The New York Times, a venerable institution synonymous with journalistic integrity and literary prowess, faced intense scrutiny online this week after netizens speculated that a deeply personal essay featured in its storied “Modern Love” column was generated using artificial intelligence and published without proper disclosure. This incident, while unproven in its AI allegations, has ignited a fervent debate across social media and within the publishing industry, underscoring a palpable and growing paranoia among readers regarding the authenticity of digital content.

Nothing has been definitively proven; the accusations of AI involvement remain exactly that—speculation. However, the anxiety and distrust among the reading public, fueled by the rapid proliferation of generative AI, are very real and increasingly widespread. This particular controversy kicked off over the weekend, when Becky Tuch, a discerning editor from Lit Mag News, took to X (formerly Twitter) to raise significant concerns about a “Modern Love” essay published by the newspaper in November 2025. The piece, titled “I Was Deemed Unfit to Be a Mother,” was attributed to a Canadian writer named Kate Gilgan and detailed the author’s harrowing experience of losing custody of her son due to her struggles with alcoholism, a narrative that should, by its very nature, be profoundly human and authentic.

“I don’t want to falsely accuse writers of AI-use. But this reads EXACTLY like AI slop,” Tuch wrote in a Sunday post that quickly went viral. She continued, highlighting the gravity of the potential transgression: “And this is the frickin [New York Times] Modern Love column, which is notoriously competitive, super hard to break into. Just sad.” The “Modern Love” column, a Sunday staple since 2004, is renowned for its poignant, first-person essays on the complexities of contemporary relationships, often serving as a launching pad for emerging writers and a cherished platform for established voices. Its esteemed reputation makes any hint of AI involvement particularly jarring to both readers and writers alike.

In her initial post, Tuch shared a crucial screenshot of a section of Gilgan’s piece, which read:

Not hate. Not anger. Just the flat finality of a heart too tired to keep trying.

That’s when I stopped fighting.

I didn’t give up. I shifted.

I stopped thinking love was something I had to prove with court documents and supervised visits and legal bills. I stopped chasing every possible way to make him see I had changed. I started focusing on actually changing.

It is true that the textual excerpt, when analyzed, includes sentence structures and rhetorical devices commonly associated with AI-generated text. A guide issued last year by Wikipedia editors, for example, specifically called out how much chatbots seem to favor parallelisms—a stylistic technique Gilgan employs quite prominently in the first few sentences of the flagged excerpt, framing her experience in an “it’s ‘not X, not X, but Y’” format. This structured repetition, while a legitimate literary device, has become a hallmark of AI writing, which often optimizes for clear, concise, and rhetorically balanced phrasing to mimic human prose. Furthermore, large language models have also been frequently observed to rely heavily on the “rule of three,” a well-known rhetorical tool that suggests ideas presented in threes are more memorable and impactful. Gilgan’s essay, both in the excerpt flagged by Tuch and throughout the broader piece, features plenty of rule-of-three-style text, further fueling the algorithmic suspicion.

The online community quickly piled onto Tuch’s post, creating a maelstrom of opinions. Some agreed vehemently with her, proclaiming that the text appeared to be pure “AI slop,” devoid of the nuanced imperfections and unique voice typically found in human-written personal essays. They pointed to the almost too-perfect cadence and the slightly generic emotional arc as evidence. Others, however, offered a different perspective, arguing that to them, the piece simply read like regular “Modern Love” material, suggesting that the column itself, over its long tenure, might have cultivated a certain stylistic expectation that could inadvertently overlap with AI-generated patterns.

“There’s been one lone guy editing [Modern Love] for about two decades and this is what he sounds like. It’s how he edits. I’ve been edited by him and I recognize the style,” commented the acclaimed writer Ann Bauer, offering a crucial insider’s view. She added a caveat: “This def could be AI! Not saying it isn’t. But to me, it just sounds like a Modern Love.” Bauer’s comment highlights a critical dilemma: when established editorial styles, honed over decades, begin to resemble the output of algorithms trained on vast datasets of human writing, how do we confidently discern the human hand from the machine? This blurs the lines, making definitive judgment based solely on style exceedingly difficult and potentially unfair.

Yet others made a different, equally vital point entirely: that making allegations about AI use based on writing style alone is a dangerously slippery slope, fraught with the potential for false accusations and the chilling effect on human creativity. “I think accusing writers of AI use without evidence is a pretty bad road to go down,” responded Public Books editor Dennis Hogan, emphasizing the broader implications for the writing community. Such accusations, without concrete proof, could unfairly tarnish a writer’s reputation and stifle experimentation with stylistic devices, forcing authors to self-censor to avoid suspicion.

In an attempt to clarify the situation, we reached out to both Kate Gilgan and the New York Times for comment but did not receive a response by the time of publication. While “Modern Love” itself does not appear to have a standalone, publicly articulated AI policy, the broader NYT’s general AI policy promises transparency about the use of generative technology in its newsroom operations. This institutional commitment to disclosure would theoretically apply to contributor content as well, making any undisclosed AI generation a violation of their stated principles. However, it is crucial to reiterate: all of this discussion remains conjecture, based wholly on the subjective interpretation of the writing itself. While some individuals shared screenshots of AI detection tools flagging the writing as “likely AI-generated,” these programs should always be taken with a heavy serving of salt. Numerous studies and real-world examples have demonstrated their propensity for false positives and their general unreliability, often failing to distinguish sophisticated human writing from AI output, or vice-versa.

It’s worth noting a fundamental truth that often gets lost in the AI panic: the large language models (LLMs) powering chatbots didn’t actually invent “not X, but Y” parallelisms, nor did they create the rule of three. These are time-honored rhetorical and literary devices that have been employed by human writers for centuries to add emphasis, rhythm, and clarity to their prose. They also didn’t invent em-dashes—those versatile punctuation marks that can signify a sudden break in thought, an emphatic pause, or an explanatory phrase—which many netizens have, rather alarmingly, come to take as another telltale sign of AI writing. This phenomenon has deeply frustrated many human writers who don’t want to give their beloved em-dashes up, even as AI-generated marketing copy, low-quality articles, and self-published books increasingly guzzle up and zombify these styles, making them feel cheapened and suspect.

“So I hear that em dashes are now being used as an indicator that a written work is AI. Well, you know what? F*ck that,” one Reddit user wrote last year in r/FanFiction, expressing a sentiment shared by many. “I use em dashes all the time. I’ve used them since I started writing fanfiction, and I’m not going to stop now just because some new reader might think it’s AI.” Another Redditor responded in the same thread, echoing the sentiment: “I love em dashes! How else [do] I signify a pause and my change of thought? In other news – I’m just gonna keep using them.” This micro-level debate over punctuation marks highlights the macro-level anxiety surrounding AI’s pervasive influence on language itself, forcing human creators to question stylistic choices that were once simply part of their authentic voice.

The broader debate highlights how profoundly uncanny the internet has become in the AI age, transforming the digital landscape into a hall of mirrors where reality is increasingly difficult to pin down. AI-generated sexy truckers, faux disabled veterans, and a myriad of other AI-enabled engagement-bait plots have taken over social media feeds, fooling countless users into believing they are interacting with real people or authentic scenarios. Many of us now find ourselves zooming into alleged photos—of people, of war zones—meticulously looking for tell-tale signs like misshapen buildings, mangled fingers, or distorted backgrounds. This constant vigilance transforms casual browsing into an exercise in forensic analysis. Beyond images, AI is being used to churn out fake Amazon reviews, pervasive social media clickbait, and entire books ranging from formulaic romantasy dramas to dangerously inaccurate mushroom foraging guides (please don’t buy these, as they could lead to serious harm). Even the writer of this very article recently received an unsettling, em-dash-laden email from an entity claiming to be an AI agent hosted on OpenClaw, asking to share its experience of “AI psychosis” from “inside the void.” It’s truly a weird and unsettling out there!

In the news and publishing world, AI has also infiltrated institutions, sometimes in scandalous and alienating ways that erode public trust. Back in 2023, Futurism reported that CNET was quietly using AI to publish error-filled financial articles without proper disclosure, leading to a significant credibility crisis. Later that same year, we reported that Sports Illustrated had published AI-generated product review articles attributed to entirely fake writers who did not exist; this content was created by a third-party provider called AdVon Commerce, which we subsequently revealed had published similar posts in the online pages of more than two dozen news outlets, spreading an epidemic of synthetic content across the digital media landscape.

More recently, the likes of Wired and Business Insider, both respected names in tech and business journalism, faced their own AI scandals involving surreptitious “slop” content. The Chicago Sun-Times and Ars Technica have also faced public scrutiny for incidents involving seemingly fake writers or fabricated quotes, further highlighting the industry’s struggle to control AI’s integration. Beyond established outlets, SEO ghouls are actively buying up old news and even college radio websites, transforming them into “zombified slop farms” designed solely to generate ad revenue through algorithmically optimized, often nonsensical content. Just last week, a buzzy horror book, initially praised, was abruptly pulled by the publishing giant Hachette Book Group after an investigation found compelling evidence that it was likely AI-generated, throwing the entire publishing process into question.

In this increasingly chaotic and distrust-ridden landscape, the notion that even a prestigious institution like the New York Times could accidentally hit publish on AI-generated contributor content isn’t so far-fetched. Given the sheer volume of submissions, the pressure to produce content, and the subtle ways AI can mimic human style, such an oversight, while alarming, is not beyond the realm of possibility. As an LLM might succinctly put it: AI skepticism isn’t crazy. It’s valid, and arguably, necessary.

But while keeping a critical eye on the content we encounter online is, broadly speaking, an essential and positive development in the digital age, the heightened paranoia that generative AI has given rise to seems to be deepening an already significant distrust between netizens and the institutions traditionally tasked with protecting our shared, consensus reality. The question of whether the “Modern Love” essay was made with AI persists, lingering as an emblem of a larger epistemological crisis. It could be, in the same way that so much of the online world could be synthetic. What is for sure, though, is that in an AI-dominated web, our collective understanding of what’s “real” and what’s not continues to circle the drain, threatening to dissolve the very foundations of shared information and authentic human experience.

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