Thinking outside the ballot box

Costello, Thomas H.; Zmigrod, Leor; Tasimi, Arber

doi:10.1016/j.tics.2023.03.012

Cited by 7 publications

(5 citation statements)

References 87 publications

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“…Yet this lack of scholarly attention on people at the political center is unwarranted given that many citizens hold moderate views, and these citizens are especially important for candidate selection 11 . The present results corroborate the perils of focusing on the extremes and indicate that reducing the entire ideological spectrum into ‘the left’ and ‘the right’ is too simplistic and misses important nuances 21 .…”

Section: Discussionsupporting

confidence: 83%

“…To conclude, political knowledge is one of the most valuable resources for citizens in a democracy 40 . The present investigation extended the theoretical debate of ideological symmetry and asymmetry among the political left and right by adopting a data-driven approach 21 and showing that the relationship between political orientation and political knowledge is more context-dependent and nuanced than previously assumed. We hope to inspire scholars of different fields to use these results as a starting point for future research examining the factors that impact the relationship between political orientation and political knowledge both within and between nations.…”

Section: Discussionmentioning

confidence: 73%

“…Recently, scholars examining political behavior and attitudes have advocated for more research utilizing a data-driven, bottom-up approach since testing a single model increases imprecision 21 . The present research adopts such a data-driven approach by testing a consecutive series of polynomial regressions modeling the relationship between political orientation and factual political knowledge in 45 nations, thereby allowing complex relationships to emerge.…”

Section: Introductionmentioning

confidence: 99%

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The association between political orientation and political knowledge in 45 nations

De keersmaecker,

Schmid,

Sibley

et al. 2024

Sci Rep

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Political knowledge is crucial for well-functioning democracies, with most scholars assuming that people at the political extremes are more knowledgeable than those at the center. Here, we adopt a data-driven approach to examine the relationship between political orientation and political knowledge by testing a series of polynomial curves in 45 countries (N = 63,544), spread over 6 continents. Contrary to the dominant perspective, we found no evidence that people at the political extremes are the most knowledgeable about politics. Rather, the most common pattern was a fourth-degree polynomial association in which those who are moderately left-wing and right-wing are more knowledgeable than people at the extremes and center of the political spectrum. This pattern was especially, though not exclusively, prevalent in Western countries. We conclude that the relationship between political orientation and political knowledge is more context-dependent and complex than assumed, and caution against (implicit) universal conclusions in social sciences.

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Section: Discussionsupporting

confidence: 83%

Section: Discussionmentioning

confidence: 73%

Section: Introductionmentioning

confidence: 99%

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The association between political orientation and political knowledge in 45 nations

De keersmaecker,

Schmid,

Sibley

et al. 2024

Sci Rep

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“…Finally, our findings raise a wide array of important directions for future research on the psychology of belief systems (69)(70)(71)(72), reasoning (45,73), and misinformation (74,75). First, there are questions related to our specific intervention.…”

Section: Discussionmentioning

confidence: 97%

Durably reducing conspiracy beliefs through dialogues with AI

Costello,

Pennycook,

Rand

2024

Preprint

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Conspiracy theories are a paradigmatic example of beliefs that, once adopted, are extremely difficult to dispel. Influential psychological theories propose that conspiracy beliefs are uniquely resistant to counterevidence because they satisfy important needs and motivations. Here, we raise the possibility that previous attempts to correct conspiracy beliefs have been unsuccessful merely because they failed to deliver counterevidence that was sufficiently compelling and tailored to each believer’s specific conspiracy theory (which vary dramatically from believer to believer). To evaluate this possibility, we leverage recent developments in generative artificial intelligence (AI) to deliver well-argued, person-specific debunks to a total of N = 2,190 conspiracy theory believers. Participants in our experiments provided detailed, open-ended explanations of a conspiracy theory they believed, and then engaged in a 3 round dialogue with a frontier generative AI model (GPT-4 Turbo) which was instructed to reduce each participant’s belief in their conspiracy theory (or discuss a banal topic in a control condition). Across two experiments, we find robust evidence that the debunking conversation with the AI reduced belief in conspiracy theories by roughly 20%. This effect did not decay over 2 months time, was consistently observed across a wide range of different conspiracy theories, and occurred even for participants whose conspiracy beliefs were deeply entrenched and of great importance to their identities. Furthermore, although the dialogues were focused on a single conspiracy theory, the intervention spilled over to reduce beliefs in unrelated conspiracies, indicating a general decrease in conspiratorial worldview, as well as increasing intentions to challenge others who espouse their chosen conspiracy. These findings highlight that even many people who strongly believe in seemingly fact-resistant conspiratorial beliefs can change their minds in the face of sufficient evidence.

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“…Political orientation has proven to be a valuable predictor of many outcomes related to misinformation, such as exposure and engagement with fake news (Guess et al, 2019) and resistance to fact-checking (Rathje et al, 2022). However, other work suggests that the traditional left-right spectrum falls short when it comes to capturing important aspects of political behavior (Costello et al, 2023). Future research should assess where in the network different groups with varying degrees of political extremity are located, and how connected they are to neighboring communities.…”

Section: Future Directionsmentioning

confidence: 99%

Scaling crowdsourcing interventions to combat partisan misinformation

Pretus,

Gil-Buitrago,

Cisma

et al. 2024

Preprint

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Partisan misinformation hijacks people’s right to make decisions based on accurate information, posing a threat to democracy and liberal values. Current interventions to counter misinformation are less effective when it comes to politically polarizing content, especially among extreme partisans who share the most misinformation. A new line of research suggests that crowdsourcing interventions, or using laypeople’s judgments to help people spot misinformation, provide an additional layer of content moderation that can help overcome these limitations. We present a model that explains when crowdsourcing interventions will be successful based on three factors: trust in fact-checking sources, dissonance with previous beliefs, and crowd size. These three factors are often at odds in politically polarized social media environments, leading to less effective fact-checking. Based on this model, we discuss how crowdsourcing interventions could be scaled in a way that is ethical and leverages artificial intelligence to connect people with neighboring communities outside their ideological echo chambers. Finally, we propose venues for future research in the field of crowdsourcing interventions that lie at the intersection between individual-level and system-level solutions to partisan misinformation.

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Thinking outside the ballot box

Cited by 7 publications

References 87 publications

The association between political orientation and political knowledge in 45 nations

The association between political orientation and political knowledge in 45 nations

Durably reducing conspiracy beliefs through dialogues with AI

Scaling crowdsourcing interventions to combat partisan misinformation

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