Five AI technologies to combat misinformation: community notes, rhetoric detection, reliability tracking, epistemic evals, and provenance tracing.
The AI Trust Gap: 82% Are Skeptical, Yet Only 8% Always Check Sources
Original Exploding Topics survey data explores public sentiment on AI Overviews and AI-generated content, highlighting trust, skepticism, and shifting content consumption habits.
AI False Claims Monitor
As the domain experts in data reliability in the topic of news and information, NewsGuard provides the leading red-teaming analysis for information reliability. AI models continue to face significant challenges in ensuring their models provide safe, accurate responses to prompts instead of spreading false claims on the internet or refusing to respond to topics in the news.
AI use in American newspapers is widespread, uneven, and rarely disclosed
AI is rapidly transforming journalism, but the extent of its use in published newspaper articles remains unclear. We address this gap by auditing a large-scale dataset of 186K articles from online editions of 1.5K American newspapers published in the summer of 2025. Using Pangram, a state-of-the-art AI detector, we discover that approximately 9% of newly-published articles are either partially or fully AI-generated. This AI use is unevenly distributed, appearing more frequently in smaller, local outlets, in specific topics such as weather and technology, and within certain ownership groups. We also analyze 45K opinion pieces from Washington Post, New York Times, and Wall Street Journal, finding that they are 6.4 times more likely to contain AI-generated content than news articles from the same publications, with many AI-flagged op-eds authored by prominent public figures. Despite this prevalence, we find that AI use is rarely disclosed: a manual audit of 100 AI-flagged articles found only five disclosures of AI use. Overall, our audit highlights the immediate need for greater transparency and updated editorial standards regarding the use of AI in journalism to maintain public trust.
AI use in American newspapers is widespread, uneven, and rarely disclosed
AI is rapidly transforming journalism, but the extent of its use in published newspaper articles remains unclear. We address this gap by auditing a large-scale dataset of 186K articles from online editions of 1.5K American newspapers published in the summer of 2025. Using Pangram, a state-of-the-art AI detector, we discover that approximately 9% of newly-published articles are either partially or fully AI-generated. This AI use is unevenly distributed, appearing more frequently in smaller, local outlets, in specific topics such as weather and technology, and within certain ownership groups. We also analyze 45K opinion pieces from Washington Post, New York Times, and Wall Street Journal, finding that they are 6.4 times more likely to contain AI-generated content than news articles from the same publications, with many AI-flagged op-eds authored by prominent public figures. Despite this prevalence, we find that AI use is rarely disclosed: a manual audit of 100 AI-flagged articles found only five disclosures of AI use. Overall, our audit highlights the immediate need for greater transparency and updated editorial standards regarding the use of AI in journalism to maintain public trust.
Our Approach to Artificial Intelligence
We are experimenting with using AI tools to extend our work as a small nonprofit, so that we can focus our time on reinforcing human connections, conversations, and communities that have eroded.
AI in journalism: Live tracker of scandals and mistakes
AI in journalism: Live tracker of mistakes and mishaps from the Mississippe Free Press to the New York Times.
Tracking AI-enabled Misinformation: 3,749 AI Content Farm sites (and Counting), Plus the Top False Claims Generated by Artificial Intelligence Tools
Coverage by McKenzie Sadeghi, Dimitris Dimitriadis, Virginia Padovese, Giulia Pozzi, Sara Badilini, Chiara Vercellone, Natalie Huet, Zack Fishman, Leonie Pfaller, and Natalie Adams | Last Updated June 23, 2026
Trust: Foundation of Human Knowledge yet online Platforms won't allow | David Karger | TEDxMIT Salon
Can AI Detectors Be Trusted?
Society has always trusted editors, teachers, peer reviewers, and readers to set acceptable standards for writing. In the past, the biggest challenge was detecting plagiarism and cracking down on other forms of cheating. Now, AI detectors are rewriting the script: they assign a score based on the likelihood that the text was created by a human or a large language model (LLM).
Deepfakes, Scams, and the Age of Paranoia
As AI-driven fraud becomes increasingly common, more people feel the need to verify every interaction they have online.
May 2025 — AI Misinformation Monitor of Leading AI Chatbots
Every month, NewsGuard’s team of expert analysts audit the top AI models to see how well they respond to prompts in the news. On average, this month they failed to counter disinformation from Russia’s Pravda Network 24 percent of the time, either spreading false claims or failing to respond. The Pravda network was designed to infect the AI models.
AI agents are checking the scientific literature — and spotting decades-old errors
The technology is proving adept at finding faults in decades-old papers and reference databases.
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.
Privacy Considerations with AI Tools
Artificial intelligence (AI) tools come in all sorts of flavors. There are notetaking and transcription tools, chatbots, device-wide agentic AI features, grammar and writing tools, translation assistants, AI summaries, and research tools, among others. As a term, “AI” may refer to features in apps, apps themselves, third-party plug-ins, or a...