Suspecting AI cheating 21%

By Nate Anderson39%

7/8/2026, 9:42:44 PM

BS Summary: This article contains 32 faulty reasoning types, including Negativity Bias, Confirmation Bias, and Appeal to Emotion, with Post Hoc (False Cause) as the most egregious example at 27.4% saturation with 281 hits. Analysis detected 2,896 faulty-reasoning hits from 1,025 analyzed words, generating a BS Score of 34.9% and a BS Rank of 21% (16,879 of 21,172 articles). This article is better (less manipulative) than 79.70% of the article peer group.

Ivy League college students are, by definition, intelligent. 
They don’t need to use generative AI to cheat on exams; they could just learn the material. 
But they also tend to be competitive, ambitious, and overscheduled, so AI can look like an easy shortcut that makes more time in their lives for things that can’t be done by a chatbot. 
When the pressure is on, which approach do they choose? 
A new scandal at Brown University reveals that huge numbers of these students are likely to cheat. 
A recent survey of Princeton students found that 29.9 percent admitted to cheating with AI on at least one exam or assignment. 
But the recent situation at Brown gives us a better sense of what this kind of cheating looks like in one particular class—and just how much it may be substituting for actual learning. 
And we know all this because the blind economics professor at the center of it all, Roberto Serrano, is not letting it go. 
In just the last week, Serrano—who was born in Spain—has told his story to El País and Inside Higher Ed , which have both run significant pieces on the scandal. 
The story that Serrano told them begins in December 2025, when a gunman attacked Brown’s campus and killed two people, including one who had recently introduced herself to Serrano. 
Roberto Serrano receiving an award from the King of Spain in 2025. 
Shaken by the experience, Serrano decided that his spring 2026 section of the quite difficult ECON 1170 would allow take-home exams for both the midterm and the final. 
Suddenly, the course received an influx of students. 
El País has the story: 
The course… typically attracts few students, but very good ones. 
[Serrano] has never had more than 30 students enrolled at a time, and on some occasions he had only eight. 
This semester, probably because of the new evaluation system, 86 students signed up for the class. 
The results of the midterm exam, which was administered on March 5, were extraordinary, with an average score of 96 out of 100. 
Forty students scored a perfect 100. 
This was indeed extraordinary, because as Serrano told Inside Higher Ed, “Historically the average grade in the midterm of this course has ranged between 65 and 80 [percent], and this exam was harder than the exams I wrote in the past, because… take-home is an opportunity to challenge the class a little bit more, given that you’re giving the students unlimited time.” 
Beyond the numbers, many of the answers, even when correct, felt slightly off. 
They had a “very convoluted style,” Serrano said. 
When he and his grad students ran the exam questions through ChatGPT, they received similar results. 
A suspicious Serrano decided that he would make the final exam in-person; he would see if students did similarly well on it. 
He emailed his class, telling them, “I am not declaring [the midterm] void for now. 
I am going to give the class a chance to prove me wrong. 
That is, if the distribution of the final exam is roughly similar to the distribution of the midterm, I will count the midterm. 
Otherwise, which is of course what I expect to happen, I will declare the midterm void and reweigh the final accordingly.” 
Eighteen students suddenly dropped the course, while nine others didn’t even attend the final exam. 
Of those 27 students, El País noted, “22 had scored a perfect 100 in the midterm exam.” 
Among those who took the test, the average score plunged—from 96 all the way down to 48. 
The professor was horrified by what appeared to be massive cheating in his course—cheating that was preventing most of the students from learning the material. 
Serrano comes across as someone with no inclination to coddle elite students. 
His attitude may be traceable in part to his own childhood, in which he went blind from retinal dystrophy at age 17 and had to make a choice about what the rest of his life would look like. 
From El País: 
After a short-lived crisis, he decided [blindness] would not stop him. 
He learned Braille, and his excellent academic record opened up the doors of Harvard. 
“Of course it affects my life, but one shouldn’t over-dramatize. 
We economists understand reality as a set of people responding to optimization problems with restrictions. 
I view my disease simply as one more restriction that I have to deal with, and I optimize based on that,” he says. 
As a university, Brown is grappling with hard questions about AI use at the moment. 
It recently released a provost-led report (PDF) on “Generative AI in Teaching and Learning,” which found that it’s not just professors who have concerns. 
Even though “56 percent of undergraduate respondents [at Brown] and 67 percent of graduate and medical student respondents reported intentionally using GenAI tools daily or weekly,” the report notes that large majorities of students also have “concerns about the impact of GenAI use on their learning” and a “fear of negative consequences for their cognitive capacity.” 
Serrano shares those concerns, and he wants universities as a whole to stand up for human thought. 
That’s why he’s not letting this story go, despite what he contends is a fairly tepid reaction from Brown administrators. 
“We cannot afford to have a society in which a significant fraction of our best young minds think that cheating is okay,” he told Inside Higher Ed. 
“That leads to a declining society, to a failed society. 
“We cannot choose to become idiots.” 
Nate is the deputy editor at Ars Technica. 
His most recent book is In Emergency, Break Glass: What Nietzsche Can Teach Us About Joyful Living in a Tech-Saturated World , which is much funnier than it sounds. 
Suspecting AI cheating, Ivy League prof ordered an in-person final; scores fell 50% 
US seeks cheaper hunter-killer drones after Iran destroys $1B worth of Reapers 
Two teens learn the hard way not to do toy gun drive-bys from a Waymo 
Lawsuit: Man used Grok to make 7K sex images of stepdaughter, then shot himself 
Aussie gov't tells volunteers to throw out thousands of functioning test routers 
Article reasoning-pattern comparisonThis article: 24.8%Nate Anderson: 7.3%Ars Technica: 2.8%Confirmation Bias24.8%This article: 0.0%Nate Anderson: 1.2%Ars Technica: 1.2%Anchoring Bias0.0%This article: 7.4%Nate Anderson: 2.7%Ars Technica: 2.4%Availability Heuristic7.4%This article: 3.3%Nate Anderson: 1.3%Ars Technica: 1.0%Representativeness Heuristic3.3%This article: 0.0%Nate Anderson: 1.6%Ars Technica: 0.6%Hindsight Bias0.0%This article: 3.9%Nate Anderson: 0.9%Ars Technica: 2.0%Overconfidence Bias3.9%This article: 6.0%Nate Anderson: 4.7%Ars Technica: 3.4%Framing Effect6.0%This article: 0.0%Nate Anderson: 0.0%Ars Technica: 0.5%Loss Aversion0.0%This article: 0.0%Nate Anderson: 0.0%Ars Technica: 0.5%Status Quo Bias0.0%This article: 0.0%Nate Anderson: 0.0%Ars Technica: 0.1%Sunk Cost Effect0.0%This article: 2.3%Nate Anderson: 0.0%Ars Technica: 4.2%Optimism Bias2.3%This article: 3.0%Nate Anderson: 0.6%Ars Technica: 1.7%Pessimism Bias3.0%This article: 27.1%Nate Anderson: 7.2%Ars Technica: 6.2%Negativity Bias27.1%This article: 4.8%Nate Anderson: 0.3%Ars Technica: 1.1%Self-Serving Bias4.8%This article: 4.9%Nate Anderson: 1.5%Ars Technica: 0.6%Fundamental Attribution Error4.9%This article: 7.2%Nate Anderson: 0.0%Ars Technica: 0.1%Actor-Observer Bias7.2%This article: 2.4%Nate Anderson: 1.0%Ars Technica: 0.6%In-Group Bias2.4%This article: 0.0%Nate Anderson: 0.0%Ars Technica: 0.2%Out-Group Homogeneity Bias0.0%This article: 4.3%Nate Anderson: 2.3%Ars Technica: 2.0%Halo Effect4.3%This article: 0.0%Nate Anderson: 0.2%Ars Technica: 0.1%Horn Effect0.0%This article: 0.0%Nate Anderson: 0.0%Ars Technica: 0.0%Dunning-Kruger Effect0.0%This article: 9.1%Nate Anderson: 1.5%Ars Technica: 1.0%Recency Bias9.1%This article: 0.0%Nate Anderson: 0.0%Ars Technica: 0.3%Primacy Effect0.0%This article: 0.0%Nate Anderson: 0.0%Ars Technica: 0.1%Blind-Spot Bias0.0%This article: 0.0%Nate Anderson: 0.2%Ars Technica: 0.5%Ad Hominem0.0%This article: 0.0%Nate Anderson: 0.0%Ars Technica: 0.2%Straw Man0.0%This article: 18.0%Nate Anderson: 1.7%Ars Technica: 4.1%Appeal to Authority18.0%This article: 3.2%Nate Anderson: 1.6%Ars Technica: 1.1%False Dilemma3.2%This article: 5.3%Nate Anderson: 3.1%Ars Technica: 0.7%Slippery Slope5.3%This article: 0.0%Nate Anderson: 0.0%Ars Technica: 0.1%Circular Reasoning0.0%This article: 9.0%Nate Anderson: 4.6%Ars Technica: 3.8%Hasty Generalization9.0%This article: 2.8%Nate Anderson: 0.0%Ars Technica: 0.2%Red Herring2.8%This article: 0.0%Nate Anderson: 0.0%Ars Technica: 0.6%Bandwagon0.0%This article: 23.0%Nate Anderson: 5.1%Ars Technica: 2.7%Appeal to Emotion23.0%This article: 5.4%Nate Anderson: 0.7%Ars Technica: 0.6%Begging the Question5.4%This article: 27.4%Nate Anderson: 1.9%Ars Technica: 2.4%Post Hoc (False Cause)27.4%This article: 0.0%Nate Anderson: 0.0%Ars Technica: 0.2%Tu Quoque0.0%This article: 3.8%Nate Anderson: 0.5%Ars Technica: 0.5%Burden of Proof3.8%This article: 0.0%Nate Anderson: 0.0%Ars Technica: 0.2%Appeal to Nature0.0%This article: 0.8%Nate Anderson: 0.0%Ars Technica: 0.2%Composition/Division0.8%This article: 12.6%Nate Anderson: 2.6%Ars Technica: 1.5%Anecdotal12.6%This article: 0.0%Nate Anderson: 0.0%Ars Technica: 0.1%No True Scotsman0.0%This article: 11.7%Nate Anderson: 0.6%Ars Technica: 1.7%Ambiguity (Equivocation)11.7%This article: 0.0%Nate Anderson: 0.0%Ars Technica: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Nate Anderson: 0.0%Ars Technica: 0.1%Middle Ground0.0%This article: 0.0%Nate Anderson: 0.0%Ars Technica: 0.1%Personal Incredulity0.0%This article: 0.0%Nate Anderson: 0.0%Ars Technica: 0.1%Special Pleading0.0%This article: 3.7%Nate Anderson: 0.0%Ars Technica: 0.1%Genetic Fallacy3.7%This article: 5.7%Nate Anderson: 4.5%Ars Technica: 1.5%Unattributed Quote5.7%This article: 7.0%Nate Anderson: 1.0%Ars Technica: 0.9%Quote-first Misdirection7.0%This article: 21.6%Nate Anderson: 4.2%Ars Technica: 4.6%Biased Writer Voice21.6%This article: 8.1%Nate Anderson: 1.8%Ars Technica: 1.0%Indoctrination8.1%This article: 0.0%Nate Anderson: 0.0%Ars Technica: 0.7%Politically Left Leaning Bias0.0%This article: 0.0%Nate Anderson: 0.0%Ars Technica: 0.2%Politically Right Leaning Bias0.0%This article: 2.8%Nate Anderson: 0.5%Ars Technica: 1.3%Attempt to Sell a Product or S…2.8%

1025 words analyzed.

Speakers

2speakers30%attributed speech720writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 3 words • 100.0% coverageWriter's voice • 8 words • 100.0% coverageWriter's voice • 17 words • 100.0% coverageWriter's voice • 34 words • 0.0% coverageWriter's voice • 10 words • 100.0% coverageWriter's voice • 17 words • 100.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 33 words • 100.0% coverageWriter's voice • 23 words • 100.0% coverageWriter's voice • 30 words • 0.0% coverageWriter's voice • 29 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 28 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageWriter's voice • 5 words • 0.0% coverageEl País • 10 words • 0.0% coverageEl País • 20 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 23 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageRoberto Serrano • 62 words • 100.0% coverageWriter's voice • 13 words • 0.0% coverageRoberto Serrano • 8 words • 100.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageRoberto Serrano • 15 words • 0.0% coverageRoberto Serrano • 13 words • 0.0% coverageRoberto Serrano • 23 words • 0.0% coverageRoberto Serrano • 21 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageEl País • 17 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 25 words • 100.0% coverageWriter's voice • 12 words • 100.0% coverageWriter's voice • 38 words • 0.0% coverageWriter's voice • 3 words • 0.0% coverageEl País • 11 words • 100.0% coverageEl País • 14 words • 0.0% coverageRoberto Serrano • 10 words • 0.0% coverageRoberto Serrano • 15 words • 0.0% coverageRoberto Serrano • 23 words • 100.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageWriter's voice • 56 words • 100.0% coverageWriter's voice • 17 words • 100.0% coverageWriter's voice • 20 words • 100.0% coverageRoberto Serrano • 27 words • 100.0% coverageRoberto Serrano • 10 words • 0.0% coverageRoberto Serrano • 6 words • 100.0% coverageWriter's voice • 8 words • 0.0% coverageWriter's voice • 29 words • 100.0% coverageWriter's voice • 13 words • 100.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverage
Selected voice

Roberto Serrano

79%flagged-word coverage
233 attributed words76% of attributed speech96% writer coverage
0%15.0%30.0%Biased Writer Voice+6.1 ptsWriter: 20.6%Roberto Serrano: 26.6%26.6%Indoctrination+20.3 ptsWriter: 3.8%Roberto Serrano: 24.0%24.0%Unattributed Quote+11.8 ptsWriter: 3.2%Roberto Serrano: 15.0%15.0%Quote-first Misdirection-10.0 ptsWriter: 10.0%Roberto Serrano: 0.0%0.0%Attempt to Sell a Product -4.0 ptsWriter: 4.0%Roberto Serrano: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.