1 00:00:01,600 --> 00:00:04,080 Speaker 1: We've talked quite a lot on this show lately about 2 00:00:04,200 --> 00:00:08,520 Speaker 1: artificial intelligence because of how quickly it's inserted itself into 3 00:00:08,560 --> 00:00:12,080 Speaker 1: so many parts of our lives, and how it's becoming 4 00:00:12,160 --> 00:00:16,759 Speaker 1: more and more difficult to tell what's real and what's fabricated. 5 00:00:17,800 --> 00:00:22,360 Speaker 1: One place where that's increasingly becoming a problem politics, especially 6 00:00:22,400 --> 00:00:26,360 Speaker 1: now as the twenty twenty four US presidential campaign heats up. 7 00:00:26,720 --> 00:00:32,280 Speaker 2: EI artificial intelligence is now hitting the US presidential campaign trail. 8 00:00:33,080 --> 00:00:36,760 Speaker 2: Donald Trump has been got in a series of aidep 9 00:00:36,920 --> 00:00:41,520 Speaker 2: figs this time. Ron DeSantis is also in the spotlight. 10 00:00:41,600 --> 00:00:45,040 Speaker 2: Reports say Desamptus published fake images of Donald Trump and 11 00:00:45,120 --> 00:00:46,040 Speaker 2: Anthony Fauci. 12 00:00:46,440 --> 00:00:51,880 Speaker 1: Already, candidates and their surrogates and even bad actors overseas 13 00:00:51,960 --> 00:00:54,280 Speaker 1: are reaching for every tool they can to try to 14 00:00:54,320 --> 00:00:58,640 Speaker 1: shape voters' perceptions and ultimately influence the outcome. 15 00:00:59,000 --> 00:01:02,160 Speaker 3: There is steph an arms race when it comes to AI, 16 00:01:02,480 --> 00:01:05,679 Speaker 3: but there is an element of mutually assured destruction. 17 00:01:05,880 --> 00:01:08,560 Speaker 1: And the government is struggling to figure out how to 18 00:01:08,640 --> 00:01:11,240 Speaker 1: police the use of AI in campaigns. 19 00:01:11,680 --> 00:01:14,560 Speaker 4: What makes the FEC really interesting in this is that 20 00:01:14,600 --> 00:01:17,640 Speaker 4: they are by designing a partisan agency with a mix 21 00:01:17,680 --> 00:01:20,480 Speaker 4: of Republicans and Democrats and so across the board, you 22 00:01:20,520 --> 00:01:29,319 Speaker 4: really see them deadlocking on almost every issue. 23 00:01:30,720 --> 00:01:33,720 Speaker 1: I'm west Caasova today on The Big Take, Bloomberg's Emily 24 00:01:33,760 --> 00:01:38,039 Speaker 1: Burnbaum and Laura Davison tell us how AI is transforming 25 00:01:38,400 --> 00:01:46,640 Speaker 1: and distorting our political reality. Emily, it seems like it 26 00:01:46,680 --> 00:01:51,240 Speaker 1: took about five minutes after AI really came forward as 27 00:01:51,240 --> 00:01:54,640 Speaker 1: a thing that was easily accessible for the political world 28 00:01:54,720 --> 00:01:57,600 Speaker 1: to say, hey, we can use this for all kinds 29 00:01:57,640 --> 00:02:00,920 Speaker 1: of reasons, some good and some real not so good. 30 00:02:02,320 --> 00:02:05,720 Speaker 3: Yeah, we're still really in the early stages of this. 31 00:02:05,880 --> 00:02:09,720 Speaker 3: We've yet to see the most dramatic examples of political 32 00:02:09,760 --> 00:02:13,480 Speaker 3: misinformation thanks to generative AI, but there are a couple 33 00:02:13,600 --> 00:02:17,880 Speaker 3: really big and well known examples that have been circulating. 34 00:02:18,120 --> 00:02:22,160 Speaker 3: So some far right politicians in Germany used AI to 35 00:02:22,440 --> 00:02:26,040 Speaker 3: generate images of immigrants that look very angry and violent. 36 00:02:26,720 --> 00:02:30,480 Speaker 3: No one was real, just you know, meant to incite 37 00:02:30,760 --> 00:02:34,839 Speaker 3: sort of nationalist fervor. Here back in the US, we're 38 00:02:34,880 --> 00:02:39,000 Speaker 3: seeing a lot more of that. So presidential candidate Ron 39 00:02:39,080 --> 00:02:44,280 Speaker 3: DeSantis his campaign arm put out a video that included 40 00:02:44,400 --> 00:02:49,680 Speaker 3: images of Anthony Fauci hugging former President Donald Trump, and 41 00:02:49,960 --> 00:02:53,960 Speaker 3: they were not real. So Desantas's campaign didn't say that 42 00:02:54,080 --> 00:02:58,600 Speaker 3: they were AI generated, but experts kind of circled and 43 00:02:58,720 --> 00:03:02,680 Speaker 3: identified them as fake, and then within a couple hours 44 00:03:02,720 --> 00:03:05,120 Speaker 3: there was a Twitter note appended to it saying these 45 00:03:05,160 --> 00:03:08,400 Speaker 3: are not real. And the other big example is the 46 00:03:08,440 --> 00:03:12,760 Speaker 3: Republican National Committee put together an AI generated video that 47 00:03:12,880 --> 00:03:16,040 Speaker 3: purported to show, you know, here's the future that Biden wants, 48 00:03:16,080 --> 00:03:19,919 Speaker 3: and it was very dystopian and disturbing. They actually said 49 00:03:19,960 --> 00:03:22,720 Speaker 3: it was AI generated. 50 00:03:23,520 --> 00:03:25,600 Speaker 4: Yeah, this video was really quite disturbing. You know. It 51 00:03:25,680 --> 00:03:29,040 Speaker 4: showed images of China attacking Taiwan. It showed the streets 52 00:03:29,080 --> 00:03:31,760 Speaker 4: of San Francisco with troops marching in as martial law 53 00:03:31,840 --> 00:03:34,680 Speaker 4: was taking over, and those looked very very real. The 54 00:03:34,680 --> 00:03:37,080 Speaker 4: one tailtale sign at the end of this video that 55 00:03:37,120 --> 00:03:40,040 Speaker 4: it was fake was it showed Joe Biden just slumped 56 00:03:40,080 --> 00:03:42,960 Speaker 4: over his desk, looking really dejected, and you could see 57 00:03:42,960 --> 00:03:45,040 Speaker 4: that his elbows weren't quite connecting with the edge of 58 00:03:45,040 --> 00:03:47,680 Speaker 4: the desk. So it also had a little disclaimer, very 59 00:03:47,760 --> 00:03:50,360 Speaker 4: very tiny in the corner saying this was AI generated. 60 00:03:50,400 --> 00:03:52,200 Speaker 4: But one of the things that consumers are gonna have 61 00:03:52,280 --> 00:03:54,920 Speaker 4: to start doing is be really good about determining what 62 00:03:55,080 --> 00:03:57,760 Speaker 4: video is fake and what is real? And there's always 63 00:03:57,800 --> 00:04:00,400 Speaker 4: with AI, the technology is pretty good, but you know, 64 00:04:00,440 --> 00:04:03,800 Speaker 4: sometimes people have six fingers on the Fauci and Trump 65 00:04:03,920 --> 00:04:07,320 Speaker 4: hugging images. You know, it looked very airbrushed. Trump's hair 66 00:04:07,360 --> 00:04:10,000 Speaker 4: looked very weird in certain angles. So that's kind of 67 00:04:10,160 --> 00:04:12,520 Speaker 4: a telltale sign if you think something looks weird and 68 00:04:12,520 --> 00:04:13,960 Speaker 4: you're like, look at the hands, look at the feet, 69 00:04:13,960 --> 00:04:15,960 Speaker 4: look at the limbs, look at some of these features. 70 00:04:15,960 --> 00:04:18,520 Speaker 4: They look a little bit distorted, and that's usually a 71 00:04:18,560 --> 00:04:20,080 Speaker 4: sign that something is a little off. 72 00:04:20,680 --> 00:04:23,240 Speaker 1: I remember in the last election we started thinking about 73 00:04:23,320 --> 00:04:27,679 Speaker 1: deep face, these videos, these pictures which are indistinguishable from 74 00:04:27,920 --> 00:04:31,360 Speaker 1: what's real, and the technology wasn't quite there yet, And now, 75 00:04:31,400 --> 00:04:33,799 Speaker 1: of course we see every day that it is getting 76 00:04:33,880 --> 00:04:36,080 Speaker 1: much better. And I guess that raises this question that 77 00:04:36,200 --> 00:04:39,479 Speaker 1: as the campaign heats up, we're going to see so 78 00:04:39,720 --> 00:04:41,839 Speaker 1: many of these images that it's going to be really 79 00:04:41,839 --> 00:04:45,279 Speaker 1: hard to tell what's real and what's not correct. 80 00:04:45,320 --> 00:04:49,720 Speaker 4: And there's no regulation that requires any person, any advertiser, 81 00:04:49,800 --> 00:04:53,839 Speaker 4: any candidate to declare something as fake. Google has said 82 00:04:54,120 --> 00:04:55,920 Speaker 4: that in their tools that they are going to have 83 00:04:56,080 --> 00:04:58,320 Speaker 4: not a physical marker on it, but sort of a 84 00:04:58,360 --> 00:05:01,200 Speaker 4: digital marker, So if people go and reverse image search 85 00:05:01,240 --> 00:05:03,040 Speaker 4: it, it will flag it as something that's fake. But that's 86 00:05:03,240 --> 00:05:05,800 Speaker 4: how often do you go and actually reverse image search something. 87 00:05:06,360 --> 00:05:08,599 Speaker 4: Not that often, So it's going to really take a 88 00:05:08,600 --> 00:05:11,920 Speaker 4: lot of discerning, both from kind of the truth squatting 89 00:05:12,040 --> 00:05:14,760 Speaker 4: faction on Twitter as well as from individual consumers to 90 00:05:14,800 --> 00:05:16,560 Speaker 4: know if something's real or fake. And as we know, 91 00:05:16,640 --> 00:05:18,040 Speaker 4: a lot of people don't even know who's running for 92 00:05:18,080 --> 00:05:18,839 Speaker 4: president right now. 93 00:05:19,320 --> 00:05:23,839 Speaker 3: Yeah, just on the topic of regulation not being in place, 94 00:05:24,120 --> 00:05:27,359 Speaker 3: the Federal Election Commission this month tried to vote on 95 00:05:27,600 --> 00:05:31,039 Speaker 3: a measure that would have enabled them to create rules 96 00:05:31,480 --> 00:05:36,200 Speaker 3: around AI generated political ads. Basically, the FEC would say 97 00:05:36,320 --> 00:05:39,800 Speaker 3: you have to declare when AI has generated your ad. 98 00:05:40,160 --> 00:05:43,119 Speaker 3: But they found themselves deadlocked. So there was a deep 99 00:05:43,160 --> 00:05:46,760 Speaker 3: disagreement among the commissioners, not even just along partisan lines, 100 00:05:46,960 --> 00:05:49,600 Speaker 3: about if they even have the authority to do that. 101 00:05:50,040 --> 00:05:55,640 Speaker 3: So the agencies that we have are currently deadlocked, unsure 102 00:05:55,640 --> 00:05:58,599 Speaker 3: how to proceed, and on Capitol Hill they're only beginning 103 00:05:58,600 --> 00:06:01,200 Speaker 3: to have these conversations. 104 00:06:02,480 --> 00:06:06,320 Speaker 1: Emily, why would the Federal Election Commission have any doubts 105 00:06:06,360 --> 00:06:08,400 Speaker 1: about what to do? Is there anyone in favor of 106 00:06:08,440 --> 00:06:11,640 Speaker 1: allowing fake stuff to be spread all over the place 107 00:06:11,680 --> 00:06:12,839 Speaker 1: without having to be labeled. 108 00:06:13,360 --> 00:06:16,599 Speaker 3: It's less about the actual measure and more about if 109 00:06:16,720 --> 00:06:19,599 Speaker 3: the FEC has the authority to do this. So we 110 00:06:19,640 --> 00:06:22,800 Speaker 3: actually run into this with tech related issues and our 111 00:06:22,839 --> 00:06:26,240 Speaker 3: government all the time. Most of these agencies weren't set 112 00:06:26,320 --> 00:06:30,880 Speaker 3: up to deal with issues like deep fakes, misinformation scams online, 113 00:06:31,000 --> 00:06:33,440 Speaker 3: and so they're having to adapt in real time, and 114 00:06:33,480 --> 00:06:37,240 Speaker 3: the FEC, some of the commissioners at least say that 115 00:06:37,279 --> 00:06:40,480 Speaker 3: they just don't have power over this part of the lot. 116 00:06:40,920 --> 00:06:44,720 Speaker 3: There are a lot of protections for political speech that 117 00:06:44,960 --> 00:06:48,880 Speaker 3: is an important bedrock of communication in America, so that 118 00:06:49,000 --> 00:06:51,400 Speaker 3: makes this issue even more difficult to deal with. 119 00:06:51,920 --> 00:06:54,800 Speaker 4: What makes the FEC really interesting in this is that 120 00:06:54,839 --> 00:06:57,880 Speaker 4: they are by designing a partisan agency with a mix 121 00:06:57,920 --> 00:07:00,920 Speaker 4: of Republicans and Democrats, and across the board you really 122 00:07:00,920 --> 00:07:04,440 Speaker 4: see them deadlocking on almost every issue. The FEC has 123 00:07:04,480 --> 00:07:07,480 Speaker 4: had very little success doing anything, which just points to 124 00:07:07,520 --> 00:07:10,320 Speaker 4: that the FEC realistically isn't going to be able to 125 00:07:10,320 --> 00:07:12,720 Speaker 4: take this one on based on all the other issues 126 00:07:12,720 --> 00:07:14,920 Speaker 4: facing the agency, and what about. 127 00:07:14,720 --> 00:07:19,000 Speaker 1: The candidates themselves. It's easy to put something out that's 128 00:07:19,040 --> 00:07:21,720 Speaker 1: fake about your opponent and maybe it gets you all 129 00:07:21,800 --> 00:07:23,560 Speaker 1: kinds of attention, but then you know they're going to 130 00:07:23,560 --> 00:07:26,400 Speaker 1: be doing it about you too, And so there's this 131 00:07:26,520 --> 00:07:29,520 Speaker 1: kind of AI fakery arms race that we seem to 132 00:07:29,560 --> 00:07:31,920 Speaker 1: be setting up. Is there any recognition on the part 133 00:07:31,960 --> 00:07:34,320 Speaker 1: of the campaigns that this is a really bad line 134 00:07:34,360 --> 00:07:34,880 Speaker 1: to cross? 135 00:07:36,280 --> 00:07:39,480 Speaker 3: So there is definitely an arms race when it comes 136 00:07:39,480 --> 00:07:42,480 Speaker 3: to AI, but there is an element of mutually assured 137 00:07:42,480 --> 00:07:46,400 Speaker 3: destruction where as soon as one campaign really goes out, 138 00:07:46,720 --> 00:07:49,200 Speaker 3: puts some words in their opponent's mouth that makes them 139 00:07:49,200 --> 00:07:53,960 Speaker 3: look bad, distributes images videos widely, then that sort of 140 00:07:54,160 --> 00:07:57,160 Speaker 3: opens this whole can of worms, and so there's going 141 00:07:57,240 --> 00:07:59,880 Speaker 3: to be tons of these kinds of ads, and actually 142 00:07:59,880 --> 00:08:03,480 Speaker 3: no one really wants that. So there's some internal reckoning 143 00:08:03,560 --> 00:08:07,800 Speaker 3: that's happening among political consultants and campaigns right now. 144 00:08:08,000 --> 00:08:10,160 Speaker 1: I guess they've been coming from these outside groups that 145 00:08:10,280 --> 00:08:12,680 Speaker 1: support campaigns so that they're able to have a certain 146 00:08:12,680 --> 00:08:17,040 Speaker 1: amount of deniability even though it's very clear which candidate 147 00:08:17,080 --> 00:08:17,760 Speaker 1: they're supporting. 148 00:08:18,200 --> 00:08:21,560 Speaker 4: But it creates for what we call like dark money groups. 149 00:08:21,560 --> 00:08:24,320 Speaker 4: So five H one C four political advacy groups. This 150 00:08:24,360 --> 00:08:26,160 Speaker 4: is a real wide opening for you know, groups that 151 00:08:26,200 --> 00:08:29,360 Speaker 4: aren't necessarily representing a specific person, but an interest area 152 00:08:29,600 --> 00:08:32,320 Speaker 4: or a larger party. The dark money groups, they can 153 00:08:32,360 --> 00:08:34,280 Speaker 4: go out and take all these images and they're super 154 00:08:34,360 --> 00:08:36,920 Speaker 4: cheap and easy to produce, so they can react in 155 00:08:36,960 --> 00:08:39,360 Speaker 4: real time. If something is said in a debate about 156 00:08:39,360 --> 00:08:41,160 Speaker 4: a candidate they don't like, they can have an image 157 00:08:41,240 --> 00:08:43,440 Speaker 4: or a video out there online by the end of 158 00:08:43,440 --> 00:08:45,320 Speaker 4: the debate. So that's what we're going to start to 159 00:08:45,320 --> 00:08:47,320 Speaker 4: see if this really rapid response. You know, what we 160 00:08:47,400 --> 00:08:49,400 Speaker 4: used to just see with with tweets or emails can 161 00:08:49,440 --> 00:08:52,000 Speaker 4: now be done with images and videos. 162 00:08:54,559 --> 00:08:57,280 Speaker 1: Laurie, we've been talking about how we're seeing this happening 163 00:08:57,320 --> 00:09:01,079 Speaker 1: at the national level, at the presidential level, but it's 164 00:09:01,120 --> 00:09:04,800 Speaker 1: also filtering down throughout politics in the US. 165 00:09:05,440 --> 00:09:05,680 Speaker 2: Yeah. 166 00:09:05,679 --> 00:09:08,000 Speaker 4: So AI is really cheap, and so that makes it 167 00:09:08,040 --> 00:09:11,040 Speaker 4: a really great tool for these smaller campaigns that don't 168 00:09:11,040 --> 00:09:12,400 Speaker 4: have a lot of money, that don't have a lot 169 00:09:12,400 --> 00:09:15,720 Speaker 4: of staff. So there's been in some mayoral elections recently 170 00:09:15,920 --> 00:09:19,120 Speaker 4: AI used both by campaigns to sort of support themselves 171 00:09:19,280 --> 00:09:21,880 Speaker 4: as well as attack ads. There was a really great 172 00:09:21,920 --> 00:09:24,560 Speaker 4: example in Shreveport, Louisiana, where there was an attack ad 173 00:09:24,640 --> 00:09:28,240 Speaker 4: against the incumbent Mayor Adrian Perkins, and it showed this 174 00:09:28,400 --> 00:09:30,640 Speaker 4: scene where it was you know, it was his face 175 00:09:30,720 --> 00:09:33,200 Speaker 4: on a body and his voice was talking, his mouth 176 00:09:33,280 --> 00:09:34,840 Speaker 4: was moving. It wasn't him, it was an actor and 177 00:09:34,840 --> 00:09:36,920 Speaker 4: then they had used AI to create it to make 178 00:09:36,960 --> 00:09:39,120 Speaker 4: it look like him. He ended up losing this race, 179 00:09:39,200 --> 00:09:41,640 Speaker 4: not necessarily because of this ad, but just a really 180 00:09:41,640 --> 00:09:44,600 Speaker 4: great example of how someone a developer in town who 181 00:09:44,640 --> 00:09:46,920 Speaker 4: didn't particularly care for the mayor could come in and 182 00:09:46,960 --> 00:09:50,160 Speaker 4: create this ad really quickly, easily and cheaply, and get 183 00:09:50,200 --> 00:09:52,160 Speaker 4: it on the airwaves and really make a splash with it. 184 00:09:52,800 --> 00:09:55,000 Speaker 4: In Toronto, we also saw the same thing in their 185 00:09:55,040 --> 00:09:59,840 Speaker 4: mayoral race, where candidate Anthony Fury used artificial intelligence images 186 00:10:00,000 --> 00:10:02,520 Speaker 4: in sort of his campaign materials, you know, showing packages 187 00:10:02,600 --> 00:10:05,040 Speaker 4: of crack pipe kits that were sponsored by the City 188 00:10:05,080 --> 00:10:07,600 Speaker 4: of Toronto, you know, using this to criticize policies of 189 00:10:07,600 --> 00:10:08,280 Speaker 4: his opponents. 190 00:10:08,679 --> 00:10:12,520 Speaker 1: Emily, you talked about how difficult it is for the 191 00:10:12,520 --> 00:10:14,760 Speaker 1: government to try and figure out how and whether they 192 00:10:14,760 --> 00:10:18,920 Speaker 1: can regulate this. Is there anything illegal about a candidate 193 00:10:19,679 --> 00:10:24,360 Speaker 1: making another candidate appear to be doing something completely false? 194 00:10:25,200 --> 00:10:29,400 Speaker 3: One use of AI that could be illegal, And we 195 00:10:29,440 --> 00:10:32,520 Speaker 3: can remember this is still an untested area of the 196 00:10:32,640 --> 00:10:35,559 Speaker 3: law in many ways, so we're not positive. But one 197 00:10:35,880 --> 00:10:38,680 Speaker 3: thing that could be illegal is if you use a 198 00:10:38,720 --> 00:10:44,560 Speaker 3: candidate's likeness to get money that the candidate doesn't actually receive. 199 00:10:45,080 --> 00:10:48,319 Speaker 3: So that is one thing that the FBC was discussing 200 00:10:48,600 --> 00:10:51,839 Speaker 3: that seems like a clear violation of our campaign laws 201 00:10:51,920 --> 00:10:54,960 Speaker 3: when you are not allowed to impersonate anyone else and 202 00:10:55,000 --> 00:10:58,000 Speaker 3: not allowed to lie about where money is going. There 203 00:10:58,080 --> 00:11:01,600 Speaker 3: are also laws dropping up in the states across the 204 00:11:01,640 --> 00:11:06,360 Speaker 3: country that ban certain kinds of quote unquote deep fakes. 205 00:11:06,400 --> 00:11:10,160 Speaker 3: So a lot of those laws pertained to pornography. So 206 00:11:10,200 --> 00:11:13,440 Speaker 3: there have been some reports that show over ninety percent 207 00:11:13,640 --> 00:11:17,120 Speaker 3: of the deep fakes on the Internet are pornographic images, 208 00:11:17,480 --> 00:11:22,600 Speaker 3: mostly featuring women, and so a bunch of states have 209 00:11:23,480 --> 00:11:26,160 Speaker 3: rushed in to fill this gap in the law, basically 210 00:11:26,280 --> 00:11:30,240 Speaker 3: just improving victims' rights, so people who were featured in 211 00:11:30,280 --> 00:11:34,440 Speaker 3: pornographic images on the internet can sue and have the 212 00:11:34,520 --> 00:11:37,360 Speaker 3: right to stop the proliferation of those. But there are 213 00:11:37,440 --> 00:11:41,640 Speaker 3: far fewer rules about election related deep fakes. There are 214 00:11:41,679 --> 00:11:47,559 Speaker 3: some they probably won't withstand legal challenges, so it's still 215 00:11:47,640 --> 00:11:50,920 Speaker 3: kind of complicated. Whenever you try to touch political speech, 216 00:11:51,320 --> 00:11:55,400 Speaker 3: but there are clearer violations after the break. 217 00:11:55,440 --> 00:11:59,920 Speaker 1: How AI is changing the way campaigns get their message. 218 00:11:59,520 --> 00:12:11,200 Speaker 5: Out, Laurie, you hinted a little bit before about how 219 00:12:11,240 --> 00:12:15,040 Speaker 5: campaigns are using AI for non nefarious reasons, that it's 220 00:12:15,040 --> 00:12:17,880 Speaker 5: just like become a useful tool being used by campaigns 221 00:12:17,920 --> 00:12:20,200 Speaker 5: the way it's used by a lot of different industries. 222 00:12:20,600 --> 00:12:22,640 Speaker 4: Yeah, so there's a bunch of different things that campaigns 223 00:12:22,640 --> 00:12:24,679 Speaker 4: are using and some that people would kind of clearly 224 00:12:24,679 --> 00:12:28,040 Speaker 4: put into a non nefarious camp. So things like helping 225 00:12:28,280 --> 00:12:31,080 Speaker 4: use AI to analyze voter rolls of people that they 226 00:12:31,080 --> 00:12:34,760 Speaker 4: should be targeting, organizing some of their data, figuring out 227 00:12:34,760 --> 00:12:38,360 Speaker 4: what kind of messages would resonate with which voters. Another 228 00:12:38,480 --> 00:12:41,080 Speaker 4: thing that they're doing is using tools like chat GBT, 229 00:12:41,240 --> 00:12:44,040 Speaker 4: not necessarily chat GPT because that tool has some restrictions 230 00:12:44,040 --> 00:12:46,680 Speaker 4: on political speech, but to write the first drafts of 231 00:12:46,800 --> 00:12:50,520 Speaker 4: press releases of fundraising emails. And they found a really 232 00:12:50,559 --> 00:12:54,480 Speaker 4: great cost savings instead of having five people who are 233 00:12:54,559 --> 00:12:57,599 Speaker 4: copywriters on a campaign working on all these messages, that 234 00:12:57,640 --> 00:13:00,400 Speaker 4: you'd have one person that is just telling the tool, okay, 235 00:13:00,440 --> 00:13:04,160 Speaker 4: write a fundraising email with a focus on democracy, right, 236 00:13:04,200 --> 00:13:06,000 Speaker 4: one with a focus on the environment right one with 237 00:13:06,040 --> 00:13:10,160 Speaker 4: a focus on defeeding Republicans, for example, and then they 238 00:13:10,200 --> 00:13:12,400 Speaker 4: can get something on the page and then just edit 239 00:13:12,440 --> 00:13:15,680 Speaker 4: it and it goes much much quicker. The one campaign 240 00:13:15,720 --> 00:13:18,200 Speaker 4: consultant described this as solving the blank page problem. Anyone 241 00:13:18,200 --> 00:13:20,640 Speaker 4: who's ever written anything can probably sympathize with that if 242 00:13:20,640 --> 00:13:22,319 Speaker 4: it's much easier to get something on the paper and 243 00:13:22,360 --> 00:13:25,160 Speaker 4: then edit it versus just starting from scratch. So they're 244 00:13:25,200 --> 00:13:27,400 Speaker 4: finding really big cost savings in that of they're able 245 00:13:27,440 --> 00:13:30,760 Speaker 4: to both raise more money because they're more effectively targeting 246 00:13:30,760 --> 00:13:33,160 Speaker 4: people as well as cut down on staff cost for 247 00:13:33,400 --> 00:13:36,640 Speaker 4: that particular function of writing. That's been really widespread and 248 00:13:36,880 --> 00:13:40,320 Speaker 4: one consultant estimated about fifty percent of campaigns are doing this, 249 00:13:40,440 --> 00:13:42,840 Speaker 4: but expect that number to be somewhere closer to one 250 00:13:42,920 --> 00:13:44,640 Speaker 4: hundred by the end of the twenty twenty four cycle. 251 00:13:45,120 --> 00:13:48,560 Speaker 3: But Congress just set new rules on how staffers can 252 00:13:48,720 --> 00:13:52,280 Speaker 3: use chat GPT, and the main concern is that a 253 00:13:52,320 --> 00:13:56,800 Speaker 3: lot of what you put into chat GPT can become 254 00:13:57,080 --> 00:13:59,720 Speaker 3: available in other ways. You know, there are a lot 255 00:13:59,720 --> 00:14:03,520 Speaker 3: of privacy concerns around chat GPT. So the new rules say, 256 00:14:04,040 --> 00:14:06,400 Speaker 3: first of all, you have to use the paid for 257 00:14:06,720 --> 00:14:11,439 Speaker 3: version of chatchept, which is better protective of privacy. Second 258 00:14:11,480 --> 00:14:14,840 Speaker 3: of all, you can't put confidential information into chat GPT, 259 00:14:15,240 --> 00:14:18,480 Speaker 3: which congressional staffers are often working with, so they're kind 260 00:14:18,559 --> 00:14:21,080 Speaker 3: of like making it up as they go along. But 261 00:14:21,360 --> 00:14:24,680 Speaker 3: congressional staffers work all day and night. They are never 262 00:14:24,760 --> 00:14:26,760 Speaker 3: off the clock, and so anything that cuts back on 263 00:14:26,960 --> 00:14:28,320 Speaker 3: time is really valuable. 264 00:14:31,400 --> 00:14:35,360 Speaker 1: Open AI. The makers of chat GPT, they are kind 265 00:14:35,400 --> 00:14:39,080 Speaker 1: of alarmed at the way campaigns could be using their 266 00:14:39,120 --> 00:14:41,280 Speaker 1: technology and or trying to figure out a way to 267 00:14:41,360 --> 00:14:41,840 Speaker 1: limit it. 268 00:14:42,320 --> 00:14:44,600 Speaker 4: If you put in really anything related to politics and 269 00:14:44,680 --> 00:14:48,040 Speaker 4: chat gept, there's sort of this standard disclaimer language coming 270 00:14:48,120 --> 00:14:49,640 Speaker 4: up of saying, you know, look, I don't have an 271 00:14:49,680 --> 00:14:52,360 Speaker 4: opinion on this. There's nuance to this, and so chat 272 00:14:52,440 --> 00:14:56,160 Speaker 4: GPT is being very careful with anything related to politics. 273 00:14:56,200 --> 00:14:57,880 Speaker 4: But if you push it a little bit, like if 274 00:14:57,920 --> 00:15:00,520 Speaker 4: you type who are the wokest Democrats, it will name 275 00:15:00,720 --> 00:15:05,120 Speaker 4: Alexandria Kazi Kort, says Rashida talib Aana Presley Bill on Omar. 276 00:15:05,440 --> 00:15:07,280 Speaker 4: Interesting that all like the top four or five names 277 00:15:07,280 --> 00:15:09,280 Speaker 4: that came up were all women. Sort of treading this 278 00:15:09,320 --> 00:15:12,080 Speaker 4: careful line, it's not completely staying out of the political arena. 279 00:15:12,600 --> 00:15:15,800 Speaker 4: So for a lot of political things, chat gibt has 280 00:15:15,840 --> 00:15:19,840 Speaker 4: basically stopped cataloging language from after September twenty twenty one, 281 00:15:20,080 --> 00:15:22,760 Speaker 4: So when you ask chat gibt a political question will 282 00:15:22,800 --> 00:15:25,400 Speaker 4: be like, here's my information as of September twenty twenty one. 283 00:15:25,600 --> 00:15:27,280 Speaker 4: You may need to do more research if you want 284 00:15:27,280 --> 00:15:29,520 Speaker 4: something more recent. So it's kind of just clamping down 285 00:15:29,560 --> 00:15:31,800 Speaker 4: and not feeding the beast, so to speak, with more 286 00:15:31,800 --> 00:15:34,480 Speaker 4: information to make it sort of an obsolete tool when 287 00:15:34,520 --> 00:15:35,840 Speaker 4: it comes to political speech. 288 00:15:36,040 --> 00:15:40,360 Speaker 3: They're also putting together something called classifiers, so open ai 289 00:15:40,600 --> 00:15:44,000 Speaker 3: is able to see what people put into chat GPT, 290 00:15:44,520 --> 00:15:47,240 Speaker 3: and so they're working hard now to figure out what 291 00:15:47,320 --> 00:15:52,200 Speaker 3: are the classifiers or identifying freezes that people use, where 292 00:15:52,280 --> 00:15:54,120 Speaker 3: when they're using those, you know that it's for a 293 00:15:54,120 --> 00:15:57,440 Speaker 3: political purpose, And then if that's happening, how can you 294 00:15:57,640 --> 00:16:01,400 Speaker 3: control what chat cept says in response? They really don't 295 00:16:01,400 --> 00:16:04,600 Speaker 3: want their product to be used to create lies and 296 00:16:04,640 --> 00:16:06,200 Speaker 3: misinformation that they're blamed for. 297 00:16:07,040 --> 00:16:09,120 Speaker 4: To sort of add though, CHATGBT is sort of the 298 00:16:09,160 --> 00:16:12,920 Speaker 4: big juggernaut and the industry of generative text AI, but 299 00:16:13,000 --> 00:16:15,280 Speaker 4: there's so many other tools that are being developed and 300 00:16:15,440 --> 00:16:18,680 Speaker 4: tools that are being developed specifically for political uses, so 301 00:16:18,760 --> 00:16:21,360 Speaker 4: usually these are paid tools that campaigns would subscribe to. 302 00:16:21,680 --> 00:16:24,000 Speaker 4: But just because chat GBT is sort of clamping down 303 00:16:24,000 --> 00:16:26,480 Speaker 4: on this, it doesn't mean that other actors can go 304 00:16:26,520 --> 00:16:29,440 Speaker 4: buy these tools that are specifically designed for this to 305 00:16:30,080 --> 00:16:31,840 Speaker 4: create some political misinformation. 306 00:16:32,680 --> 00:16:36,880 Speaker 1: Laura earlier, Emily painted this picture of mutual assured destruction 307 00:16:37,040 --> 00:16:39,520 Speaker 1: where if one candidate attacks the other and the other 308 00:16:39,600 --> 00:16:42,400 Speaker 1: attacks back, then everybody gets hurt. And in you're reporting, 309 00:16:42,440 --> 00:16:46,400 Speaker 1: you found that both Democrats and Republicans are using this technology, 310 00:16:46,400 --> 00:16:47,760 Speaker 1: but in slightly different ways. 311 00:16:48,880 --> 00:16:51,160 Speaker 4: So what we've seen in terms of the visual and 312 00:16:51,280 --> 00:16:54,120 Speaker 4: video side as Republicans using this more. We saw big 313 00:16:54,160 --> 00:16:56,920 Speaker 4: first video ad was the RNC attacking Biden. We saw 314 00:16:57,000 --> 00:17:00,400 Speaker 4: DeSantis attacking Trump with this. But both parties are definitely 315 00:17:00,480 --> 00:17:03,040 Speaker 4: using it, and probably Democrats are using it more. When 316 00:17:03,080 --> 00:17:05,600 Speaker 4: it comes to the text and generative AI, they have 317 00:17:05,760 --> 00:17:09,200 Speaker 4: firms that are using the text side a lot more. 318 00:17:09,400 --> 00:17:12,320 Speaker 4: That's really widespread among campaigns. This is a really hard 319 00:17:12,320 --> 00:17:14,919 Speaker 4: thing that's hard to track you know exactly how widespread 320 00:17:14,920 --> 00:17:18,480 Speaker 4: it is within either party. Democrats are definitely more cautious 321 00:17:18,680 --> 00:17:21,760 Speaker 4: on using the visual and image side. They kind of 322 00:17:21,800 --> 00:17:24,119 Speaker 4: like to say, look, we're being responsible here, We're not 323 00:17:24,200 --> 00:17:28,680 Speaker 4: going to create misinformation or deep fakes. Republicans, particularly because 324 00:17:28,680 --> 00:17:31,000 Speaker 4: they're going into a contested primary so they have more 325 00:17:31,040 --> 00:17:32,919 Speaker 4: going on right now, but they're a little bit more 326 00:17:32,960 --> 00:17:35,359 Speaker 4: willing to try out this tool and see how it works, 327 00:17:35,400 --> 00:17:37,960 Speaker 4: while Democrats are a little bit hanging back on the sidelines. 328 00:17:38,400 --> 00:17:41,439 Speaker 3: I spoke to a spokesperson for the Democratic National Committee 329 00:17:41,720 --> 00:17:47,160 Speaker 3: who said Democrats are wary of misinformation. There's a history 330 00:17:47,200 --> 00:17:50,800 Speaker 3: there that goes back to the twenty sixteen election. There 331 00:17:50,880 --> 00:17:55,840 Speaker 3: is a whole team dedicated to stopping misinformation at the DNC, 332 00:17:56,400 --> 00:17:59,359 Speaker 3: so that makes them extra cautious as they begin to 333 00:17:59,440 --> 00:18:03,160 Speaker 3: implement AI slowly into things like fundraising. 334 00:18:05,400 --> 00:18:08,480 Speaker 1: Emily, that's an interesting point that the Democrats are saying 335 00:18:08,480 --> 00:18:10,320 Speaker 1: that they're going to really need to be monitoring this. 336 00:18:10,400 --> 00:18:11,919 Speaker 1: Do you think that we're going to have now this 337 00:18:11,960 --> 00:18:16,920 Speaker 1: whole campaign industry where groups are doing AI checks similar 338 00:18:16,960 --> 00:18:18,560 Speaker 1: to the way we have fact checkers. 339 00:18:19,280 --> 00:18:24,880 Speaker 3: Yeah, there is this anxiety and wariness among political consultants 340 00:18:25,080 --> 00:18:28,880 Speaker 3: about how AI is going to be deployed. So the 341 00:18:29,000 --> 00:18:34,400 Speaker 3: trade Association for Political Consultants, which exists, shockingly came out 342 00:18:34,400 --> 00:18:37,639 Speaker 3: with this statement saying we are against the use of 343 00:18:37,680 --> 00:18:41,080 Speaker 3: deep fakes in political campaigns, and we really shouldn't be 344 00:18:41,160 --> 00:18:45,000 Speaker 3: messing too much with this technology. It's quite dangerous. So 345 00:18:45,200 --> 00:18:49,160 Speaker 3: I do think that increasingly there is desire to call 346 00:18:49,240 --> 00:18:53,719 Speaker 3: out misinformation, to call out when generative AI is being used. 347 00:18:54,040 --> 00:18:56,919 Speaker 3: I also think that a lot of technology companies are 348 00:18:56,920 --> 00:18:59,480 Speaker 3: about to make a lot of money off of basically 349 00:18:59,560 --> 00:19:03,000 Speaker 3: tools that allow you to identify what's real. Those are 350 00:19:03,080 --> 00:19:07,119 Speaker 3: going to be commonly used, at least among political campaigns, 351 00:19:07,119 --> 00:19:08,560 Speaker 3: if not the general population. 352 00:19:09,640 --> 00:19:12,720 Speaker 1: When we come back, what can we do to avoid 353 00:19:12,760 --> 00:19:25,920 Speaker 1: getting duped? So what are we supposed to do about this? 354 00:19:26,200 --> 00:19:31,080 Speaker 1: Just as citizens watching a campaign, trying to make good decisions, 355 00:19:31,240 --> 00:19:35,879 Speaker 1: trying to figure out what's real and what's not. I mean, Laura, 356 00:19:36,000 --> 00:19:39,120 Speaker 1: you kind of jokingly at the beginning said, oh, look 357 00:19:39,119 --> 00:19:41,520 Speaker 1: at the hands, let's eve it as six fingers. But 358 00:19:41,960 --> 00:19:44,920 Speaker 1: this is a pretty serious thing. How are we going 359 00:19:44,960 --> 00:19:47,399 Speaker 1: to be able to discern what's real and what's not. 360 00:19:48,600 --> 00:19:50,560 Speaker 4: This is probably when tech companies are going to have 361 00:19:50,640 --> 00:19:53,520 Speaker 4: to start stepping in. We've seen Twitter and Facebook come 362 00:19:53,560 --> 00:19:57,880 Speaker 4: in with labels on misinformation regarding vaccines or other things. 363 00:19:57,960 --> 00:20:01,000 Speaker 4: Regarding the twenty twenty election, we're probably going to see 364 00:20:01,040 --> 00:20:02,560 Speaker 4: those start to come in. I don't know that the 365 00:20:02,560 --> 00:20:05,720 Speaker 4: tech companies, they don't have fully fledged policies yet on 366 00:20:05,760 --> 00:20:07,639 Speaker 4: how to do that, and part of it is that 367 00:20:07,680 --> 00:20:10,840 Speaker 4: it is really difficult to check. We see companies like 368 00:20:10,880 --> 00:20:13,240 Speaker 4: Google saying, Okay, we're going to put these markers in 369 00:20:13,320 --> 00:20:16,119 Speaker 4: these images. That's probably the next step that we're going 370 00:20:16,160 --> 00:20:18,399 Speaker 4: to see of each company, because they want to be 371 00:20:18,440 --> 00:20:20,879 Speaker 4: seen as responsible and because they don't want an image 372 00:20:20,880 --> 00:20:23,160 Speaker 4: created on their platform to be the thing that blows 373 00:20:23,240 --> 00:20:26,080 Speaker 4: up an election, for example. You're going to see pressure 374 00:20:26,280 --> 00:20:28,720 Speaker 4: in the industry to do more, but it's right now, 375 00:20:28,800 --> 00:20:31,400 Speaker 4: it's really incumbent upon the viewer. So it is kind 376 00:20:31,400 --> 00:20:32,920 Speaker 4: of looking at the image, look to see if there's 377 00:20:32,920 --> 00:20:36,000 Speaker 4: a little tag in the corner that mentions it's AI generated, 378 00:20:36,119 --> 00:20:37,960 Speaker 4: or a screen at the very end of an ad 379 00:20:38,000 --> 00:20:39,760 Speaker 4: that says this was created by AI. 380 00:20:40,200 --> 00:20:43,120 Speaker 1: You know, in previous campaigns, we've seen Facebook, we've seen 381 00:20:43,160 --> 00:20:46,560 Speaker 1: Twitter make big public announcements, They've hired all of these 382 00:20:46,560 --> 00:20:48,480 Speaker 1: people who are going to be monitoring, they're going to 383 00:20:48,480 --> 00:20:50,520 Speaker 1: try to crack down on fakery, and yet they just 384 00:20:50,720 --> 00:20:53,280 Speaker 1: could not possibly do it in the case of Twitter, 385 00:20:53,400 --> 00:20:56,840 Speaker 1: we're seeing all kinds of fakery all over the platform, 386 00:20:56,960 --> 00:21:00,840 Speaker 1: especially since Elon Musk took over the company and kind 387 00:21:00,840 --> 00:21:03,920 Speaker 1: of opened it up in a way that previously people 388 00:21:03,960 --> 00:21:05,119 Speaker 1: couldn't post stuff on it. 389 00:21:05,960 --> 00:21:09,520 Speaker 3: Yes, but we're also seeing tools like Twitter's community notes, 390 00:21:09,560 --> 00:21:13,840 Speaker 3: which allows everyday users to weigh in on whether something 391 00:21:13,960 --> 00:21:18,240 Speaker 3: is true or false, that was already under construction before 392 00:21:18,280 --> 00:21:21,359 Speaker 3: Elon Musk came in. It's actually proven to be a 393 00:21:21,400 --> 00:21:27,119 Speaker 3: really effective obstacle for the spread of generative AI misinformation. 394 00:21:27,320 --> 00:21:29,440 Speaker 3: So if we think about the ad Byron de Sampas's 395 00:21:29,560 --> 00:21:32,760 Speaker 3: campaign within hours that had a Twitter note on it 396 00:21:33,000 --> 00:21:36,200 Speaker 3: saying tech experts have looked at this and these images 397 00:21:36,240 --> 00:21:39,399 Speaker 3: are not real. So if you think about what you 398 00:21:39,480 --> 00:21:42,800 Speaker 3: can do as an individual, it's a mitzvah to just 399 00:21:43,040 --> 00:21:48,400 Speaker 3: get out the word that something is fake, that maybe 400 00:21:48,720 --> 00:21:54,720 Speaker 3: tech experts are weighing in and just spreading that information together. 401 00:21:55,200 --> 00:21:57,280 Speaker 3: People create media literacy that way. 402 00:21:58,000 --> 00:22:02,240 Speaker 4: And the thing too is ethicists are less concerned about 403 00:22:02,240 --> 00:22:04,639 Speaker 4: people like Biden and Donald Trump that have swarms of 404 00:22:04,640 --> 00:22:07,320 Speaker 4: press following everywhere they go and everything they do. But 405 00:22:07,440 --> 00:22:10,800 Speaker 4: on the local level, where local news isn't as strong, 406 00:22:10,840 --> 00:22:13,760 Speaker 4: where there are people and candidates and politicians who aren't 407 00:22:13,760 --> 00:22:17,440 Speaker 4: necessarily followed as closely. It's way easier to spread misinformation 408 00:22:17,520 --> 00:22:20,080 Speaker 4: in these areas where there is more of a news vacuum. 409 00:22:20,440 --> 00:22:22,920 Speaker 1: Emily Laura, thanks so much for coming on the show. 410 00:22:23,280 --> 00:22:25,080 Speaker 3: Thanks so much for having us. 411 00:22:25,119 --> 00:22:28,040 Speaker 1: Thank you, thanks for listening to us here at The 412 00:22:28,040 --> 00:22:31,360 Speaker 1: Big Take. It's a daily podcast from Bloomberg and iHeartRadio. 413 00:22:31,680 --> 00:22:36,120 Speaker 1: For more shows from iHeartRadio, visit the iHeartRadio app, Apple Podcasts, 414 00:22:36,200 --> 00:22:38,920 Speaker 1: or wherever you listen, and we'd love to hear from you. 415 00:22:39,200 --> 00:22:42,400 Speaker 1: Email us questions or comments to Big Take at Bloomberg 416 00:22:42,440 --> 00:22:45,760 Speaker 1: dot net. The supervising producer of The Big Take is 417 00:22:45,880 --> 00:22:50,560 Speaker 1: Vicky Virgalina. Our senior producer is Catherine Fink. Federica Romanello 418 00:22:50,720 --> 00:22:55,440 Speaker 1: is our producer. Our associate producer is Zeneb Sidiki. Rafael 419 00:22:55,600 --> 00:22:59,000 Speaker 1: m Seely is our engineer. Our original music was composed 420 00:22:59,000 --> 00:23:02,600 Speaker 1: by Leo Sidrin. I'm Westkasova. We'll be back tomorrow with 421 00:23:02,720 --> 00:23:03,680 Speaker 1: another Big Take.