In the October 2024 flash floods in Spain, social media posts falsely claimed authorities were concealing the number of casualties. The narrative centered on a flooded parking structure in Valencia, where hundreds of bodies were falsely claimed to be trapped. This narrative gained traction even after videos showing the premises had been evacuated.

Not all misinformation consequences are equal. Faced by hundreds of thousands of false claims online and offline every day, fact checkers need a robust way to identify the important ones to check. This scalable model—used by fact checkers in trials in Europe, Africa, and the Middle East since 2024—helps forecast the potential imminent and cumulative harms of different false claims and is an early warning system for society that focuses efforts on factually false claims that cause real-world harms.

Fact checkers should maintain high standards of accountability because they hold unique positions in society by verifying content that can influence political practices and society as a whole. To maintain these professional standards, fact-checking network organizations such as the International Fact-Checking Network (IFCN) and the European Fact-Checking Standards Network (EFCSN) have established codes of standards, and fact-checking organizations should comply with them in a substantive way.

Fact-checking has become a key response to disinformation during crises and conflicts, but its role is increasingly contested due to concerns about its effectiveness and its co-optation by different political actors. In polarized, high-choice environments, fact-checking is often embedded within partisan and state-aligned infrastructures, shaping validation and rejection of knowledge claims.

Media have made misinformation conversations part of daily life. We looked at nearly four decades’ worth of news stories about misinformation to see exactly what this coverage looked like. We searched five major U.S. daily newspapers for articles containing the misinformation-related terms—disinformation, misinformation, conspiracy theory, fake news, and propaganda—then extracted words in proximity to these key terms to identify associative patterns.

We conducted an expert survey of almost a hundred academics, fact checkers, and journalists who actively work towards mitigating disinformation and providing policy advice in the European context to examine whether they share views on generative artificial intelligence’s (AI) role in disinformation.