that most of 35 00:01:58,400 --> 00:02:00,840 Speaker 3: the rest of us play by, And so I think 36 00:02:00,920 --> 00:02:03,480 Speaker 3: for me, it's just sort of like opened my eyes 37 00:02:03,560 --> 00:02:06,320 Speaker 3: to the fact that we think something is supposed to 38 00:02:06,400 --> 00:02:09,840 Speaker 3: work a certain way, and yet that's not set in 39 00:02:09,880 --> 00:02:13,520 Speaker 3: stone or very rigid necessarily, especially when you are a 40 00:02:13,639 --> 00:02:16,080 Speaker 3: very rich and powerful person, which he is. And so 41 00:02:16,600 --> 00:02:20,480 Speaker 3: maybe I was just too naive previously to assume, like, Okay, 42 00:02:20,560 --> 00:02:23,000 Speaker 3: a binding contract means everyone will actually do what they 43 00:02:23,000 --> 00:02:25,280 Speaker 3: say they're going to do, but he's just sort of 44 00:02:25,360 --> 00:02:29,960 Speaker 3: like proved that almost nothing that's even said or agreed 45 00:02:30,000 --> 00:02:32,280 Speaker 3: to is set in stone until he decides that it is. 46 00:02:33,600 --> 00:02:36,240 Speaker 1: Since then, I've learned that Elon Musk was even more 47 00:02:36,360 --> 00:02:39,839 Speaker 1: incapable of running Twitter than I originally thought, and he's 48 00:02:39,880 --> 00:02:42,160 Speaker 1: been more than willing to engage personally in some of 49 00:02:42,160 --> 00:02:52,360 Speaker 1: the platform's most abusive and divisive practices. Next up, Russia's 50 00:02:52,360 --> 00:02:55,680 Speaker 1: President Vladimir Putin. We marked the one year anniversary of 51 00:02:55,680 --> 00:02:58,440 Speaker 1: the Russia Ukraine War last year by speaking with one 52 00:02:58,440 --> 00:03:02,120 Speaker 1: of the foremost experts on Russia, Stephen Kotkin. He's a 53 00:03:02,160 --> 00:03:06,400 Speaker 1: senior fellow at Stanford University's Hoover Institution. Here's what Stephen 54 00:03:06,440 --> 00:03:08,200 Speaker 1: has learned from watching the war unfold. 55 00:03:08,800 --> 00:03:12,720 Speaker 4: Sadly, I've learned many things I already knew that the 56 00:03:12,760 --> 00:03:19,360 Speaker 4: world is full of evil, that war is still a problem. Happens, 57 00:03:19,520 --> 00:03:24,400 Speaker 4: it's not something that is, let's say, rare. I've also 58 00:03:24,560 --> 00:03:29,160 Speaker 4: learned that the West, rather than one world ism is 59 00:03:29,200 --> 00:03:33,520 Speaker 4: the basis of our security and prosperity. So the GAT 60 00:03:33,639 --> 00:03:37,720 Speaker 4: rather than the wto NATO, the EU, and the First 61 00:03:37,760 --> 00:03:42,960 Speaker 4: Island chain rather than Kumbayah. Those are all things that 62 00:03:43,000 --> 00:03:46,400 Speaker 4: I thought before that have been strengthened with this war. 63 00:03:47,160 --> 00:03:50,520 Speaker 4: The biggest thing I got wrong is I expected another 64 00:03:50,640 --> 00:03:54,480 Speaker 4: part of the world to blow up while this was happening. 65 00:03:55,040 --> 00:03:58,440 Speaker 4: I expected other countries to take advantage of the situation, 66 00:03:59,280 --> 00:04:03,760 Speaker 4: whether that would be something happening with Iran, something happening 67 00:04:03,800 --> 00:04:09,640 Speaker 4: with North Korea, with China. I expected maybe it wouldn't 68 00:04:09,680 --> 00:04:11,840 Speaker 4: even be in a place that I was paying attention to. 69 00:04:12,320 --> 00:04:16,640 Speaker 4: So one bad thing happens, and it's not an isolated event. 70 00:04:17,440 --> 00:04:20,880 Speaker 4: It's a potential trigger for other bad things to happen 71 00:04:20,920 --> 00:04:24,279 Speaker 4: in an unraveling. So far, that's not been the case. 72 00:04:25,040 --> 00:04:27,520 Speaker 4: I predicted that that would happen, and I've been wrong 73 00:04:27,560 --> 00:04:30,800 Speaker 4: about that, fortunately, So let's hope I continue to be 74 00:04:30,880 --> 00:04:35,679 Speaker 4: wrong about that going forward, because it's enough already trying 75 00:04:35,680 --> 00:04:39,400 Speaker 4: to resolve this criminal aggression against Ukraine. 76 00:04:39,600 --> 00:04:42,320 Speaker 1: Since that episode aired, I've learned that Vladimir Putin is 77 00:04:42,360 --> 00:04:45,400 Speaker 1: willing to allow massive losses among his own troops to 78 00:04:45,480 --> 00:04:49,480 Speaker 1: continue prosecuting a devastating war that has no end in sight. 79 00:04:54,839 --> 00:04:58,799 Speaker 1: If you didn't already know the acronym SBF, you probably 80 00:04:58,880 --> 00:05:01,640 Speaker 1: learned it in the last few month months. Sam Bankman 81 00:05:01,720 --> 00:05:06,160 Speaker 1: freed once captured the world's attention with his crypto company FTX, 82 00:05:06,920 --> 00:05:10,360 Speaker 1: but then he was convicted of fraud and conspiracy. While 83 00:05:10,360 --> 00:05:12,719 Speaker 1: we were waiting for his trial to start, I spoke 84 00:05:12,720 --> 00:05:16,000 Speaker 1: with Hannah Miller, who covers crypto for Bloomberg News and 85 00:05:16,080 --> 00:05:21,320 Speaker 1: hosts the podcast Spellcaster, about the life and times of SBF. 86 00:05:22,160 --> 00:05:24,039 Speaker 1: Here's what Hannah learned in her reporting. 87 00:05:24,839 --> 00:05:27,719 Speaker 5: I think the top thing I've learned is that be 88 00:05:27,839 --> 00:05:30,839 Speaker 5: suspicious of anyone who claims to be a hero, especially 89 00:05:31,240 --> 00:05:35,400 Speaker 5: in this industry, and really question their motivations, look at 90 00:05:35,440 --> 00:05:39,680 Speaker 5: how it benefits them personally, and then I don't know. 91 00:05:39,680 --> 00:05:42,760 Speaker 5: I still think crypto has to figure out what exactly 92 00:05:43,040 --> 00:05:45,840 Speaker 5: it wants to use boxing technology for. You know, this 93 00:05:45,920 --> 00:05:50,560 Speaker 5: is an industry still finding its legs, and these bad 94 00:05:50,600 --> 00:05:53,440 Speaker 5: actors are just hobbling things. 95 00:05:54,080 --> 00:05:56,880 Speaker 1: Since the trial, I've learned that SBF wasn't just your 96 00:05:56,920 --> 00:05:59,960 Speaker 1: average grifter. He was convicted of fraud in a federal 97 00:06:00,000 --> 00:06:03,200 Speaker 1: courtroom for presiding over one of the business world's biggest 98 00:06:03,240 --> 00:06:12,599 Speaker 1: financial scandals. And of course there's Donald Trump. The former 99 00:06:12,640 --> 00:06:15,840 Speaker 1: president faces a total of ninety one charges across four 100 00:06:15,880 --> 00:06:18,479 Speaker 1: criminal cases and he's still the front runner in the 101 00:06:18,480 --> 00:06:22,680 Speaker 1: Republican primary. After his first indictment, I sat down with 102 00:06:22,720 --> 00:06:25,800 Speaker 1: my colleague Noah Feldman to dig into what it all meant. 103 00:06:26,240 --> 00:06:28,719 Speaker 1: Noah is a professor at Harvard Law School and a 104 00:06:28,760 --> 00:06:32,440 Speaker 1: columnist here at Bloomberg Opinion. Here's what Noah learned in 105 00:06:32,480 --> 00:06:35,039 Speaker 1: the aftermath of those first charges being filed. 106 00:06:35,680 --> 00:06:38,640 Speaker 6: The biggest aha for me is that a value that 107 00:06:38,720 --> 00:06:41,920 Speaker 6: we all usually like, namely prosecutors should do things slowly 108 00:06:41,960 --> 00:06:46,640 Speaker 6: and methodically, is actually a disaster when it comes to 109 00:06:47,120 --> 00:06:50,880 Speaker 6: someone like Donald Trump, a politician who has lost an 110 00:06:50,920 --> 00:06:54,000 Speaker 6: election and is planning to run again. I wish that 111 00:06:54,080 --> 00:06:56,880 Speaker 6: you and I were having this entire set of conversations 112 00:06:57,640 --> 00:07:01,240 Speaker 6: eighteen months ago, in the early days of the Biden administration, 113 00:07:01,680 --> 00:07:03,800 Speaker 6: when whatever Trump might say about running for office, it 114 00:07:03,880 --> 00:07:07,520 Speaker 6: was a long way off before midterms, a whole different world. 115 00:07:08,320 --> 00:07:12,120 Speaker 6: And that is a possible scenario to imagine. Notwithstanding what 116 00:07:12,160 --> 00:07:14,280 Speaker 6: you were saying about the charges that the other prosecutors 117 00:07:14,280 --> 00:07:15,920 Speaker 6: in the New York Days Office wanted to bring, and 118 00:07:16,080 --> 00:07:18,040 Speaker 6: I'm happy to talk about that sometime in the future. 119 00:07:18,280 --> 00:07:21,480 Speaker 6: Basically old history. At this point, those were charges that 120 00:07:21,520 --> 00:07:25,080 Speaker 6: were ready at least a year ago, for what it's worth, 121 00:07:25,680 --> 00:07:29,160 Speaker 6: and ditto for the Georgia case. The facts were gathered, 122 00:07:29,240 --> 00:07:31,000 Speaker 6: it took a little bit longer, perhaps in the case 123 00:07:31,000 --> 00:07:35,200 Speaker 6: of the federal prosecution. But the danger that our political 124 00:07:35,200 --> 00:07:39,760 Speaker 6: season keeps expanding in time, and that therefore it gets 125 00:07:39,840 --> 00:07:42,280 Speaker 6: harder and harder to bring charges against someone like Donald 126 00:07:42,280 --> 00:07:45,640 Speaker 6: Trump is a real one. And so my takeaway is 127 00:07:45,680 --> 00:07:47,760 Speaker 6: the thing that I really don't think I fully understood 128 00:07:47,800 --> 00:07:49,720 Speaker 6: before we entered this season. I think I did understand 129 00:07:49,720 --> 00:07:51,600 Speaker 6: that there was going to be a trade off between 130 00:07:51,920 --> 00:07:55,280 Speaker 6: protecting our political process and our democracy seeming to be 131 00:07:55,360 --> 00:08:00,800 Speaker 6: truly objective and being truly objective meaningfully and prosecuting Trump. 132 00:08:00,840 --> 00:08:02,520 Speaker 6: I understand there was a trade off. I didn't fully 133 00:08:02,560 --> 00:08:05,760 Speaker 6: understand the time to mention, and as I see it, 134 00:08:05,760 --> 00:08:08,360 Speaker 6: it fills me with regret that these processes didn't go 135 00:08:08,440 --> 00:08:11,240 Speaker 6: by a lot more efficiently than they seem to have done. 136 00:08:11,600 --> 00:08:14,040 Speaker 1: I've reported on Trump for a long time, and I 137 00:08:14,160 --> 00:08:16,160 Speaker 1: even faced off against him in a court battle of 138 00:08:16,200 --> 00:08:18,760 Speaker 1: my own when he sued me for defamation after I 139 00:08:18,800 --> 00:08:22,000 Speaker 1: published my book Trump Nation, The Art of Being the Donald. 140 00:08:22,520 --> 00:08:25,360 Speaker 1: The case was dismissed, but I learned a lot about Trump. 141 00:08:25,360 --> 00:08:28,840 Speaker 1: From that experience, watching all of his legal woes this year, 142 00:08:29,120 --> 00:08:31,880 Speaker 1: I learned that Trump is more than willing to sabotage 143 00:08:31,920 --> 00:08:35,560 Speaker 1: public trust in the nation's judicial and law enforcement systems 144 00:08:35,880 --> 00:08:39,400 Speaker 1: in order to save his own hide. And on that note, 145 00:08:39,440 --> 00:08:42,440 Speaker 1: we'll take a break. When we come back, we'll remember 146 00:08:42,440 --> 00:08:50,840 Speaker 1: some of the big events of the past year. We're 147 00:08:50,880 --> 00:08:53,880 Speaker 1: back looking at our first year of learnings here at Crash. Course, 148 00:08:54,760 --> 00:08:57,560 Speaker 1: of course, the show focuses on collisions, and there have 149 00:08:57,600 --> 00:09:00,360 Speaker 1: been a lot of disruptions in big news moments here. 150 00:09:01,200 --> 00:09:04,880 Speaker 1: Most recently, we've seen a war breakout between Israel and Hamas. 151 00:09:05,559 --> 00:09:08,800 Speaker 1: The current conflict is steeped in decades of tension, so 152 00:09:08,840 --> 00:09:11,120 Speaker 1: I knew I needed to have a nuanced conversation with 153 00:09:11,160 --> 00:09:14,120 Speaker 1: my colleagues and Bloomberg opinion about how we got here. 154 00:09:14,920 --> 00:09:18,480 Speaker 1: Mark Champion covers global politics for US, so he traveled 155 00:09:18,480 --> 00:09:20,760 Speaker 1: to Israel to report from the front lines of the 156 00:09:20,800 --> 00:09:23,840 Speaker 1: war zone. Here's what Mark learned on the ground. 157 00:09:24,559 --> 00:09:29,720 Speaker 7: I think I did not understand like the Israelis. I 158 00:09:29,760 --> 00:09:32,240 Speaker 7: think I mean, I was familiar with Hamas, but I 159 00:09:32,360 --> 00:09:38,720 Speaker 7: did not understand how carefully they had been preparing and 160 00:09:38,800 --> 00:09:42,679 Speaker 7: how frankly efficiently they had been preparing for this, and 161 00:09:42,760 --> 00:09:49,560 Speaker 7: they are a more dangerous fighting force than I perhaps 162 00:09:49,640 --> 00:09:52,960 Speaker 7: had expected. One of the things that really intrigues me 163 00:09:53,000 --> 00:09:58,000 Speaker 7: about this is whether what went on in Ukraine would 164 00:09:58,040 --> 00:10:02,359 Speaker 7: have been carefully watched by them. This sort of asymmetric warfare, 165 00:10:03,000 --> 00:10:05,600 Speaker 7: what Hamas did is at a different level to what 166 00:10:06,000 --> 00:10:08,800 Speaker 7: you know. Terrisa always gaged an asymmetric warfare, but this 167 00:10:08,880 --> 00:10:11,120 Speaker 7: was at a different level with you know, sort of 168 00:10:11,240 --> 00:10:16,760 Speaker 7: combined force operations, you know, AirLand and sea, drones, hang gliders, 169 00:10:16,760 --> 00:10:20,000 Speaker 7: et cetera. And just the fact that you know, a 170 00:10:20,160 --> 00:10:25,440 Speaker 7: much smaller force in Ukraine was able to force back 171 00:10:26,040 --> 00:10:29,720 Speaker 7: the second largest military in the world. Who nobody thought 172 00:10:29,800 --> 00:10:32,440 Speaker 7: that was possible. That's one of the questions in my 173 00:10:32,559 --> 00:10:35,079 Speaker 7: mind as to whether you know, we are in an 174 00:10:35,080 --> 00:10:39,160 Speaker 7: era when there is an optimism for smaller forces that 175 00:10:39,240 --> 00:10:41,880 Speaker 7: they can do this type of thing because they've seen 176 00:10:41,920 --> 00:10:42,840 Speaker 7: the Ukrainians do it. 177 00:10:43,800 --> 00:10:46,040 Speaker 1: Since the war broke out, I've learned that a brutal 178 00:10:46,040 --> 00:10:49,080 Speaker 1: conflict in Gaza is unlikely to be solved through diplomacy 179 00:10:49,800 --> 00:10:56,480 Speaker 1: or even the end of the current war. Earlier in 180 00:10:56,480 --> 00:10:59,240 Speaker 1: the year, the banking system was rocked by the failures 181 00:10:59,240 --> 00:11:04,000 Speaker 1: of Silicon Valley Bank, First Republic Bank, Credit Sweese, and more. 182 00:11:04,720 --> 00:11:08,320 Speaker 1: Those crises exposed fault lines running beneath our fragile financial 183 00:11:08,320 --> 00:11:11,880 Speaker 1: ecosystem and called into question the power of the Federal Reserve. 184 00:11:12,720 --> 00:11:14,880 Speaker 1: In the midst of that turmoil, I sat down with 185 00:11:14,920 --> 00:11:19,200 Speaker 1: Paul Davies, a financial columnist for Bloomberg Opinion. Here's what 186 00:11:19,320 --> 00:11:20,880 Speaker 1: that episode taught Paul. 187 00:11:21,600 --> 00:11:23,679 Speaker 2: I think the key thing that it's taught me is 188 00:11:24,440 --> 00:11:28,640 Speaker 2: even when all of the fundamentals, all of the foundational 189 00:11:29,160 --> 00:11:32,280 Speaker 2: numbers of the state of an institution, say that it 190 00:11:32,440 --> 00:11:35,480 Speaker 2: sounds and say that it's trustworthy, you can still have 191 00:11:35,559 --> 00:11:38,920 Speaker 2: people turn around and say, ah, I don't like it, 192 00:11:39,160 --> 00:11:39,760 Speaker 2: I'm leaving. 193 00:11:40,840 --> 00:11:43,800 Speaker 1: Since that episode aired, I've learned that maybe things weren't 194 00:11:43,800 --> 00:11:46,880 Speaker 1: as threatening to the entire banking system as everyone seemed 195 00:11:46,880 --> 00:11:51,160 Speaker 1: to think when SVB began teetering. Most US banks now 196 00:11:51,480 --> 00:11:59,480 Speaker 1: seem to be doing just fine. Fox News has been 197 00:11:59,520 --> 00:12:01,360 Speaker 1: at the center of a lot of issues that are 198 00:12:01,360 --> 00:12:05,600 Speaker 1: fodder for crash course, trump mania, culture wars, and misinformation. 199 00:12:06,559 --> 00:12:09,360 Speaker 1: The latter came into focus in a lawsuit brought by 200 00:12:09,360 --> 00:12:14,040 Speaker 1: Dominion Voting Systems, a voting machine company that Fox erroneously 201 00:12:14,040 --> 00:12:17,720 Speaker 1: claimed had switched votes from Trump to Biden in twenty twenty. 202 00:12:18,520 --> 00:12:21,480 Speaker 1: To dig into the implications of that defamation case, I 203 00:12:21,559 --> 00:12:24,920 Speaker 1: called on David Fokenflick, who followed the whole ordeal as 204 00:12:25,000 --> 00:12:29,320 Speaker 1: NPR's media correspondent and the author of Murdoch's World, The 205 00:12:29,400 --> 00:12:32,960 Speaker 1: Last of the Old Media Empires. Here's what David learned 206 00:12:33,120 --> 00:12:35,040 Speaker 1: watching that case shake out. 207 00:12:35,360 --> 00:12:39,200 Speaker 8: You know, each generation, each epic, has its own moments 208 00:12:39,240 --> 00:12:45,679 Speaker 8: in which things like how defamation is defined are either affirmed, reshaped, 209 00:12:45,800 --> 00:12:50,120 Speaker 8: or utterly rewritten. You know, you have three Supreme Court 210 00:12:50,240 --> 00:12:52,840 Speaker 8: justices who, in different ways and from different perspectives, have 211 00:12:53,320 --> 00:12:56,880 Speaker 8: registered themselves over the years as being open to reviewing 212 00:12:56,920 --> 00:13:00,920 Speaker 8: this question and this definition. And there's so concerned, or 213 00:13:00,920 --> 00:13:03,520 Speaker 8: at least there was before all this evidence was developed 214 00:13:03,520 --> 00:13:06,120 Speaker 8: against Fox, but some concern that were Fox to be 215 00:13:06,120 --> 00:13:08,200 Speaker 8: found liable, it would be appealed to the Supreme Court, 216 00:13:08,240 --> 00:13:09,760 Speaker 8: and then the Supreme Court would use that as an 217 00:13:09,760 --> 00:13:13,280 Speaker 8: opportunity to change how restrictive and how difficult that bar 218 00:13:13,480 --> 00:13:17,600 Speaker 8: is for people to meet. I think that Fox is 219 00:13:17,679 --> 00:13:20,280 Speaker 8: raising a question which I think is interesting one, which 220 00:13:20,320 --> 00:13:22,080 Speaker 8: is for all the people who are happy to see 221 00:13:22,080 --> 00:13:24,240 Speaker 8: Fox get a come up and many of them in 222 00:13:24,320 --> 00:13:26,280 Speaker 8: the media, many of them liberals, and some of them 223 00:13:26,360 --> 00:13:30,640 Speaker 8: just deeply scornful and contemptuous of the things that have 224 00:13:30,720 --> 00:13:33,600 Speaker 8: been revealed about the fundamental nature of the way Fox operates. 225 00:13:34,040 --> 00:13:35,800 Speaker 8: You know, it's a careful what you wish for thing, 226 00:13:36,160 --> 00:13:38,320 Speaker 8: because this stuff could be turned against the New York 227 00:13:38,360 --> 00:13:42,760 Speaker 8: Times or NBC or the Associated Press too, depending on 228 00:13:42,880 --> 00:13:45,839 Speaker 8: the circumstances and the nature of the judges who are 229 00:13:45,880 --> 00:13:46,920 Speaker 8: hearing such cases. 230 00:13:47,800 --> 00:13:50,319 Speaker 1: Fox was forced to pay seven hundred and eighty seven 231 00:13:50,400 --> 00:13:54,120 Speaker 1: million dollars to settle that lawsuit with dominion, and then 232 00:13:54,200 --> 00:13:57,280 Speaker 1: changes followed. Rupert Murdoch slept down as the head of 233 00:13:57,280 --> 00:14:00,280 Speaker 1: the company he founded. We did a whole separate episod 234 00:14:00,440 --> 00:14:03,680 Speaker 1: about the end of his reign. But watching Fox unravel 235 00:14:03,800 --> 00:14:05,760 Speaker 1: even more in the past year, I've learned that we 236 00:14:05,760 --> 00:14:10,320 Speaker 1: shouldn't expect Fox to change. It only changes its leadership, 237 00:14:10,520 --> 00:14:13,560 Speaker 1: It never really changes its spots, and the Carneact just 238 00:14:13,640 --> 00:14:21,280 Speaker 1: goes on. In our time of climate change, in extreme weather, 239 00:14:21,600 --> 00:14:25,280 Speaker 1: it was perhaps not entirely surprising that twenty twenty three 240 00:14:25,440 --> 00:14:28,080 Speaker 1: was another year for the record books. So I turned 241 00:14:28,080 --> 00:14:31,520 Speaker 1: to my colleague Mark Gongloff, a columnist with Bloomberg Opinion, 242 00:14:31,720 --> 00:14:35,640 Speaker 1: who specializes in covering the environment and climate change. I 243 00:14:35,720 --> 00:14:38,880 Speaker 1: call him the climates are inside Bloomberg Opinion, and he 244 00:14:39,000 --> 00:14:41,080 Speaker 1: told me there's still time to learn from our climate 245 00:14:41,120 --> 00:14:43,960 Speaker 1: related mistakes and invest in the future of our planet. 246 00:14:44,680 --> 00:14:49,400 Speaker 9: I am learning that the changes are much more complicated 247 00:14:49,440 --> 00:14:53,400 Speaker 9: than I even realized at first. The biggest thing, though, 248 00:14:53,400 --> 00:14:56,320 Speaker 9: I think, is just the energy transitions can be so expensive. 249 00:14:56,320 --> 00:14:58,800 Speaker 9: I mean, Bloomberg and EF I always hate to say 250 00:14:58,800 --> 00:15:00,920 Speaker 9: this number because it's so terrified, but Bloomberg and ef 251 00:15:01,000 --> 00:15:02,440 Speaker 9: estimated the world is going to have to spend two 252 00:15:02,480 --> 00:15:06,600 Speaker 9: hundred trillion dollars to get our emissions down to avoid 253 00:15:06,600 --> 00:15:08,760 Speaker 9: the worst climate disasters. And that sounds like a lot, 254 00:15:08,920 --> 00:15:10,880 Speaker 9: but that is over the next between now and say 255 00:15:10,880 --> 00:15:13,840 Speaker 9: twenty fifty, And then if you start to add up 256 00:15:13,880 --> 00:15:17,480 Speaker 9: the costs that happen. Claudia sam Great Economists, just wrote 257 00:15:17,480 --> 00:15:19,560 Speaker 9: a column for us that said it's going to cost 258 00:15:19,600 --> 00:15:22,920 Speaker 9: maybe three hundred billion dollars a year in lost worker 259 00:15:22,960 --> 00:15:26,200 Speaker 9: productivity due to heat alone by twenty fifty. And so 260 00:15:26,280 --> 00:15:29,080 Speaker 9: you take those little effects and the effects of hurricanes 261 00:15:29,120 --> 00:15:32,880 Speaker 9: and droughts and wildfires and just general health. We haven't 262 00:15:32,880 --> 00:15:35,320 Speaker 9: even gotten into the health effects of climate change, how 263 00:15:35,360 --> 00:15:38,960 Speaker 9: diseases are moving there, are expanding their horizons and moving 264 00:15:39,040 --> 00:15:42,240 Speaker 9: into new areas. All that stuff adds up, and so 265 00:15:42,480 --> 00:15:45,680 Speaker 9: the biggest thing I've learned is to think about these things, 266 00:15:45,800 --> 00:15:48,960 Speaker 9: the transition, the spending on green energy and the like, 267 00:15:49,120 --> 00:15:52,240 Speaker 9: as investments rather than costs, because the real costs are 268 00:15:52,240 --> 00:15:55,240 Speaker 9: what happened if we don't do anything. What we're spending 269 00:15:55,240 --> 00:15:57,880 Speaker 9: to avoid that stuff is an investment and a better future. 270 00:15:58,840 --> 00:16:02,200 Speaker 1: Since that conversation, and I've learned the climate catastrophes seem 271 00:16:02,240 --> 00:16:04,640 Speaker 1: to be the only things that focus the public's attention 272 00:16:05,120 --> 00:16:08,920 Speaker 1: on a world growing dangerously warmer, and even then, people 273 00:16:09,000 --> 00:16:13,120 Speaker 1: still aren't taking the threat seriously enough. We're going to 274 00:16:13,200 --> 00:16:15,320 Speaker 1: take a quick break then come back to look at 275 00:16:15,320 --> 00:16:25,840 Speaker 1: cultural collisions. We're back, and we're going to end our 276 00:16:25,880 --> 00:16:28,280 Speaker 1: tour through the past year by remembering some of the 277 00:16:28,280 --> 00:16:31,720 Speaker 1: big cultural moments of the year. After the COVID nineteen 278 00:16:31,760 --> 00:16:35,480 Speaker 1: pandemic popularized working from home, twenty twenty three marked a 279 00:16:35,520 --> 00:16:40,280 Speaker 1: big push in rto return to office. Some companies handle 280 00:16:40,360 --> 00:16:43,120 Speaker 1: the transition better than others, and I wanted to talk 281 00:16:43,160 --> 00:16:46,880 Speaker 1: to my colleague at Bloomberg opinion Sarah Green Carmichael about 282 00:16:46,960 --> 00:16:51,280 Speaker 1: changes in office culture since the pandemic. Here's what Sarah's learned. 283 00:16:52,040 --> 00:16:55,920 Speaker 10: I think what I am learning is that the motivational 284 00:16:55,960 --> 00:16:59,120 Speaker 10: model of the last fifteen years was really about a 285 00:16:59,160 --> 00:17:02,760 Speaker 10: specific time and place in economy and when companies were 286 00:17:02,760 --> 00:17:05,920 Speaker 10: competing on talent and not on capital because interest rates 287 00:17:05,920 --> 00:17:08,560 Speaker 10: were really low for a really long time. When companies 288 00:17:08,600 --> 00:17:11,760 Speaker 10: were competing on talent, they really believed in this sort 289 00:17:11,800 --> 00:17:15,560 Speaker 10: of company culture hire great people and set them free 290 00:17:15,800 --> 00:17:18,720 Speaker 10: and have them deeply committed to the work sort of idea. 291 00:17:19,680 --> 00:17:21,800 Speaker 10: And I think what we're seeing now is what happens 292 00:17:21,800 --> 00:17:26,439 Speaker 10: when the economy slows down. When you have convinced employees 293 00:17:26,480 --> 00:17:28,920 Speaker 10: to buy into an ownership culture and that they need 294 00:17:28,920 --> 00:17:31,760 Speaker 10: to act like owners and entrepreneurs. They are going to 295 00:17:31,880 --> 00:17:34,160 Speaker 10: have some ideas on how the business should be run. 296 00:17:34,640 --> 00:17:37,159 Speaker 10: They're going to have ideas and what political causes you support. 297 00:17:37,200 --> 00:17:38,800 Speaker 10: They are going to have ideas and what the remote 298 00:17:38,800 --> 00:17:41,520 Speaker 10: work policy should be. And so I think that this 299 00:17:41,720 --> 00:17:44,920 Speaker 10: shift I'm seeing from sort of fed up executives who 300 00:17:44,960 --> 00:17:46,840 Speaker 10: are sort of like, oh my god, stop complaining, get 301 00:17:46,840 --> 00:17:49,560 Speaker 10: back to work. Don't be such a snowflake. It's a 302 00:17:49,560 --> 00:17:52,680 Speaker 10: little bit like, but you spent fifteen years like telling 303 00:17:52,760 --> 00:17:55,400 Speaker 10: us we should act like owners, like that's what we're doing. 304 00:17:55,600 --> 00:17:57,439 Speaker 10: I think that's where a lot of this tension is 305 00:17:57,440 --> 00:18:01,119 Speaker 10: coming from. And I do not know if motivational model 306 00:18:01,680 --> 00:18:04,280 Speaker 10: that I have seen for the last fifteen years will persevere. 307 00:18:04,359 --> 00:18:06,240 Speaker 10: And in some ways it would be healthy if it didn't. 308 00:18:06,440 --> 00:18:08,320 Speaker 10: Maybe a lot of us could use some more distance 309 00:18:08,320 --> 00:18:10,560 Speaker 10: from our jobs and not identify so much with them 310 00:18:10,600 --> 00:18:13,240 Speaker 10: and have so much of ourselves invested in them. But 311 00:18:13,359 --> 00:18:15,960 Speaker 10: if employees pull back from that, that's when you start 312 00:18:16,000 --> 00:18:17,800 Speaker 10: to have executives worried about quiet quitting. 313 00:18:18,000 --> 00:18:18,240 Speaker 11: Right. 314 00:18:18,680 --> 00:18:21,480 Speaker 10: So I think that there's this sort of dance playing out. 315 00:18:21,800 --> 00:18:23,800 Speaker 10: We kind of all want to have it all. Employees 316 00:18:23,840 --> 00:18:27,280 Speaker 10: want to have high salaries and ownership and work life balance, 317 00:18:27,320 --> 00:18:29,280 Speaker 10: and then I think in some ways managers want to 318 00:18:29,320 --> 00:18:32,760 Speaker 10: have a docile, obedient workforce that they can underpay, but 319 00:18:32,800 --> 00:18:34,760 Speaker 10: who also will work around the clock, and like, we 320 00:18:34,800 --> 00:18:36,080 Speaker 10: can't have all these things. 321 00:18:37,119 --> 00:18:39,480 Speaker 1: My own experience of Artio has taught me that the 322 00:18:39,520 --> 00:18:43,280 Speaker 1: work world has changed, perhaps permanently, and managers are going 323 00:18:43,320 --> 00:18:43,680 Speaker 1: to have to. 324 00:18:43,680 --> 00:18:44,199 Speaker 9: Change with it. 325 00:18:49,320 --> 00:18:51,720 Speaker 1: Returning to the office also looks a little different for 326 00:18:51,800 --> 00:18:55,399 Speaker 1: some workers as the use of artificial intelligence or AI 327 00:18:56,000 --> 00:18:59,960 Speaker 1: has really ballooned. My colleague parme Olsen is Bloomberg epin 328 00:19:00,119 --> 00:19:04,080 Speaker 1: is technology columnists and an AI guru. So I asked 329 00:19:04,119 --> 00:19:07,000 Speaker 1: Parmi what she's learned from the past year of AI 330 00:19:07,119 --> 00:19:08,440 Speaker 1: innovation and disruption. 331 00:19:09,119 --> 00:19:12,200 Speaker 12: Well, I think the thing that really surprised me about chat, 332 00:19:12,280 --> 00:19:16,199 Speaker 12: hept and some of the latest generative AI tools to 333 00:19:16,240 --> 00:19:19,679 Speaker 12: come out in the past year is how creative AI 334 00:19:19,920 --> 00:19:23,160 Speaker 12: seems to be. Because for years and years when people 335 00:19:23,200 --> 00:19:27,600 Speaker 12: talked about AI taking people's jobs, it was about taking 336 00:19:27,920 --> 00:19:31,760 Speaker 12: factory worker jobs and truck driver jobs. But now it 337 00:19:31,840 --> 00:19:35,120 Speaker 12: seems like the real jobs that are at threat are 338 00:19:35,600 --> 00:19:40,720 Speaker 12: the creative classes and professional mark jobs. I didn't want 339 00:19:40,720 --> 00:19:43,399 Speaker 12: to say it, but you did. But the other thing 340 00:19:43,440 --> 00:19:47,119 Speaker 12: I want to say that as a big shortcoming of 341 00:19:47,200 --> 00:19:52,280 Speaker 12: these systems is that they're often inaccurate. I shouldn't say often, 342 00:19:52,400 --> 00:19:56,560 Speaker 12: but often enough that it's a problem. Open AI will 343 00:19:56,600 --> 00:20:01,360 Speaker 12: not say how often these systems get things wrong. I've 344 00:20:01,400 --> 00:20:03,840 Speaker 12: asked it, but my own experience, it's just I think 345 00:20:03,880 --> 00:20:06,920 Speaker 12: it's somewhere between five and fifteen percent of the answers 346 00:20:06,920 --> 00:20:10,560 Speaker 12: that it's given me are factually incorrect. Now, think about 347 00:20:11,080 --> 00:20:15,080 Speaker 12: using that as a search tool. We use search to 348 00:20:15,160 --> 00:20:19,680 Speaker 12: get information, to get facts, and if it's wrong ten 349 00:20:19,720 --> 00:20:22,400 Speaker 12: percent of the time, are people really going to want 350 00:20:22,440 --> 00:20:24,159 Speaker 12: to use it? I think that's going to be a 351 00:20:24,240 --> 00:20:28,240 Speaker 12: real problem for these companies using these systems, for as 352 00:20:28,280 --> 00:20:29,760 Speaker 12: search engine companions. 353 00:20:30,240 --> 00:20:30,760 Speaker 8: It's not a. 354 00:20:30,720 --> 00:20:36,520 Speaker 12: Trivial issue because recently Microsoft and Google had these big 355 00:20:36,560 --> 00:20:41,320 Speaker 12: announcements about their new chat companions, these chatbots that we're 356 00:20:41,359 --> 00:20:43,480 Speaker 12: going to help Bang and we're going to help Google. 357 00:20:44,280 --> 00:20:47,600 Speaker 12: And in both demonstrations there were errors. So if they 358 00:20:47,600 --> 00:20:50,359 Speaker 12: can't even fact check that and get that right, what 359 00:20:50,400 --> 00:20:52,359 Speaker 12: are these systems going to be like when they're actually 360 00:20:52,359 --> 00:20:53,080 Speaker 12: out in the wild. 361 00:20:54,000 --> 00:20:57,200 Speaker 1: My lessons about AI keep mounting since that episode aired. 362 00:20:57,760 --> 00:21:01,240 Speaker 1: AI is everywhere and it's changing everything and we all 363 00:21:01,280 --> 00:21:09,600 Speaker 1: will have to learn to adapt. And I can't look 364 00:21:09,640 --> 00:21:13,679 Speaker 1: back at twenty twenty three without talking about Barbie. The 365 00:21:13,720 --> 00:21:16,960 Speaker 1: summer blockbuster film took the world by storm and generated 366 00:21:17,000 --> 00:21:20,400 Speaker 1: more hot takes than people expected. So I sat down 367 00:21:20,400 --> 00:21:23,520 Speaker 1: with Emma Gray, a pop culture commentator and the author 368 00:21:23,560 --> 00:21:26,760 Speaker 1: of A Girl's Guide to Joining the Resistance. Here's what 369 00:21:26,880 --> 00:21:29,800 Speaker 1: Emma learned from witnessing Barbie mania. 370 00:21:30,160 --> 00:21:32,919 Speaker 11: I think this really drove home for me that you 371 00:21:33,040 --> 00:21:37,960 Speaker 11: really can take a cultural product that is complicated, that 372 00:21:38,119 --> 00:21:42,040 Speaker 11: is controversial, that is not politically perfect, and you can 373 00:21:42,160 --> 00:21:47,560 Speaker 11: use it to say something real and complicated and trigger 374 00:21:47,840 --> 00:21:53,400 Speaker 11: real and complex discourse. And I think that this has 375 00:21:53,480 --> 00:21:57,840 Speaker 11: really redefined for me what I look at as selling 376 00:21:57,920 --> 00:22:01,760 Speaker 11: out and yeah, the ways that you can take a 377 00:22:01,760 --> 00:22:05,800 Speaker 11: cultural product that might seem silly and surface level and 378 00:22:05,840 --> 00:22:08,280 Speaker 11: turn it into a story that has real heart and 379 00:22:08,280 --> 00:22:10,120 Speaker 11: can actually teach us something about ourselves. 380 00:22:11,520 --> 00:22:16,199 Speaker 1: Here's a little song for you. I'm just Tim, but 381 00:22:16,280 --> 00:22:18,840 Speaker 1: I learned a lot from Barbie and the cultural phenomenon 382 00:22:18,840 --> 00:22:21,760 Speaker 1: it sparked. Mostly, I learned that we all need to 383 00:22:21,800 --> 00:22:24,280 Speaker 1: keep our minds, eyes, and hearts open to what all 384 00:22:24,320 --> 00:22:27,280 Speaker 1: the people around us want neat, even if they're bad singers. 385 00:22:30,400 --> 00:22:33,720 Speaker 1: Thanks for listening to this special recap episode of Crash Course. 386 00:22:34,359 --> 00:22:36,320 Speaker 1: Check out the show notes to links to all of 387 00:22:36,320 --> 00:22:40,359 Speaker 1: the episodes mentioned in today's show. Here at Crash Course, 388 00:22:40,440 --> 00:22:44,280 Speaker 1: we believe the collisions can be messy, impressive, challenging, surprising, 389 00:22:44,560 --> 00:22:48,520 Speaker 1: and always instructive. In today's Crash Course, I was reminded 390 00:22:48,520 --> 00:22:50,480 Speaker 1: that you can learn about a whole bunch of different 391 00:22:50,520 --> 00:22:53,240 Speaker 1: important topics over the course of one year's worth of 392 00:22:53,280 --> 00:22:56,600 Speaker 1: podcast episodes, and I'm excited to keep learning more with 393 00:22:56,640 --> 00:22:59,640 Speaker 1: you in the coming year. What did you learn? We'd 394 00:22:59,640 --> 00:23:01,680 Speaker 1: love to hear from you. You can tweet at the 395 00:23:01,680 --> 00:23:05,800 Speaker 1: Bloomberg Opinion handle at Opinion or me at Tim O'Brien 396 00:23:06,160 --> 00:23:10,240 Speaker 1: using the hashtag Bloomberg Crash Course. You can also subscribe 397 00:23:10,240 --> 00:23:12,760 Speaker 1: to our show wherever you're listening right now and leave 398 00:23:12,800 --> 00:23:15,520 Speaker 1: us a review that helps more people find the show. 399 00:23:16,640 --> 00:23:19,879 Speaker 1: This episode was produced as they all were all year long, 400 00:23:20,359 --> 00:23:24,840 Speaker 1: by the indispensable Anna Mazarakus and me, our supervising producers 401 00:23:24,840 --> 00:23:27,760 Speaker 1: Magus Hendrickson, and we had editing help from Sage Bauman, 402 00:23:28,119 --> 00:23:33,040 Speaker 1: Jeff Grocott, Mike Niitza and Christine Vanden Bilart. Blake Maples 403 00:23:33,080 --> 00:23:35,800 Speaker 1: does our sound engineering as he did all year long, 404 00:23:36,280 --> 00:23:38,880 Speaker 1: and our original theme song was composed by Luis Gara. 405 00:23:39,440 --> 00:23:42,080 Speaker 1: I'm Tim O'Brien. We'll be back next week with a 406 00:23:42,119 --> 00:23:43,440 Speaker 1: new episode of Crash Course.