00:17:08 · Nate Silver, Nate Silver, Joe Weisenthal
[00:17:08] S1: Right. [00:17:08] S2: On the other hand, if you have a model that's like a consensus model, thermometer that looks at the correlations and translates poles into probabilities. Like, that's really what Flipper, my model, is doing. And, like, so, like, oh, actually, I kind of like that from a modeling standpoint because it proves the kind of underlying hypothesis that, like, polsters are rational actors and, therefore, although poles are imprecise instruments, there is a lot of incentive not to systematically miss. I got it. [00:17:39] S3: So what you're saying is because you can look at the math and say, look, You can't really justify turning a plus nine into a plus two as someone who aggregates polls and then creates a model that can give you some sort of confidence that like. [00:17:56] S2: Confidence that the errors in the long run, if you have elections every two or four years, will never have data to prove it. But confident that the errors are symmetric in the forecast. [00:18:05] S3: Yeah, I get exactly what you're saying. So, OK, people don't pick up the phone like they used to. [00:18:10] S1: Yeah.
00:18:10 · Nate Silver, Joe Weisenthal, Tracy Alloway
[00:18:10] S1: Yeah. [00:18:10] S3: You know, certainly they don't recognize it. And if someone calls me and asks for my political opinion, no way. So then there's this vision. Well, why don't we just create an AI replica of Tracy Alloway and an AI replica of Joe Weisenthal and an AI replica of a high school educated oil worker in Texas and an AI replicated version of a HR professional who works for General Motors in the Detroit suburbs. And we just pull them. And then we don't know. And they're always going to pick up the phone. What's wrong with this? [00:18:42] S0: This is the digital twin idea. [00:18:43] S3: Why don't we just create a digital twin of all America?
00:18:46 · Nate Silver
[00:18:46] S2: So the problem is like, and by the way, I think these companies are smart. I know some people that work for them, right? But like polling cannot be outsourced to AI agents, right? Because it's one of the few sources of ground truth that we have anymore, number one. And also the models are kind of, so if you ask a poll to create like a synthetic Hispanic respondent, right? 99% of their synthetic responses Hispanic respondents love soccer. It's a bit like if you ask like Claude to pick a number from zero to 10, like always pick seven. It's a bit like, I mean, this gets into the whole existential thing about how like large language models work and like they're kind of, it's kind of the ideal type or something, but like, but no, we need original data, right? Models like Flipper or prediction markets can aggregate that data, but, but, you know, because like voters aren't all that predictable. You know, I don't even like the kind of slicing and dicing that you see. Oh, the Hispanic vote, right? Well, the Hispanic vote is younger Hispanics and older Hispanics, people who are relatively new to the country and people who have been here for a long time, right? Cuban Americans and Puerto Ricans and Mexican Americans and Dominicans and everything else. And like those groups don't always agree with one another. Sure. And people miss it. Like the Hispanic vote is one of the most swingy demographics in the United States. And so like, yeah, it just gets overly reductive and kind of almost like a snake eating its tail a little bit.
00:20:08 · Tracy Alloway, Nate Silver, Nate Silver, Joe Weisenthal
[00:20:08] S0: I feel like turnout in particular would be difficult for a digital twin to model? Like maybe you can come up with political preference based on demographics, but like predicting whether someone is actually going to leave the House and vote seems particularly difficult to me. But tell me if I'm wrong. [00:20:23] S2: Yeah, we did a little simulation in South Carolina, which is one of the more surprising races to be polling closely. And, you know, and one more, frankly, be a bit more surprised Democrats won. [00:20:32] S1: Right. [00:20:32] S2: But like, you know, what if black voters in South Carolina turned out at 2024 rates and white voters turn out at 2022 rates, like that shifts the top lines by like 10 points, right? It's a deliberately extreme example. And in South Carolina, the white vote is very conservative. But, you know, that's an example of like, you know, because you have had some midterms where 2018 in particular, you had some states getting up to presidential type turnout. But if it's differential turnout, that would you need that for a state like South Carolina to flip. [00:21:04] S3: The Democrats have 14 percent in Mississippi. on polymarket. [00:21:07] S2: Yeah, that one's a little weird. [00:21:09] S3: These are funny states. These southern states are pretty funny, right? Because the top line votes are actually offered frequently fairly close. It's just that every white is a Republican and all the non-whites are not Republicans. And so while it looks really close, it's just like, it's just purely demographics.
00:21:09 · Joe Weisenthal, Nate Silver, Tracy Alloway
[00:21:09] S3: These are funny states. These southern states are pretty funny, right? Because the top line votes are actually offered frequently fairly close. It's just that every white is a Republican and all the non-whites are not Republicans. And so while it looks really close, it's just like, it's just purely demographics. [00:21:28] S2: No, so we have a concept in our model that we call elasticity, which is how sensitive is a state to changes in the national race. And that's based on voter-level microdata where we see people clustered at the tails or more in the middle. And, you know, South Carolina, but especially like Louisiana, Mississippi, have very low elasticity. So that's why. So we are lower than polymarket and Democrats in those states. [00:21:50] S0: Actually, since you mentioned demographics, can we talk about gerrymandering for a second? So to what degree do you see that, I guess, backfiring on the Republicans at this point? [00:22:00] S2: So, yeah, a gerrymander where you wind up with fewer seats than you would have under the original maps is a dummymander. Is a term for it? [00:22:06] S0: This is an actual term.
00:22:06 · Tracy Alloway, Nate Silver, Joe Weisenthal, Nate Silver
[00:22:06] S0: This is an actual term. [00:22:07] S2: It's a term. We have terms for everything in politics. Only poker players have more terms in politics. In Florida, Ron DeSantis drew a map for kind of a presidential year baseline. In presidential years, I expect Florida to remain a pretty red state, right? It's not robust for like a D plus nine climate where Florida goes from R plus 13 to R plus four, right? or something, right? It wasn't designed for that. And if Democrats kind of run the table in Florida, then they could actually wind up with more seats than they would have under the old map, right? In Texas, Republicans hope to make a lot of their gains from, I guess, this maybe frankly arrogant presumption that, oh, now Hispanics in South Texas are now our voters instead of being swingy. And so, like, that probably won't be a dummy mander, but could be a case where the places they hope to maintain gains, you'll have Democratic incumbents holding on. [00:22:57] S3: Intuitively, if you're a mapmaker... And your only goal is to maximize the number of seats that your party wins. You have to take some risks, right? Is this the key idea here? [00:23:08] S1: Correct.