UnHerd69%

AI has ruined literary prizes 54%

By Vincenzo Barney0%

7/4/2026, 1:00:20 PM

BS Summary: This article contains 35 faulty reasoning types, including Hasty Generalization, Biased Writer Voice, and Slippery Slope, with Negativity Bias as the most egregious example at 30.5% saturation with 239 hits. Analysis detected 2,217 faulty-reasoning hits from 784 analyzed words, generating a BS Score of 52.3% and a BS Rank of 54% (10,146 of 21,887 articles). This article is worse (more manipulative) than 53.60% of the article peer group.

This week, the Commonwealth Short Story Prize, run by the UK-based Commonwealth Foundation, gave its annual award to Trinidadian writer Jamir Nazir for his short story “The Serpent in the Grove”. 
Established to spotlight new voices from underrepresented parts of the Commonwealth, the prize is intended to elevate writers from regions often overlooked in global publishing circuits. 
Nazir’s story supposedly had just the underrepresented qualities they were looking for. 
Nazir’s name will be familiar to some because in May the prize, which had an agreement with prestigious UK-based literary magazine Granta to publish its finalists, was found to have shortlisted at least three howlers that were most likely generated by AI. 
In particular, Nazir’s “The Serpent in the Grove” quickly attracted attention for its chatbot syntax and bizarre lines such as “She had the kind of walking that made benches become men.” 
Granta’s human readership  rather than its editors or Commonwealth’s professional-writer judges  were the ones to cry foul. 
After being run through AI-detection software, “The Serpent in the Grove” and two other short stories were found to be entirely or almost entirely generated by AI. 
Nazir’s photograph appeared to be AI-generated as well, a falsification to which Nazir later admitted. 
“That definitely had AI in it,” he said to writer Kevin Hosein in now-deleted screenshots, “because I had taken that shot with an old t-shirt on and guys in India wanted a picture to put because I was supposed to be on a board of directors for another company and they used that by putting the suit and maybe cleaning up the beard.” 
The explanation raises more questions than it answers. 
Why was Nazir impersonating a board member for an Indian company? 
Does this convoluted stratagem suggest the skills of a prize-winning writer? 
During the initial scandal, Granta released a statement to journalists, distancing itself from the controversy. 
“Granta editors have no control over the selection of the Commonwealth Prize stories, and nor are they involved in choosing the jury,” the journal’s publisher, Sigrid Rausing, explained. 
Rausing also struck an arch tone, musing: “It may be that the judges have now awarded a prize to an instance of AI plagiarism  we don’t yet know, and perhaps we never will know.” 
On 19 June, however, Granta announced an end to its partnership with the Commonwealth Foundation. 
“For the sake of our own editorial integrity, the Granta Trust board has now taken the decision that we will no longer engage in external publishing partnerships,” a prepared statement read. 
Since May, the “all-star judging panel” of another prestigious publication, the UK edition of the magazine Harper’s Bazaar, has fallen for AI content. 
The magazine flew “writer” Kavyta Kay to Burgh Island, off the coast of Devon, for a stay in the Burgh Island Hotel as a reward for winning first place in its short story competition. 
Talk about bizarre: her Nazir-like tale, “Back and Forth”, was also found by writer Nabeel S. 
Qureshi  the first to discover Nazir’s AI  to be 100% AI-generated. 
“There’s no formula to a successful short story,” Ruth Ozeki, the award-winning novelist and head judge of the Harper’s prize, said, announcing the winner. 
“But whatever its strength is going to be  whether plot, a narrative voice or poetic language  it must be established quickly.” 
What Kavyta Kay’s AI chatbot established quickly was all the necessary clichés and stereotypes that the Leftist mainstream requires in order to ventriloquize the Third World. 
The piece included wise, anthropomorphic nature (that knowing, waiting tree), tiredness from long walks (the burden of being a non-Westerner), and a connection to animal and bodily instincts (their feet taking them to places they can’t foretell). 
Not to mention that the story is written in the unmistakable, consolidated unistyle of the modern mainstream. 
Harper’s Bazaar has yet to release a statement on the scandal. 
We’ve been hurtling toward this moment for a long time, and may have arrived sooner than we expected. 
As the publishing-industrial complex has long favored bad algorithmic writing  or what it calls mainstream and upmarket  a human might be able to venture a few conclusions: publishers and arbiters of taste are not, and have never been, on the side of the individual, only the collective. 
They care only if humans buy their books, not if they write them. 
We’re heading for a future in which publishers can pinch a penny by replacing the already small cost of fees and book advances with monthly premium subscriptions to an AI bot. 
Storytelling will be replaced by corporations generating slop at the click of a mouse. 
Where we go from there, perhaps only the trees know. 
Article reasoning-pattern comparisonThis article: 5.0%Vincenzo Barney: 5.9%Unherd: 6.6%Confirmation Bias5.0%This article: 0.0%Vincenzo Barney: 0.2%Unherd: 0.4%Anchoring Bias0.0%This article: 10.5%Vincenzo Barney: 3.8%Unherd: 3.5%Availability Heuristic10.5%This article: 8.0%Vincenzo Barney: 1.2%Unherd: 1.8%Representativeness Heuristic8.0%This article: 2.3%Vincenzo Barney: 1.3%Unherd: 1.4%Hindsight Bias2.3%This article: 5.7%Vincenzo Barney: 1.8%Unherd: 2.7%Overconfidence Bias5.7%This article: 5.0%Vincenzo Barney: 1.2%Unherd: 5.1%Framing Effect5.0%This article: 0.0%Vincenzo Barney: 0.1%Unherd: 0.3%Loss Aversion0.0%This article: 0.0%Vincenzo Barney: 0.5%Unherd: 0.6%Status Quo Bias0.0%This article: 6.3%Vincenzo Barney: 0.2%Unherd: 0.2%Sunk Cost Effect6.3%This article: 0.0%Vincenzo Barney: 0.9%Unherd: 1.3%Optimism Bias0.0%This article: 13.8%Vincenzo Barney: 1.6%Unherd: 3.0%Pessimism Bias13.8%This article: 30.5%Vincenzo Barney: 12.5%Unherd: 10.7%Negativity Bias30.5%This article: 0.0%Vincenzo Barney: 0.1%Unherd: 0.7%Self-Serving Bias0.0%This article: 5.5%Vincenzo Barney: 1.0%Unherd: 1.8%Fundamental Attribution Error5.5%This article: 0.0%Vincenzo Barney: 0.1%Unherd: 0.2%Actor-Observer Bias0.0%This article: 5.7%Vincenzo Barney: 1.4%Unherd: 1.6%In-Group Bias5.7%This article: 0.0%Vincenzo Barney: 0.3%Unherd: 1.8%Out-Group Homogeneity Bias0.0%This article: 0.0%Vincenzo Barney: 0.0%Unherd: 1.7%Halo Effect0.0%This article: 0.0%Vincenzo Barney: 0.0%Unherd: 0.2%Horn Effect0.0%This article: 0.0%Vincenzo Barney: 0.0%Unherd: 0.0%Dunning-Kruger Effect0.0%This article: 9.8%Vincenzo Barney: 0.7%Unherd: 1.3%Recency Bias9.8%This article: 0.0%Vincenzo Barney: 0.0%Unherd: 0.4%Primacy Effect0.0%This article: 0.0%Vincenzo Barney: 0.0%Unherd: 0.1%Blind-Spot Bias0.0%This article: 5.7%Vincenzo Barney: 1.6%Unherd: 2.2%Ad Hominem5.7%This article: 0.0%Vincenzo Barney: 2.0%Unherd: 1.6%Straw Man0.0%This article: 11.7%Vincenzo Barney: 1.7%Unherd: 3.2%Appeal to Authority11.7%This article: 7.0%Vincenzo Barney: 2.3%Unherd: 3.1%False Dilemma7.0%This article: 14.3%Vincenzo Barney: 1.7%Unherd: 2.0%Slippery Slope14.3%This article: 0.0%Vincenzo Barney: 0.3%Unherd: 0.3%Circular Reasoning0.0%This article: 24.1%Vincenzo Barney: 14.0%Unherd: 13.8%Hasty Generalization24.1%This article: 2.4%Vincenzo Barney: 0.6%Unherd: 0.3%Red Herring2.4%This article: 2.9%Vincenzo Barney: 0.3%Unherd: 0.5%Bandwagon2.9%This article: 4.0%Vincenzo Barney: 4.9%Unherd: 4.6%Appeal to Emotion4.0%This article: 3.3%Vincenzo Barney: 1.6%Unherd: 1.3%Begging the Question3.3%This article: 11.2%Vincenzo Barney: 3.2%Unherd: 3.9%Post Hoc (False Cause)11.2%This article: 8.0%Vincenzo Barney: 0.3%Unherd: 0.4%Tu Quoque8.0%This article: 1.4%Vincenzo Barney: 0.0%Unherd: 0.5%Burden of Proof1.4%This article: 2.2%Vincenzo Barney: 1.2%Unherd: 0.3%Appeal to Nature2.2%This article: 9.6%Vincenzo Barney: 0.7%Unherd: 0.8%Composition/Division9.6%This article: 13.6%Vincenzo Barney: 1.6%Unherd: 4.2%Anecdotal13.6%This article: 3.3%Vincenzo Barney: 0.6%Unherd: 0.3%No True Scotsman3.3%This article: 4.2%Vincenzo Barney: 1.3%Unherd: 1.9%Ambiguity (Equivocation)4.2%This article: 0.0%Vincenzo Barney: 0.0%Unherd: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Vincenzo Barney: 0.0%Unherd: 0.1%Middle Ground0.0%This article: 0.0%Vincenzo Barney: 0.0%Unherd: 0.1%Personal Incredulity0.0%This article: 0.0%Vincenzo Barney: 0.1%Unherd: 0.1%Special Pleading0.0%This article: 0.0%Vincenzo Barney: 0.5%Unherd: 0.4%Genetic Fallacy0.0%This article: 8.8%Vincenzo Barney: 1.3%Unherd: 2.1%Unattributed Quote8.8%This article: 4.0%Vincenzo Barney: 1.2%Unherd: 1.0%Quote-first Misdirection4.0%This article: 17.6%Vincenzo Barney: 9.0%Unherd: 13.9%Biased Writer Voice17.6%This article: 3.3%Vincenzo Barney: 3.2%Unherd: 2.3%Indoctrination3.3%This article: 8.0%Vincenzo Barney: 0.9%Unherd: 1.9%Politically Left Leaning Bias8.0%This article: 0.0%Vincenzo Barney: 0.8%Unherd: 1.5%Politically Right Leaning Bias0.0%This article: 4.0%Vincenzo Barney: 0.6%Unherd: 0.3%Attempt to Sell a Product or S…4.0%

784 words analyzed.

Speakers

5speakers28%attributed speech565writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 5 words • 100.0% coverageWriter's voice • 31 words • 0.0% coverageWriter's voice • 26 words • 0.0% coverageWriter's voice • 12 words • 100.0% coverageWriter's voice • 42 words • 0.0% coverageWriter's voice • 31 words • 100.0% coverageWriter's voice • 19 words • 0.0% coverageWriter's voice • 27 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageJamir Nazir • 63 words • 0.0% coverageWriter's voice • 8 words • 100.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 11 words • 100.0% coverageGranta • 15 words • 0.0% coverageSigrid Rausing • 28 words • 0.0% coverageSigrid Rausing • 35 words • 100.0% coverageWriter's voice • 15 words • 0.0% coverageGranta Trust board • 31 words • 0.0% coverageWriter's voice • 23 words • 100.0% coverageWriter's voice • 34 words • 100.0% coverageWriter's voice • 16 words • 100.0% coverageWriter's voice • 13 words • 0.0% coverageRuth Ozeki • 24 words • 0.0% coverageRuth Ozeki • 23 words • 0.0% coverageWriter's voice • 26 words • 100.0% coverageWriter's voice • 37 words • 100.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 49 words • 100.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 31 words • 100.0% coverageWriter's voice • 14 words • 100.0% coverageWriter's voice • 10 words • 0.0% coverage
Selected voice

Sigrid Rausing

100%flagged-word coverage
63 attributed words29% of attributed speech95% writer coverage
0%30.0%60.0%Unattributed Quote+49.5 ptsWriter: 6.0%Sigrid Rausing: 55.6%55.6%Biased Writer Voice-24.4 ptsWriter: 24.4%Sigrid Rausing: 0.0%0.0%Politically Left Leaning B-11.2 ptsWriter: 11.2%Sigrid Rausing: 0.0%0.0%Quote-first Misdirection-5.5 ptsWriter: 5.5%Sigrid Rausing: 0.0%0.0%Attempt to Sell a Product -5.5 ptsWriter: 5.5%Sigrid Rausing: 0.0%0.0%Indoctrination-4.6 ptsWriter: 4.6%Sigrid Rausing: 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.