Big Technology Podcast
00:49:37 · Ranjan Roy
[00:49:37] S1: Well, yeah. So election night last Tuesday, this week, I mean, could guess Tuesday. It's been, again, another long week. So my biennial foray into actually watching CNN and ABC News and kind of network news, I don't do at any other time. I was kind of shocked because even they are all partnering with the of the world and like showing on the screen and like bringing prediction markets into everything. The prediction markets almost in every race, I think it was all the toss ups effectively called them well before the networks did themselves. And by calling them the, you know, like the prediction, the price went up to like 97¢, 99¢ in a lot of these races. So the prediction markets were ahead in terms of basically saying who won each race before the networks had officially called them. Now, on one side, it's very interesting because it's like, can you bring together the masses and through kind of that price discovery actually be faster about kind of parsing information that is out there in some way? Or then there's the other take of just, networks actually wanna get it right whereas prediction markets don't care either way. So, like, but to me, it was both fascinating having always been really interested in the space, but also it was kind of depressing and terrifying again because I still view them as generally gambling platforms and not some other type of thing. Where do you where do you fall in the... Are there prediction markets the future of political news?
00:51:21 · Alex Kantrowitz
[00:51:21] S0: Well, I think there's a debate going on this week that sort of will will... Whichever side you land on will sort of point to the answer there. So Tarek Mansour, the CEO of Kalshi, she said prediction market favorites won 479 of the first 487 races. That's 98%. And Nate Silver, famed pollster, former guest on the show, said give me a break. The polls and models provided the direction in contrast to vibes and dumb insiders. And, yes, it's good that traders were smart enough to trust them, but the better election models were more confident about the outcome than the markets and got there more quickly. So, basically, he's basically saying, yeah, you were able to, you know, hit your accuracy, but you're piggybacking off of the hard work of pollsters. Chris Hayes, I'm a 100% team Nate in this beef. It's obvious to anyone paying attention that the betting just moved over time towards the models. That's the info they were working off of. They didn't discover anything.
00:52:17 · Ranjan Roy
[00:52:17] S1: Well, actually, I mean, on that, I don't know if you saw this. Annie Andrews in South Carolina who had the shocking win to actually be a senator now from South Carolina over Darlene Graham. It's that kind of reflexivity concept of like the numbers driving the numbers that come after that. Again, in this case they're saying, it's the polling numbers that of course then guided the betters on to then make that prediction. I don't know if you... She... Her internal polling had actually shown her three points ahead a month ago and they hit it because they knew that if that... Because that would be kind of this like massive story around you know South Carolina, Lindsey Graham's sister in trouble. So to avoid additional resources and money coming in, they actually hid those internal numbers. Rather than letting them further kind of drive the narrative over what has come. So yeah, I do agree that the polling is critical for those kind of markets to actually find the right outcome. I don't know, it's really interesting to me in that academically, again, I think it's... Polling has always been kind of weird to me, especially with advances in technology today, the idea especially when they were still kind of like phoning people to ask them questions was crazy. By the same token, I just worry about people gambling their lives away on these things that are not supposed to be gambling apps.
00:53:58 · Alex Kantrowitz, Ranjan Roy
[00:53:58] S0: Yeah. I've said on the show, I I don't think that the gamblification of everything is is a good thing. But it is... Look, if you're watching it, it's a good... It's a useful data point. So you can see it. You can see it in real time. You can't see polls in real time. So they got Nate Silver on that front. Alright, Ranjan. It was great speaking with you. We did it. We made it work. I'll make sure that I'll have a cool furniture from now on to... I didn't realize it made [00:54:20] S1: me laugh. I can see you gambling on that. That's a good gambling chair, colonization chair, cigar chair, all of the above. That that is the most multifunctional chair for any vice you could think of. [00:54:33] S0: Yeah. Including speaking of you. [00:54:37] S1: On that note. On that note. [00:54:40] S0: On that note. I I do wanna say on air, thank you for for coming out to the marathon. And I know I was too fast, but I appreciate you coming out and supporting. [00:54:48] S1: You made it. You made it, man. Congrats. [00:54:52] S0: Finished. Knees are knees are barely working, but, yeah, I appreciate you being that [00:54:56] S1: great. Also a good marathon recovery chair. It is just good for everything. Mhmm. But [00:55:03] S0: I... [00:55:03] S1: I'm just bring... I'm bringing it back. At this point, I have to buy it and ship it. So it's not part of the show. It's it's this... It's three of us, you and this chair.
00:55:03 · Ranjan Roy, Alex Kantrowitz
[00:55:03] S1: I'm just bring... I'm bringing it back. At this point, I have to buy it and ship it. So it's not part of the show. It's it's this... It's three of us, you and this chair. [00:55:13] S0: Alright, Ranjan. Have a great weekend. Thanks for coming Alright. On Thanks everybody for listening and watching. We'll see you next time on Big Technology Podcast.