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The development of artificial intelligence (AI) allows rapid creation of AI-synthesized images. In a pre-registered experiment, we examine how properties of AI-synthesized images influence belief in misinformation and memory for corrections. Realistic and probative (i.e., providing strong evidence) images predicted greater belief in false headlines.

Some of today’s most popular large language model (LLM)-powered chatbots occasionally reference Kremlin-linked disinformation websites, but it might not be for the reasons many fear. While some recent studies have claimed that Russian actors are “grooming” LLMs by flooding the web with disinformation, our small-scale analysis finds little evidence for this.

As language models (LMs) continue to develop, concerns over foreign misinformation through models developed in authoritarian countries have emerged. Do LMs favor their home countries? This study audits four frontier LMs by evaluating their favoritism toward world leaders, then measuring how favoritism propagates into misinformation belief.

In February 2025, Google’s AI Overview fooled itself and its users when it cited an April Fool’s satire about “microscopic bees powering computers” as factual in search results (Kidman, 2025). Google did not intend to mislead, yet the system produced a confident falsehood.

We surveyed 1,000 U.S. adults to understand concerns about the use of artificial intelligence (AI) during the 2024 U.S. presidential election and public perceptions of AI-driven misinformation. Four out of five respondents expressed some level of worry about AI’s role in election misinformation.

Social scientists, journalists, and policymakers are increasingly interested in methods to mitigate or reverse the public’s beliefs in conspiracy theories, particularly those associated with negative social consequences, including violence. We contribute to this field of research using an artificial intelligence (AI) intervention that prompts individuals to reflect on the uncertainties in their conspiracy theory beliefs.

Academic journals, archives, and repositories are seeing an increasing number of questionable research papers clearly produced using generative AI. They are often created with widely available, general-purpose AI applications, most likely ChatGPT, and mimic scientific writing. Google Scholar easily locates and lists these questionable papers alongside reputable, quality-controlled research.

Research on digital misinformation has turned its attention to large language models (LLMs) and their handling of sensitive political topics. Through an AI audit, we analyze how three LLM-powered chatbots (Perplexity, Google Bard, and Bing Chat) generate content in response to the prompts linked to common Russian disinformation narratives about the war in Ukraine.

Was the 2023 Slovakia election the first swung by deepfakes? Did the victory of a pro-Russian candidate, following the release of a deepfake allegedly depicting election fraud, herald a new era of disinformation? Our analysis of the so-called “Slovak case” complicates this narrative, highlighting critical factors that made the electorate particularly susceptible to pro-Russian disinformation.