AI-detection tools are getting better. Basically every recent, high-profile accusation of someone passing off AI-generated writing as their own has started in the same way: with a tool called Pangram. In March, when a horror novel from a major publishing house was pulled just days before its scheduled U.S. release date, it was in part because Pangram, an AI-detection program, had identified the text as AI-generated. Other people have fed text into Pangram to suggest that chatbots have been used to write articles in major newspapers including, multiple short stories awarded a prestigious literary prize, and most recently, significant chunks of Pope Leo XIV's encyclical warning about the dangers of AI. The tool is also used by universities to vet student work and scientific associations to scan research papers.

We Asked the Author to Explain How He Used AI. A book about how AI shapes perceptions of reality came under fire for using AI-generated quotes. Its problems go beyond that. Earlier this month, WIRED published an excerpt from Steve Rosenbaum's buzzy new book,, which looks at how artificial intelligence warps people's sense of reality. Shortly thereafter, The New York Times reported that the book contained over a half-dozen made-up or misattributed quotes.

The Pope's Warnings About AI Were AI-Generated, a Detection Tool Claims Pangram Labs' updated Chrome extension puts warning labels on AI slop as you scroll your social feeds. On Monday, a brand-new Reddit account popped up on the widely read forum r/AmItheAsshole, where users have their personal disputes arbitrated by strangers. This particular user asked if they had crossed a line by "refusing to babysit my stepmother's kids because I have my own job and responsibilities." The post itself was succinct, straightforward, and grammatically clean, explaining a situation in which the person's stepmother and father often expected them to provide childcare on little notice, eventually leading to an argument. "Now there's tension at home, and I'm starting to wonder if I handled it the wrong way," the redditor concluded.

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.

Abstract--Adversarial perturbations in speech pose a serious threat to automatic speech recognition (ASR) and speaker verification by introducing subtle waveform modifications that remain imperceptible to humans but can significantly alter system outputs. While targeted attacks on end-to-end ASR models have been widely studied, the phonetic basis of these perturbations and their effect on speaker identity remain underexplored. In this work, we analyze adversarial audio at the phonetic level and show that perturbations are associated with systematic phonetic tendencies, such as vowel centralization and consonant substitutions. Using the DeepSpeech ASR model as our target, we generate targeted adversarial examples and evaluate their impact on speaker identity embeddings across genuine and impostor samples. Results across 16 phonetically diverse target phrases demonstrate that adversarial audio induces both transcription errors and identity drift, highlighting the need for phonetic-aware defenses to ensure the robustness of ASR and speaker recognition systems.

AI slop is flowing onto every major platform where people post online--and Medium is no exception. The 12-year-old publishing platform has undertaken a dizzying number of pivots over the years. It's finally on a financial upswing, having turned a monthly profit for the first time this summer. Medium CEO Tony Stubblebine and other executives at the company have described the platform as "a home for human writing." But there is evidence that robot bloggers are increasingly flocking to the platform, too.