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AI detectors are creating a new era of distrust | The Verge

More people are adopting AI detection tools to determine if what they’re reading was generated by a machine. However, these tools may not be as accurate as t...

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AI detectors are creating a new era of distrust | The Verge
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AI detectors are creating a new era of distrust | The Verge

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Tools that promise to detect AI writing can be dubious, but educators and publishers are using them anyway.

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Tools that promise to detect AI writing can be dubious, but educators and publishers are using them anyway.

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If you buy something from a Verge link, Vox Media may earn a commission. See our ethics statement.

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Long before Chat GPT became a thing, educators and editors frequently used anti-plagiarism tools to see if writers were being honest about their work. These tools work by comparing a written work against a database filled with content from across the web, scholarly articles, and more to check for matching sentences and phrases. Some, like Turnitin, offer a percentage that claims to illustrate how much of the student’s writing overlaps with other works. Between potential false positives and uncertainty about whether work was duplicated intentionally, some educators have backed away from using that particular tool.

But now, the hunt for copied content is evolving into a war on AI-generated work. As quickly as students have picked up Chat GPT, Google Gemini, and Microsoft Copilot, teachers have adopted so-called AI detectors just as fast. A survey from the Center for Democracy and Technology found that 43 percent of sixth to 12th grade teachers in the US regularly used AI detectors between 2024 and 2025. Some universities already using Turnitin in their learning management systems found that the service automatically enabled AI detection when the tool launched in 2023.

Instead of comparing pieces of written content, AI detectors like GPTZero, Pangram, and the one created by Turnitin rely on their own AI models to guess whether something might not be human-written — a process that’s arguably even murkier than matching text on the web. As noted by GPTZero, AI detectors use an algorithm to analyze a text’s wording, rhythm, and structure, as well as to pick up on patterns in length and tone that may be more common in AI-written text. This relatively subjective evaluation isn’t as solid as something you could back up by matching text online, and can get tripped up by writers who speak English as a second language. Despite this, Turnitin has said that its AI detector falsely flags less than 1 percent of human-written content as AI, while Pangram claims its false positive rate is just 1 in 10,000. GPTZero claims it has a similarly low rate of mistaking human content for AI.

People online are already accusing each other of “sounding like AI,” but the ready availability of AI detection tools is only adding fuel to the LLM witch hunt. In some high-profile cases, AI writing accusations have directly impacted people’s livelihoods and reputations. Last month, the publisher Minotaur dropped a $2 million book deal over concerns that its author, Jerry Falade, used AI — something he vehemently denies.

There’s Thierry Rignol, a French national who sued Yale last year after a professor accused him of writing portions of his final exam with AI, resulting in a failing grade and a one-year suspension. The professor used GPTZero to scan Rignol’s writing for signs of AI, but the lawsuit argues that “AI surveillance and detection tools are known to unfairly target non-native English speakers” like Rignol. In February, a student at Adelphi University won a lawsuit against the school after his professor similarly claimed he used AI to write an essay. Though the lawsuit doesn’t say which AI tool the professor used to examine the student’s essay, Adelphi University has a licensing agreement with Turnitin.

A 2023 Stanford study found that AI detectors falsely flagged essays written by non-native English speakers as AI more often than native speakers. (Many services still argue that their tools are accurate when dealing with text written by non-native speakers.) These tools may also be biased against neurodivergent writers.

As pointed out by the University of California, Los Angeles, AI detection tools are trained to pick up on patterns that could indicate AI use, such as repetitive terms and phrases, text that sounds too formal or informal, and nonsensical phrasing. Some, like Quill Bot, also measure the “unpredictability” of text, as “AI tends to make the most ‘obvious’ or most common language choices as compared with human-produced writing,” according to UCLA. They may also look for sentence structure that remains the same throughout as another sign of AI. But these measurements aren’t indicative of AI on their own, as some people may just have a writing style with these qualities.

Even though Turnitin touts low false positive rates, it maintains that its tool “may not always be accurate” and shouldn’t be used to take actions against a student. Grammarly warns that users “should never rely on the results of an AI detector alone,” while GPTZero says “no AI detector can ever truly be 100% perfect.” Open AI even shut down its own AI writing detector in 2023 due to low accuracy.

But AI writing accusations are still being flung across the web. Last week, in a video broadcast to the more than 3.5 million followers across his social channels, Ozzy Osbourne’s son, Jack, accused journalist and Verge contributor Kat Tenbarge of using AI to write an article for Rolling Stone, while flaunting the results from an AI detector, Getsolved, as “proof” of his claim. Tenbarge has refuted the claim in a video and a post on her website, but Osbourne hasn’t retracted his accusation or deleted the video, leaving Tenbarge to deal with the trolls.

There are numerous examples of false accusations, from writers to students, with many accusers failing to acknowledge the disclaimers that come along with some of these AI detection tools.

The uncertainty surrounding AI detectors is enough for some educational institutions to stop using them altogether. Yale University, Johns Hopkins University, Vanderbilt University, Georgetown University, and others have disabled or restricted the use of AI detection tools. The Massachusetts Institute of Technology also warns that “AI detectors don’t work.”

Instead of relying on tools to weed out AI, many schools are encouraging educators to rethink their lessons. The University of Chicago, for example, suggests telling students to slow down their reading, breaking up longer writing assignments, and requiring students to reflect on their work. Stanford University says professors can consider holding assessments in classrooms, while MIT advises professors to leave room for students to disclose whether they used AI for help on an assignment, without penalty.

With AI becoming more prevalent in and outside the classroom, efforts to suss out what’s written by a human or a machine are ramping up as well. Some online platforms are only exacerbating suspicions surrounding AI use. Substack has built Pangram into its app, allowing users to scan blogs for suspected AI-generated content, while Linked In added a “seems like AI slop” button on posts. The result is a new era of distrust, where readers constantly question whether what they’re reading is AI and real human writers try their best not to sound like it.

The Authors Guild is helping writers get ahead of accusations by giving them “Human Authored” certifications. There are also Not by AI and Written by Human badges users can add to their work online.

Wikipedia created a guide to help editors spot AI writing, which includes looking for writing that “puffs up” the importance of a topic or provides “superficial analysis of information.” The site has also banned AI-generated articles.

The New York Times has a fun quiz that asks you to look at five pairs of passages and choose which blurb you like better — the catch is that one of them is written with AI.

Inside Higher Ed spoke to some educators about how they’re approaching AI in school, with one lecturer raising concerns about the costs and resources that could go into AI-proofing assignments.

My colleague Jess Weatherbed detailed how the fanfiction community is having its own internal struggle over how to determine which stories are generated by AI.

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