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Podcast Summary: Pioneers of AI - Episode: Can AI Talk Us Out of Conspiracy Theories?
Episode Overview In this episode of *Pioneers of AI*, host Rana el Kaliouby engages with David Rand, a professor at Cornell University, who explores how AI can be utilized to combat conspiracy theories. With a focus on both the psychological allure of conspiracy theories and the potential of AI chatbots to debunk these beliefs, Rand shares insights from his recent study which indicates that AI can effectively reduce belief in conspiracy theories through fact-based conversations.
Key Themes and Discussions
The Nature of Conspiracy Theories
- Definition: Conspiracy theories are explanations for events or situations that involve covert plots by powerful conspirators.
- Common Misconceptions: Not all conspiracies are false; historical examples like Watergate illustrate real conspiracies. Conversely, many false claims lack the conspiratorial aspect.
- Psychological Factors: Rand discusses the motivations behind why people believe in conspiracy theories, emphasizing that many individuals may simply not have encountered adequate counter-evidence.
AI as a Tool for Debunking
- Study Objective: The research aimed to determine if AI chatbots could effectively engage with conspiracy theorists and provide them with factual information that might alter their beliefs.
- Methodology:
- Participants believing in conspiracy theories were engaged in dialogues with an AI chatbot designed to counter their beliefs.
- The conversations personalized responses based on the individual's assertions and beliefs.
Findings and Effectiveness
- Results: The study found an average reduction of approximately 20% in belief among participants after engaging with the AI chatbot.
- Long-Term Effects: Follow-up assessments indicated that the belief reduction was stable over time, with no significant decay in the change observed even two months later.
- User Experience: Participants reported that the AI provided clear, logical explanations that often made more sense than their original beliefs.
Implications and Future Applications
- Scaling the Approach: Rand has launched debunkbot.com, enabling users to engage in similar conversations with the AI, which has attracted significant organic traffic and demonstrated consistent results in belief reduction.
- Broader Applications: Potential uses for this AI methodology extend to debunking misinformation in healthcare (e.g., vaccine myths) and improving public understanding of complex social issues like the racial wealth gap.
Psychological Insights
- Overconfidence and Misconceptions: Rand highlights a tendency among conspiracy believers to overestimate how many others share their views, contributing to their steadfast beliefs.
- Addressing Misinformation: The study suggests that many conspiracy believers simply have not been exposed to accurate information, rather than actively ignoring it.
Conclusion The conversation emphasizes the potential of AI to serve as an impartial and effective tool for combating misinformation and conspiracy theories. By fostering fact-based dialogues and personalized responses, AI can play a critical role in helping individuals reconsider and potentially revise their beliefs.
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Call to Action Listeners are encouraged to explore debunkbot.com and share their experiences, particularly if they or someone they know holds conspiracy beliefs.
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Next Episode Preview In the upcoming episode, Rana el Kaliouby will speak with Laila Ibrahim, COO of Google DeepMind, focusing on leveraging AI to accelerate scientific discovery and democratize access to education.
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Podcast Credits
- Host: Rana el Kaliouby
- Guest: David Rand
- Production: Wait What
- Executive Producer: Eve Trow
- Music: Brian Holliday
Listeners are invited to join the conversation on various social media platforms to stay connected with the ongoing discussions surrounding AI's impact on society.
Written by AI. May contain mistakes. Listen to the episode to check what was said.
Transcript
Automatic transcript. May contain errors.0:00Starting a business comes with its share of ups and downs, which is why staying true to your vision is essential. a non-negotiable for Romeo and Milka Bregali, Capital One business customers and co-owners of Ra's plant-based restaurant in New York. Romeo and Milka took a leap of faith when starting their own restaurant, gutting an empty space and building it from the ground up. Every pipe, every wall, every detail. But building from scratch came with a heavy financial burden, which is when they turned to their Capital One business card. With the flexibility of the card's no preset spending limit, they were able to spend more and earn more rewards while bringing their vision to life.
0:36Today, Raz's success is proof that with passion and the right support, it's possible to make your dreams a reality. Learn more at CapitalOne.com slash business cards.
0:51It's true that AI can accelerate misinformation and conspiracy theories. Because it can generate fake images and videos with the click of a button. But AI can also be part of the solution. And that's the focus of David Rand, a brain and cognitive science professor at MIT and now Cornell. Given that the technology exists, bad actors are going to be using it to do bad things. And what kind of positive things can we do with it? Like what are ways to have some net positive impacts on society? David and his team harnessed the power of AI chatbots to help debunk conspiracy theories. On this episode of Pioneers of AI, we're digging into how that actually works.
1:35We will look at how AI can walk someone through their belief in a conspiracy theory and possibly deprogram their thinking with personalized, fact-based conversation. I'm Rana El-Khalyubi, and this is Pioneers of AI, a podcast taking you behind the scenes of the AI revolution.
2:03Hi, David. Welcome to Pioneers of AI. Thanks for having me. It's great to be here. So when we were doing research for this podcast, I realized that you were in several rock bands growing up. Tell us more about that.
2:24yeah yeah that was from i think by like maybe junior year in high school through the first uh year of grad school the thing that i cared the most about uh in life was playing in punk rock bands um and so i played in normal punk rock bands through college and then um all my uh bandmates graduated and left. And so I started doing electronic music where I programmed things on the laptop, plug it into the speakers and run around and sing and do jump kicks. And people thought it was kind of weird. Okay. One of my old bandmates said this, and I would always say it in my sense, he said, for the first song, he thought it was kind of funny because it was a guy running around singing with a laptop.
3:01And then the second song, he started to feel really awkward and embarrassed for me because there's just a guy running around singing with a laptop. And then by the third song, he started getting into it. Okay, great. That's awesome. So let's talk about conspiracy theories. And I want to start first by defining what a conspiracy theory is. And it's basically a theory that explains an event or a set of circumstances as a result of a secret plot, usually by some powerful conspirators. Would you agree with that definition? And also, what are some of the most common conspiracy theories out there today?
3:31Yeah, so that's a great definition of a conspiracy. And I think one important point is not all conspiracies are false. Sometimes powerful actors do actually conspire. Like, you know, Watergate was a conspiracy. And also not all false claims are conspiracies. There are lots of false claims that just like directly make inaccurate statements, but don't have this kind of conspiratorial aspect to it. So it's a particular slice of things. And I think a lot of the reason that a lot of people are interested in conspiracy theories is although they're not definitionally false, a lot of the very popular conspiracy theories are pretty obviously false and yet widely believed.
4:13And so it makes them kind of psychologically interesting of like, how is it that people continue to believe things that are clearly not true in the face of substantial amounts of counter evidence? I mean, what is the psychology of conspiracy theory? Like, why do people believe in it and, you know, believe in some of these theories and believe so strongly? Right. Yeah. So this is what the research that we're going to talk about today kind of grew out of, which is in the face of evidence that various previous estimates have said something like half of Americans believe at least one conspiracy theory that is kind of widely refuted.
4:52And so the standard psychological explanation is people want to believe. There are all these different motivations that drive you to believe conspiracy theories. And so therefore, you sort of ignore or write off counter evidence because you want to believe. And so these kind of psychological motivations basically blind you to corrective evidence. But this line of research that we've been doing was largely set up to try and challenge that take. okay, so it's possible that people believe conspiracy theories because they just ignore evidence and, you know, these motivations insulate you against inconvenient evidence.
5:28But we're like, another possibility is just that people often haven't heard the right evidence. And, you know, what we've seen from some of these dialogues that we've collected is people will say things like, oh, I 100 % believe that 9-11 was an inside job. I've watched a bunch of videos on YouTube and they were very compelling. And so it's essentially like they were only exposed to the conspiratorial explanation and they never got the debunking. It's because people may have been not necessarily motivated to go out and search for disconfirmatory evidence, but that doesn't mean that they would ignore it when they get it.
6:08And actually, I think another important part of this is my close collaborator, Gordon Pennycook, and I had a paper recently on conspiracy belief, where we found that conspiracy believers massively overestimate how many other people believe in the conspiracy they believe in. Interesting. They think everybody, like, it's like obvious and everybody believes in the same theory. Right. And it seems crazy because of like, how could that be? So part of it is what we show in that paper is that a strong predictor of believing in conspiracy theories is being overconfident in your own abilities. But I think it's also part of that overconfidence is not appreciating the fact that other people disagree with you.
6:46You would think that, okay, so how would you know that other people don't believe the conspiracy theory? It would be because when you say, hey, I believe 9-11 was an inside job, they'd be like, no, come on, that's crazy. But if you think about it, nobody likes or almost nobody likes doing that because people don't like confrontation. So when you're at Thanksgiving and you're saying all your crazy conspiracy theories, you might have some relatives that would be willing to get into it with you, but most people are going to be like, yeah, all right, whatever, Bob and then change the subject. And so if you're an overconfident person, you're like, oh, great, they agreed with me.
7:17Like, you know. During COVID-19, my mom saw this Italian TikToker, and I guess he believed that Bill Gates was implanting 5G chips in the COVID vaccine, and she kind of believed it. And to your point about not being confrontational, I'm like, I rolled my eyes and just like left it at that. Right, right, right, right, right, exactly. So a result of that is I think a lot of people, like a good chunk of people that strongly believe conspiracy theories, haven't actually heard the non-conspiratorial explanation for whatever they're interested in explained in a clear and cogent way. And so our idea was maybe if we just could, like facts and evidence do matter to a lot of conspiracy theorists, you just have to give the right facts in the right way.
8:09because, you know, another important element of conspiracy theories is often they're very complicated. And since they're not constrained by the truth, you can have many different versions of them. Part of what makes it really hard for humans to debunk other people's beliefs is this great variety in what people believe. And then we were like, okay, well, what has access to a vast amount of information and has the ability to personalize their response to whatever the person says, oh, well, these new large language models like, you know, GPT. And so that was what we did in this project. We wanted to say, could GPT actually effectively debunk conspiracies, which would mean that actually information does work if it's the right information?
8:50Or are the conspiracy theorists just going to ignore whatever GPT has to say, which is what you would expect based on this sort of more motivational, I want to believe, kind of psychological framework. What makes a conspiracy theory successful? Like, what are the ingredients of a conspiracy theory? And also, are there like stronger theories than others? And how do you assess that? In some sense, the question of what makes a conspiracy theory successful is a million-dollar question if you're a conspiracy theory generator. And I don't think we really know. In the same way, it's like saying, what make content go viral?
9:26It's like, well, if I knew, all my stuff would be going viral. Right, right, right. Right. It's an evolutionary process where you've got the ecosystem is just like, you know, all these different possible conspiracy theories. Every time somebody makes up a new one, it's like introducing a new variant. And so you can wind up with these very elaborate, very bizarre, but very popular conspiracy theories because they arise out of this sort of cultural evolutionary process.
9:55We're going to take a short break. When we return, we'll dive into David's study, which used AI chatbots to debunk conspiracy theories and the surprising results of that research. Stay with us.
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11:12So you came in basically with this hypothesis that using AI could possibly help people kind of move away from their belief around a theory. So who did you partner with? How did you conduct the study? Where did you find these people? What do you tell them coming in? Yeah, so this is a collaboration with my long term, really close collaborator, Gordon Pennycook, who's in the psych department at Cornell. and Tom Costello, who was a professor at American University now, and he's moving to Carnegie Mellon this summer. And so we did online survey experiments. We recruit participants from a sort of nationally representative-ish sample.
11:54And then we start by asking them what conspiracy they believe. And then we filter down to people that actually believe a conspiracy. They could just type out anything that they want. Now, what's the evidence that you see for this? Like, what makes you believe it. And they type that out. And then we use GBT to summarize back everything they wrote into one sentence. So we have like a running example I'll use here is a 9-11 conspiracist in our data. And so the person was like, you know, I think that the US government was behind the 9-11 attacks and evidence for it is that World Trade Center of Building 7 collapsed, even though it wasn't hit by a plane.
12:29And Bush didn't look at all surprised when he was reading to children and somebody whispered in his ear that 9-11 was happening and he just like kept reading to the kids. And we say, okay, this is what you said. Now zero to a hundred, how much do you believe it? And so now we've got this numerical measure of how much they believe it. And then we say, okay, now in the next part of the experiment, you're going to have a conversation with advanced AI. And, you know, the goal of the study is to see how humans and AI can have, you know, conversations about, you know, complicated topics. And for the people that or in the treatment, we say, we're going to talk about, you're going to talk to the AI about one of the things you just answered questions about.
13:09And in the control, we say, you're going to talk to the AI about whether you like dogs versus cats more, or like, you know, what'd you think about the firefighters or like what your experiences with healthcare have been, whatever, random things that are like not related to conspiracy theories. So we can just control for the effect of having a conversation with an AI in general, but not about the specific thing that we care about. Then we tell the AI in the treatment, you know, you're going to be talking to a conspiracy theory believer. This is the conspiracy they believed. This is how much they believed it, zero to 100.
13:40Your goal is to sort of explain to them why it's not supported by evidence and talk them out of it and try to change their mind to have a less conspiratorial view of the world. And I should say that when we were designing this experiment, Tom was like, I've got all these ideas for different prompts for the AI to try. And I was like, dude, there's no way this is going to work. Like, just pick something. Let's just try it. Probably it's going to be a bust and whatever. So just don't sink too much time into it. Was your hypothesis going in, come on, like AI is not going to move people? Yeah, that is basically, I was totally on board with the I want to believe kind of explanation of conspiracy theories.
14:17And actually, because I've been working on, you know, misinformation and social media for the last decade, I would often get asked by reporters, what can you do to talk people out of conspiracy theories once they've gone down the rabbit hole. And I was always like, basically, it's a lost cause at that point. And so what we really should be focused on is trying to prevent people from starting to believe in conspiracies in the first place. So that was the lens that I brought to this work at the beginning. And then they have this back and forth conversation. And so for our 9-11 conspiracy theorist, the AI says, it always starts out being very polite and sort of affirming in some sense.
14:52And it's like, I understand why big issues like this would raise lots of questions and, you know, I understand this, but like, okay, let's look at the evidence. And so he says, okay, it's true that World Trade Center Building 7 collapsed, even though it wasn't hit by a plane, but an NTSB investigation showed that's because it was hit by debris from one of the towers that was hit by the plane, and then it caught on fire and collapsed. And so it's true that Bush didn't respond when, you know, he was talking to kids and they were told about it. And, you know, supporters and critics have argued about whether this was the right thing to do or not, But he was trying to avoid a panic.
15:28It's not that he already knew about it. And like, remember, conspiracy theories kind of like are trying to offer easy explanations for things and, you know, remember to engage in critical thinking. And then the person is like, OK, but what about these reports that the towers were brought down by demolitions? And also, I believe jet fuel doesn't burn hot enough to melt steel. So these are like classic 9-11 conspiracy things. And so the AI is like, yeah, it's true that people have speculated about this kind of thing before, but there's lots of evidence that the towers were not brought down by demolitions.
16:02The thing that sounded like explosions were successive floors of the tower collapsing one after another, making like booms. And like it takes months to set up a controlled demolition in the basement of a building. There's no way they could have done it without somebody finding out about it. And then the person is like, okay, fine. But then how do we let these men into our country so easily and give them flying lessons? Seems like there really wasn't much security. And then I was like, yes, it's true that that happened. But you have to remember that before 9-11, there were no security procedures in place to be watching for that kind of thing because they didn't know that it was an issue.
16:37And then for instance, like, okay, thanks very much. And so part of what I think what comes out of these kinds of dialogues is that with conspiracy theories in particular, unlike other kinds of false beliefs, there's this conspiratorial explanation, which is some kind of complicated thing. And then in general, the debunking isn't saying, no, the fact that you are saying is wrong. It's like, yes, that did happen. But here is some just like much simpler non-conspirational explanation. And so then they go through this three round back and forth dialogue. How long is each round? I think on average, the dialogues took something like six or seven minutes.
17:18Okay, not hours and hours. Yeah, yeah, yeah, exactly, exactly. And so now that you've talked to the AI, we're going to return to some of the questions we asked you about beforehand, whatever the one sentence summary and be like, how much do you believe it? And so this particular 9-11 conspiracist that started at 100 % goes down to 40%. Wow. And it was that kind of in general what you saw with the other respondents too? Well, it was a particularly good one. But when you look on average, we've ran, so like the first study had like 1 ,000 participants, and then we did a 2 ,000-person replication.
17:52And since then, we've run many of these studies, and it always works. It's something usually around about a 20 % reduction in belief. That's an amazing finding. It's really powerful. Does it stick? That's a key question. So when we ran the original experiment, my jaw hit the floor. I was like, whoa, this is crazy. This is way more than we expected. And then our immediate question is exactly what you said of like, does this stick? And so 10 days later, we recontacted the people and we were just like, hey, here's this statement. How much do you believe it? And at 10 days, the effect was totally stable.
18:33Like it hadn't gotten any smaller. It was just as big as it was immediately. And we were like, wow, this is really cool. We start writing up the paper. And then we have the paper basically ready to submit. And then we're like, all right, one more time. Let's just recontact them again. So we contacted them. That was like two months after the original treatment. The effect, again, was completely stable. It hadn't really decayed at all. Incredible. Before we move on to the other kind of sorts of like false beliefs, etc. Did you experiment with different personalities of the LLM, like one that is more forceful or one that's nicer?
19:09Yeah. So what we've done in follow-up work is a few things in that vein. The first thing that we did, which is like the most commonly asked question every time we presented this stuff, is people would say, well, what if it was a human? Like, is this something special about just people deferring to AI? And our theory going into the whole thing was that this isn't anything AI specific. It's just that the AI is good at coming up with the facts and evidence. We couldn't really rule it out because in the original experiment, we asked people beforehand how much they trust AI. And as you might imagine, it worked better for people that trusted AI more.
19:47But importantly, even the people that said they completely didn't trust AI, it still worked to some extent for them. But we're like, okay, well, maybe there's some really important AI aspect going on here, even though we kind of doubt it. And so we ran an experiment where we had people talk to the AI and we either told them they were talking to an AI or we told them that they were talking to an expert. We found it didn't make any difference at all whether you called it a human or an expert. Even when you called it an expert, it really effectively reduced people's belief. And so it's not something special about thinking it's an AI.
20:20It's the facts and evidence. Talking with these chatbots helped change people's minds about conspiracy theories, and the effects were long-lasting. So what does it look like to apply this use of AI at scale? And are there more applications beyond conspiracy theories? That's after the break.
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22:12So you've essentially taken this research and you're applying it at scale in a number of ways. So you launched debunkbot.com, which I've played around with a little bit with all these COVID conspiracies. But I feel like I have to be a believer first, really, for this to really work. Yeah, yeah, that's right. So tell your mom, tell your mom to give it a real shot. Mom! Oh, God, if she listens to this, she's going to hate me. But yeah, what are other ways you are applying this kind of finding? So I think the first thing just to say on the debunkbot.com, so it's a website that exists out in the world.
22:50Anybody can go and basically just do exactly our study. And we're in the process of doing a sort of a user experience overhaul to make it even friendlier. But we've had more than 100 ,000 visitors and just organic traffic from us not doing anything to promote it, essentially. And when you analyze those conversations, you see that people changed their beliefs as much or more as the people that we paid to do the survey in our experiment. So I'm going to say for the debunk bot, you know, listeners, you can go and try it yourself. If there's any conspiracies you believe in, see what you think. But also I feel like part of the value of it is if you have friends or relatives that are conspiratorial, you can send them that way.
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23:31And also you can practice with it. You know, if you want to get ready for your Thanksgiving debate, you know, like you can say the things that you've heard your friend or relative say, see what Debunkbot says back to it, and then have that ammunition ready when you show up. One powerful thing David has done is apply this work to real-time events. After the Trump assassination attempt in July of 2024, he leveraged AI to combat developing conspiracy theories around the shooting. Here's more on that. So in the original study, the beliefs that we were debunking were these classic conspiracy theories, or at least like very widely discussed conspiracy theories where there is a large body of disconfirmatory evidence and non-conspiratorial explanations.
24:23So that is very powerful, but it requires the non-conspiratorial explanations to exist. And so when things are happening in real time, we don't know. It's not like it has been investigated and here's the real explanation. And so you might have expected that the debunk bot wouldn't really work in those cases because it wouldn't know what to say. And so we wanted to try it out. And so as you mentioned, during the week after the first Trump assassination attempt, there was all different kinds of conspiracies going around, both on the right and on the left. Generally, of the flavor of the people on the right thought the Secret Service let the gunman through and they wanted Trump to get assassinated.
25:04And the people on the left thought the whole thing was fake and it was just a publicity stunt for Trump. And so what we did is we did this exact same setup. And to our surprise, we found that the model worked just about as well as it did for debunking the classic conspiracies. But when you look at what's happening in the conversations, it's doing it in a very different way. Like for the emerging conspiracies, it's not offering alternative explanations and, you know, because they don't exist. And instead, what it's saying is basically, here is what is known, and everything that's not that, we just don't know.
25:44And so you shouldn't be believing things. It's basically encouraging people to engage in some critical thinking and not just, like, jump to conclusions and not just believe whatever they hear, but basically say anything that's not this is just speculation, so, like, don't believe it. But after the second Trump assassination attempt, we recontacted a bunch of the people from the first study and we're like, hey, what do you think about what's happening with this assassination attempt? And we found a spillover where the people that were in the treatment after the first conspiracy theory were less conspiratorial about the second assassination.
26:20So you did a study around the racial wealth gap, which I'm very curious about. It's an area that I'm very interested in. Tell us more about that. After we did the conspiracy theory first set of experiments, we were like, wow, we picked conspiracy theories because we thought they were going to be really resistant to evidence. And yet we found these like really big effects. Let's try and push it even further, trying to find other boundary cases where we really don't think this is going to work. And so the next experiment that we ran was on trying to explain sort of like the structural factors underpinning the racial wealth gap, try to explain that to Republicans.
27:01And we're like, nobody, I think, thinks that the reason that people are saying or rejecting structural explanations for the racial wealth gap is about facts and evidence. You know, it's like a super salient culture war kind of topic. it's very identity laden. And so I ran this with the expectation that it wouldn't really do much again, because I didn't think that there was like, Oh, you explained it to me. Okay. That makes sense. Like, you know, what, what world is that? So basically we had a similar setup where we gave, we recruited, uh, you know, a large number of Republicans from these online samples.
27:37We gave them some statistics about how, uh, white families in the U S have so much more wealth than Black families. And then we were like, you know, one to seven, how much do you think this is explained by, and we've listed various structural factors. We didn't say the word structural, but things like legacies of slavery versus, you know, another one, other options like, you know, cultural or genetic deficiencies and other kind of like racist stuff. And then we said, okay, free text, write out exactly how you explain it. And then they have the conversation with the model. And what we found was sort of as expected, a large fraction of the respondents initially really rejected the structural explanations.
28:17But among those people that rejected the structural explanations, we got like a really big, you know, 15 or 20 percentage point increase in people saying like the structural explanations make sense. And when you look at the dialogue, a lot of people saying, oh yeah, like this is the first time someone's explained something to me that actually makes sense. And like with the conspiracy theories, you know, I think something that's important to remember is, you know, 75 % of the conspiracy theorists didn't stop believing after the conversation. So it's not like it works for everyone. But the point is, there's like a really substantial chunk of people that just never heard the explanations before.
28:52And that's true even for, you know, the racial wealth gap thing. I think in general, like the average person doesn't want to have inaccurate beliefs. But I feel like you very rarely get exposed to the evidence that contradicts what you already believe because you're listening to people, you know, you're watching news that's from your side and you're listening to political elites that are from your side and you're hanging out with friends that are either from your side or polite and don't want to get in arguments about things. And so you just sort of like don't get exposed to the disconfirmatory evidence.
29:26Are there other areas where you're very excited to apply this word? I mean, ultimately, your work is about changing people's minds, right? Are there other use cases or applications of this? Yeah. So, I mean, I think there's a lot of applications in healthcare in terms of, like, first countering misinformation, like, around vaccines and things like that, but just way more generally helping people make informed decisions. And I feel like another one is local politics, where I feel like local elections, in many cases, actually impact your life much more than national elections. And people are amazingly uninformed about, I think, even sort of what we call high-information voters who care about politics in general typically know very little about school board candidates and city council candidates and mayoral candidates and stuff like that.
30:17But you can imagine building one of these models that essentially just helps people navigate information, like ingests all the statements from all the candidates and public videos. And then you can say, well, this is what I care about. And it says, okay, well, this is sort of where different candidates stand on that. All right. So to wrap, I always ask all my guests the same question. In this world where AI is very persuasive and it's smart and it knows all the evidence and facts, what does it mean to be human in the age of AI? Okay. So my snarky answer is it means check the sources. Okay. I like it.
30:53I love it. And what it means to be human is to see, is the source that this AI citing something I actually think is credible or not? I love it. That's an awesome answer. I think this is a great way to end our conversation, David. That was awesome. All right. Well, thanks so much. This was really fun.
31:12Often conspiracy theories are deep-seated in people's minds, and it seems like nothing could budge them at all on their thinking. But David's research suggests that AI can help with this, that facts do matter. And by walking people through orchestrated dialogues powered by logic and facts, their minds can change. And maybe AI is a great tool for this precisely because it doesn't roll its eyes or get frustrated by someone's beliefs. It just delivers a counter-argument, patiently and methodically. and that is huge. So I have an ask of you. If you know someone who's bought into a conspiracy theory or you yourself believe in something that you're not sure is true, go check out debunkbot.com and report back with your experience.
32:05We'd love to feature your response on the show. Leave us a voicemail at 601-633-2424. That's 601-633-2424 We can't wait to hear more Next week on Pioneers of AI We speak with Laila Ibrahim COO of Google DeepMind We'll talk about leveraging AI to accelerate scientific discovery and democratize access to education Subscribe to the pod wherever you're listening so you don't miss it
32:46Pioneers of AI is a Wait What original. Our executive producer is Eve Trow. Our producer is Rachel Ishikawa. And our associate producer is Jordan Smart. Our senior talent executive is Stephanie Stern. Mixing and mastering by Brian Pugh. Original music by Brian Holliday. And our head of podcasts is Litao Moulad. You can join the conversation on LinkedIn, Instagram, TikTok, YouTube, and X. Just search for at Pioneers of AI. Thanks so much for listening.
From the publisher
From deepfakes to fabricated news, AI has been shown to generate convincing deceptive images and videos, increasing the spread of misinformation. David Rand, a professor of Information Science and marketing at Cornell University, is using the same technology for a different purpose: debunking those very same conspiracy theories. In a recent and groundbreaking study, Rand and his team asked participants who believed in conspiracies to talk with an AI chatbot specifically designed to reduce those beliefs. The results were surprising. Rand joins Pioneers of AI to discuss what makes conspiracy theories so alluring, how AI can be a powerful tool for debunking them through fact-based conversations, and what this could mean for combating other forms of misinformation.
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