They Won a Prestigious Writing Prize. Then These Key Giveaways Sparked Allegations of AI

A London-based literary competition is facing major scrutiny after three of five winners have been accused of using AI—partly or wholly—to write their prize-winning stories. The 2026 Commonwealth Short Story Prize selected one winner each from five regions that span Africa, Asia, Canada and Europe, the Caribbean, and the Pacific. Following publication of the winning entries in literary magazine Granta, online sleuths called foul. The Caribbean regional winner, Jamir Nazir, was praised for the “lyrical precision and haunting atmosphere” of his short story “The Serpent in the Grove,” as well as “the confidence and restraint of its voice,” according to a post on social media platform X by Commonwealth Foundation Creatives. But internet denizens allege that the very same voice that won the prize may not be human at all. Nabeel S. Qureshi, an AI marketing entrepreneur and a former visiting scholar at the Mercatus Center at George Mason University, flagged certain signs he said were AI tells such as “‘Not X, not Y, but Z’ sentences,” as well as the use of the word “‘hum,'” in a post on X. He concluded by writing: “A major milestone for AI, at any rate …” Following the allegations, Wired ran the text of “The Serpent in the Grove” through AI detection tool Pangram, which the publication notes has consistently outperformed other similar tools. It determined that the text was 100 percent AI-generated. It’s worth noting that no AI-detection tools are totally accurate. “The Serpent in the Grove” isn’t the only story under scrutiny. Pangram determined that “The Bastion’s Shadow” by John Edward DeMicoli, the winner from Malta, was also fully AI-generated and that “Mehendi Nights” by Sharon Aruparayil, the winner from India, was partially written using AI. Holly Ann Miller’s “Second Skin,” and Lisa-Anne Julien’s “Me and Ma’am,” however, were ruled “fully human-written” by Pangram, according to Wired. The regional winners were chosen from 7,806 entries, which the Commonwealth Foundation noted on its site is the “second highest number in the Prize’s history.” A final winner from among the five will be announced on June 30. Following the allegations, the Commonwealth Foundation released a statement on its website, acknowledging the challenges generative AI poses to literary and creative work. The statement also noted that the foundation’s judging process is robust, but judges do not currently use AI checkers in any stage. “We are aware of allegations and discussion regarding generative AI and our Short Story Prize. We take these claims seriously and are committed to responding to them with care and transparency,” the statement reads. “When they submit stories to the Prize, writers accept our entry rules and guidelines. These include confirming that their submission is their own original work. All shortlisted writers have personally stated that no AI was used and, upon further consultation, the Foundation has confirmed this.” The foundation also noted that until a reliable tool emerges with which the organization can screen unpublished work for AI, the prize competition “must operate on the principle of trust.” As always, Redditers had much to say about the subject, some assuming AI guilt, others questioning the accuracy of the AI checking tools, and many picking at the quality of the stories more broadly. “This…doesn’t surprise me given the state of contemporary literary prose. It honestly just reads like bog-standard ‘MFA voice,’” one Redditor wrote of Nazir’s story. A recent report from digital marketing agency Graphite found that since the debut of ChatGPT in 2022, there has been a meteoric rise of AI-generated content on the internet. The number of articles written by AI now equals that of human-written content, although the overall share seems to have plateaued. Axios reported at the time that the quality of AI-generated writing has meaningfully improved, not to mention that it can be difficult to determine what constitutes AI writing. Whereas some content is mostly or entirely AI-generated, some writers use AI tools throughout the process of drafting and editing. BY CHLOE AIELLO @CHLOBO_ILO

Anthropic Just Banned Being Cruel to Claude. The Reason Should Concern Us All

There are lots of reasons to have feelings about artificial intelligence. It seems like everyone thinks AI will replace human workers. There are real questions about the ethics and legality of scooping up basically the entire internet to train models. There are even questions about how they work and whether they could someday become dangerous. If you understand nothing else about AI chatbots, understand this: They do not have feelings. They are not people, and they don’t experience pain or frustration. They’re token-generation machines. You give them a prompt, they break it down into tokens, and then they generate new tokens one at a time using a predictive model trained on enormous amounts of human writing. At its basic level, it’s 1s and 0s running through transistors in a GPU in some data center in Boise, Idaho, or wherever. Sometimes those 1s and 0s come back out as tokens that sound a lot like feeling words. But, and this is important, using words to describe feelings isn’t the same thing as having feelings. Claude produces those words only because it was trained to produce a response the way humans would respond in a similar situation with similar language input. That doesn’t make it human or capable of human experiences. Which is why it’s worth noting that Anthropic issued an update to its usage policy that bans being cruel to its model. You cannot be cruel to something incapable of experiencing pain or suffering, and an LLM is capable of neither. Look, thinking that it’s absurd that Anthropic is making this a policy isn’t the same as condoning bad behavior. I don’t condone cruelty in any situation. No one should. But my reason is just that it’s bad to practice cruelty, not because you might hurt a chatbot’s feelings. In its updated usage policy, which takes effect November 12, Anthropic says it now prohibits “sustained and needless abusive or cruel behavior toward our models.” The company says the new policy applies only to what it calls extreme cases of repeated abuse, not ordinary frustration, criticism, or legitimate research. Apparently, you’ll still be able to tell Claude that it’s doing a bad job; you just can’t do it repeatedly and for no reason. On the one hand, that might seem like a relatively harmless policy. We can even all agree that antisocial or cruel behavior shouldn’t be encouraged. But I also think that you can believe more than one thing at a time. For example, you can believe it’s not useful for you or the experience of using the model to be overly aggressive, taunting, or insulting toward a piece of computer software. Likewise, if you find yourself drawn toward trying to repeatedly engage an AI chatbot in disturbing conversations, you might want to do some self-reflection and seek help. But I don’t think that is inconsistent with also believing that Anthropic’s policy raises a much bigger question about how AI companies want us to think about their products. Specifically, why would a company that builds software believe it needs to protect that software from cruelty? Anthropic’s stance on Claude’s feelings This isn’t the first time the company has said that its AI models might need some measure of moral consideration. Last year, the company announced that Claude could end conversations with users who are repeatedly abusive. At the time, Anthropic explained that the decision was motivated primarily by research into what it calls “model welfare.” Anthropic has contributed to this problem with its stance on whether its models are conscious or capable of subjective experiences. It has repeatedly suggested the possibility that they might be, and now it’s using that as a reason to establish rules about how people interact with its software. There is a meaningful debate about consciousness and why physical and chemical interactions result in a sense of self-being and subjective experience. It’s a big enough challenge that it’s even called the hard problem of consciousness. But it’s a leap to go from the idea that scientists and philosophers don’t fully understand consciousness to suggesting that a chatbot might be capable of experiencing cruelty. To be fair, there’s nothing wrong with Anthropic deciding that it doesn’t want people using Claude to practice abusive behavior. There are reasonable arguments for discouraging that sort of thing, especially if it might reinforce harmful behavior toward actual people. But that’s not the same thing as saying people shouldn’t be cruel to Claude. The people problem The bigger problem is that Anthropic is suggesting something that should concern us all: It’s conditioning us to think of chatbots as though they were people. We already know that users can develop emotional attachments to AI companions. AI chatbots are designed to communicate naturally, similar to the way a human would. For people who are lonely or emotionally vulnerable, the distinction between a simulated relationship and actual human connection can become increasingly difficult to discern. That’s why the language these AI companies use is especially important. When a chatbot tells someone it cares about them, the company behind it should be making clear that those words are just tokens generated by software, not evidence of some kind of personal connection or affection. But Anthropic is, instead, suggesting the possibility that the relationship might work both ways. If Claude can be treated cruelly, wouldn’t that suggest it can also experience kindness? If it can suffer, couldn’t it also care about the person it’s talking to? To be fair, Anthropic doesn’t explicitly make those claims. But suggesting that its models need to be protected from pain and suffering introduces a dynamic that points to only one thing—it sure seems like it wants you to think of it as a person. I would argue that’s exactly the sort of confusion AI companies should be working to prevent. Right now, AI companies are pushing their technology at a relentless pace. The result of that is that it is becoming far more useful. At the same time, it is becoming incredibly complex, and it’s getting harder to understand how it works. Those companies should be trying to help users understand the difference between language that sounds like human feelings and emotion, and actual human experience. Obviously, Anthropic has every right to set rules for how customers use its products. But that doesn’t mean we shouldn’t ask questions about those rules, especially when they reinforce potentially misleading ideas about what artificial intelligence is. In fact, the most concerning thing about Anthropic’s new policy isn’t whether Claude might someday develop feelings. It’s that one of the companies building the world’s most powerful AI systems is already asking us to behave as though it has. EXPERT OPINION BY JASON ATEN, TECH COLUMNIST @JASONATEN

Google’s Newest Gemini Model Can Handle Your Invoices, Contracts, and Taxes. There’s Just 1 Catch

Buried in administrative tasks? Google’s newest Gemini model could help do them for you. On Wednesday, the search giant unveiled Gemini 4 Argon, its new frontier AI model. Google said Argon excels at complex tasks in areas like legal research, taxes, and finance. It ranks first on a key leadership board for knowledge work tasks, beating the likes of Anthropic’s Claude and OpenAI’s GPT-6 models. To support Argon’s complex workflows, Google is expanding the model’s output limit from 64,000 tokens to a whopping 1 million tokens. (Tokens are the chunks of data AI models process and generate.) Google said the higher limit gives Gemini more room to reason through tough problems and generate longer responses in one go. For founders, that could mean tackling complex workflows without breaking them into smaller requests. Google claims Argon can process invoices, draft contracts, and plan taxes exceptionally well, leaving more time for humans to build brands, land clients, and iterate on products. It could also mean higher-quality outputs so the tokens you’re burning through are well spent. Google announced introductory pricing of $2 per million input tokens and $10 per million output tokens, meaning longer workflows can rack up your AI bills. Google said Argon is accelerating its internal workflows, including optimizing quantum computing algorithms, reducing memory use in data centers, and migrating large codebases to new programming languages, helping its teams build faster. The company also touts Argon’s enhanced cybersecurity capabilities, saying it can find, validate, and fix software vulnerabilities. Founders will have to wait to get their hands on Argon. Google began its initial rollout through the Fairwind program, which gives vetted partners, including governments, healthcare providers, and telecommunications operators access to its AI cybersecurity tools. Participants can use Argon to find and address security flaws, with access restricted to internal cybersecurity teams. Google says it will gather feedback and strengthen safeguards before expanding availability. The release comes four weeks after Google launched Gemini 3.8 Flash, described as offering stronger reasoning and coding capabilities at the same speed and low cost as its predecessor. Meanwhile, Gemini’s audience keeps growing. In August, Google said the Gemini app surpassed 1 billion monthly users, making it the fastest-growing product in the company’s history. Google has its eyes on small businesses, too. Josh Woodward, who oversees Gemini and Google Labs, said on X that businesses are using Gemini to create marketing materials. For startups, Google offers a vertically integrated approach, hosting AI models, cloud infrastructure, its own chips, and technical assistance under one roof. Google Cloud’s startup chief Darren Mowry previously told Inc. that this approach can shorten the time it takes founders to build. BY AARON MOK

Wondering If AI Wrote That Document? These Are the Surprising New Clues

Artificial intelligence has come a long way in a short time, but it still has quite some distance to go before its writing abilities are indistinguishable from human authors’. A new study from Graphite, a San Francisco-based marketing firm, has examined the writing styles of the major frontier AI models. And while you won’t be able to catch AI-written prose quite as easily as you used to (when the models couldn’t get enough of the word “delve” and had em dashes everywhere), there are still plenty of signs to look for. The good news for AI companies is the gap is closing, albeit slowly. An October 1 study found Anthropic’s Claude Opus 5.5 had 2,548 tells that a document was being written by AI. That’s down from 3,746 with Opus 4. An earlier study by the group, which was released in mid-September, said it collectively found almost 13,000 tells among all frontier AI models. An earlier model of Claude Opus (Opus 5), for example, used the pattern “less like a _ and more like” roughly 105 times as often as human writers. Graphite didn’t update the frequency count of that particular phrase in its updated study, but it did note that the overall word-distribution divergence (a statistical measure of how differently two texts use words overall) from human writing is 19 percent lower than it was with Opus 5, which was released on July 24. Not all AI models are improving, though. The word-distribution divergence of GPT-6 Astra, released September 4, is 8 percent higher than that of GPT-5.6 Sol, which debuted on July 9 of this year. In other words, Astra is getting worse at writing like us. So long, em dashes One message was clearly received by programmers, though—get rid of the em dash. Opus 5.5 uses em dashes 99 percent less often than Opus 5, the study found, while Astra uses them 95 percent less often than GPT-5. Both, in fact, use the punctuation less than human-written stories—like this one. Still, there are plenty of tells. The study of Opus 5.5 found that the AI continues to have some favorite words it defaults to, though maybe not quite as much as it did with “delve” in the early days. “Dependable” is a favorite of the Anthropic model, getting used 23 times more often than humans use the word. “Clearer” is also a high-ranker, being used 14 times as frequently. Other go-to words included “matters” (13X), “quietly,” “practical,” and “steady” (all 11X). When it comes to transitioning between ideas, Opus 5.5 is a tremendous fan of the phrase “looking ahead the,” using it 40 times more than the human rate. Other popular picks include “Adds another later” (27X), “What comes next (24X), and “in practice” (7X). Those tells pale in comparison with the ones AI exhibits when it tries to point out things it feels readers might miss. Opus 5.5 used “this matters” 116 times more frequently than humans—and “why __ matters” 92 times more often. And when describing something by contrasting it with another item or idea, it favored “is more than a __, it” (e.g., “alcohol is more than a disinfectant, it can also be consumed”), using the phrase 98 times more than the human rate. (“Rather than simply” was the runner up, with a 32X usage.) Researchers also compared Opus 5.5 with GPT-6 Astra and found that AI tells were hardly universal. Some 65 percent of tells are unique to one model family, the September study found. Astra, for instance, used the phrase “does not establish” 275 times more than Opus 5.5. Anthropic’s model, meanwhile, leaned into some superlatives 79 times more frequently than Astra. Despite it all, Graphite notes that Opus 5.5 is making progress toward mimicking human writing, even if it still has a long way to go. “Some tells become less common, while others become more common,” it wrote. “Opus 5.5 uses well-known tells less often and its overall word use is more similar to human writing, but it still disproportionately uses thousands of words, phrases, and frames.” BY CHRIS MORRIS @MORRISATLARGE