In Texas, AI-generated political ads are blurring the line between real and fake - Poynter

The small effects of political advertising are small regardless of context, message, sender, or receiver: Evidence from 59 real-time randomized experiments

Campaign persuasion operates with notable consistency across political parties, message tone, and information environment., Evidence across social science indicates that average effects of persuasive messages are small. One commonly offered explanation for these small effects is heterogeneity: Persuasion may only work well in specific circumstances. To evaluate heterogeneity, we repeated an experiment weekly in real time using 2016 U.S. presidential election campaign advertisements. We tested 49 political advertisements in 59 unique experiments on 34,000 people. We investigate heterogeneous effects by sender (candidates or groups), receiver (subject partisanship), content (attack or promotional), and context (battleground versus non-battleground, primary versus general election, and early versus late). We find small average effects on candidate favorability and vote. These small effects, however, do not mask substantial heterogeneity even where theory from political science suggests that we should find it. During the primary and general election, in battleground states, for Democrats, Republicans, and Independents, effects are similarly small. Heterogeneity with large offsetting effects is not the source of small average effects.

Deepfakes, Elections, and Shrinking the Liar’s Dividend

Heightened public awareness of the power of generative AI could give politicians an incentive to lie about the authenticity of real content.

AI Fakes Spread Disinformation. Is the Distrust They Create Even Worse?

Manipulated images undermine our shared reality—and the democracy built upon it.

Stop and Consider:Our campaign

During a federal election there is a large amount of information being distributed, much of it online, which is seeking to influence your vote. Some of this may be disinformation, or false information.

Dialogues on Democracy: Belief-Tailored AI Conversations Reduce Inaccurate Election Denial Beliefs

Elections, while central to democratic functioning, have become increasingly threatened by beliefs about election fraud. Artificial intelligence (AI) provides a novel opportunity to address such false beliefs through dynamic conversation and debunking. Through two experiments (N = 1,802 Republicans from Lucid who endorsed election fraud claims), we examined the use of AI to fact-check 2020 election conspiracies prior to the 2024 US Presidential election. We tested the effects of two treatments (an information-tailored and values-tailored AI dialogue) in which AI fact-checked their claims and tailored arguments to the specific election conspiracy that the participant themselves articulated. Both treatment conditions, when compared to a control dialogue and a simple statement that the conspiracy was incorrect, reduced confidence in their election conspiracy claims. There was no significant difference between information-tailored and values-tailored feedback. Promisingly, participants with the strongest baseline denialism experienced the largest decreases in denialism beliefs. These studies highlight the potential of AI-driven interventions to address election misinformation.

The Minimal Persuasive Effects of Campaign Contact in General Elections: Evidence from 49 Field Experiments

Significant theories of democratic accountability hinge on how political campaigns affect Americans’ candidate choices. We argue that the best estimate of the effects of campaign contact and advertising on Americans’ candidates choices in general elections is zero. First, a systematic meta-analysis of 40 field experiments estimates an average effect of zero in general elections. Second, we present nine original field experiments that increase the statistical evidence in the literature about the persuasive effects of personal contact tenfold. These experiments’ average effect is also zero. In both existing and our original experiments, persuasive effects only appear to emerge in two rare circumstances. First, when candidates take unusually unpopular positions and campaigns invest unusually heavily in identifying persuadable voters. Second, when campaigns contact voters long before election day and measure effects immediately—although this early persuasion decays. These findings contribute to ongoing debates about how political elites influence citizens’ judgments.

Alarming AI ads are flooding social media in the lead-up to Victoria’s election. But who is behind them?

A machete-wielding robber, a ‘tsunami of debt’ … campaigns echoing opposition talking points outspend major parties

Google research shows the fast rise of AI-generated misinformation | CBC News

From fake images of war to celebrity hoaxes, AI technology has spawned new forms of reality-warping misinformation online. New analysis co-authored by Google researchers shows just how quickly the problem has grown.

Republican AI Ad Uses Cutting Edge Tech to Tell Age Old Lies

A political ad made by the GOP in response to Biden's reelection announcement imagines a dystopia using AI-generated imagery.

Russian Bots Manipulate View Counts on Fake Videos Ahead of US Midterms

State-backed Matryoshka campaign targeting Democrats inflates view counts of fabricated stories, creating illusion of popularity.

How to tell if an image is AI-generated

Scammers are using AI-generated images to make fake stories more convincing. Here's how to separate real from fake.

Deep Storytelling: Collective Sensemaking and Layers of Meaning in U.S. Elections

Misinformation and disinformation about elections remain pressing concerns for researchers, policymakers, and the public. Critics, however, argue that fears surrounding these issues are exaggerated due to a lack of evidence of impact. This debate highlights the challenges inherent in assessing the impacts of misinformation, as the drivers of false and misleading content often exist in the context of a specific claim. To address this issue, we examined false and misleading information surrounding the 2020 and 2022 U.S. national elections, focusing on the contextual features of online conversations that fueled various rumors. We developed two qualitative codebooks, creating the second after realizing that the first, which labeled individual tweets, failed to capture broader rumoring dynamics. By integrating multi-layered qualitative coding with thematic analysis and quantitative visualizations, we show how influencers, political elites, and audiences collaboratively told deep stories from 2020 through 2022. As these stories were told, audiences interpreted events in 2022 through the lens of the 2020 story, guided by influencers' cues, leading to an evolution in storytelling style between the two election cycles. This ongoing performance was tailored to align with the incentive structures, affordances, and attention economy of social media. We combine deep stories with theories of collective sensemaking and rumoring, creating a framework to better assess the contextual features surrounding false and misleading information.

How Technology Is Shaping Modern Politics

Discover how technology is reshaping politics, from digital campaigns to AI, and the challenges of misinformation and election security.

How to break populist parties’ appeal? An experimental evaluation of communication counter-strategies

Right-wing populist parties have become a major challenge to liberal democracies worldwide. How can mainstream parties effectively counter their appeal? While prior research has focused on the drivers of populist support, much less is known about how to counter right-wing populist rhetoric. We test four communication counter-strategies that target core elements of right-wing populist appeals: (i) undermining populists’ claims to democratic credibility, (ii) promoting inclusive in-group identity to counter exclusionary narratives, (iii) highlighting their performance legitimacy, and (iv) emphasizing the procedural legitimacy of mainstream parties. Drawing on real-world party communications from social media, manifestos, and press releases, we created 170 experimental treatments (posters and social media posts varying in format and complexity) to simulate how voters encounter political messages in everyday life. In a large-scale survey experiment with over 24,000 respondents in Germany, messages undermining right-wing populists’ democratic credibility prove most effective, particularly among citizens with high initial support for such parties.

Recent Utah, Texas incidents fuel rumors and political narratives undermining trust in election integrity

A CIP Election Rumor Rundown

Deep Fakes: A Looming Challenge for Privacy, Democracy, and National Security — California Law Review

Harmful lies are nothing new. But the ability to distort reality has taken an exponential leap forward with “deep fake” technology. This capability makes it possible to create audio and video of real people saying and doing things they never said or did. Machine learning techniques are escalating th