The concern emerges against a backdrop of rapid institutional response to generative AI. As large language models have become widely available, many journals, universities, and professional bodies have adopted policies that limit or restrict the use of AI in academic writing. Enforcement of these policies has leaned heavily on AI detection software, tools that attempt to distinguish machine-generated prose from human writing by analyzing stylistic patterns, vocabulary choices, and overall cadence. The problem, as Smith and Aggarwal emphasize, is that these tools are far from infallible. Citing recent research, they note that even automated detectors do not achieve perfect accuracy, and that human readers perform considerably worse. One study found that people cannot identify AI-generated writing any more reliably than random chance would allow.

Despite these limitations, anxiety about being accused of using AI is demonstrably shaping how authors write. The em dash has been singled out in public discourse, including commentary in major newspapers, as a marker of perceived overuse by AI tools. Yet the authors point out that peer-reviewed studies establishing a genuine association between the punctuation mark and machine generation are lacking. The association is largely a matter of perception, amplified by social media conversation and anecdote rather than systematic evidence. Still, perception can be powerful. Because the em dash may now carry a negative connotation, authors who wish to avoid evoking skepticism from reviewers and editors may simply stop using it.

The pressure is not hypothetical. In preparing a prior manuscript, one of the authors was advised by a mentor that the use of em dashes might be interpreted by reviewers as a sign of AI involvement. Both authors report hearing similar accounts from colleagues across academic medicine. These anecdotes suggest that a quiet recalibration of writing style is already underway, driven not by journal policy or formal guidance but by fear of suspicion. The authors argue that trainees and early-career academics, who are still developing their scholarly voices, may be particularly vulnerable to these pressures, internalizing the idea that certain stylistic choices are risky before they have had the chance to make those choices their own.

What is at stake, the correspondence contends, extends well beyond a preference for one punctuation mark over another. Writing, like other forms of art, is a medium through which individuals express personality, share perspective, and communicate thought. Stylistic signatures, including rhythm, cadence, and punctuation habits, are part of what makes an author’s voice recognizable. By unnecessarily restricting these elements, the academic community risks constricting what scholars are able to say and how they are able to connect with readers. The authors suggest this may be particularly damaging in fields such as psychiatry, where narrative skill and clarity of expression are not decorative extras but essential professional tools, central to both clinical communication and scholarship.

The technical reality of AI detection undercuts the logic of policing individual stylistic features. As Smith and Aggarwal observe, even automated detection software does not rely on any single tell in isolation. Instead, such systems perform a holistic analysis of a piece of writing, weighing overall style, paragraph length, grammatical choices, and vocabulary together before rendering a judgment. If the most sophisticated detectors require whole-text analysis to reach conclusions of imperfect reliability, then treating a lone punctuation mark as evidence of machine authorship is analytically indefensible. Overemphasis on a single element, such as punctuation considered in isolation, raises the very real potential for false accusations against human authors whose only offense is a fondness for the em dash.

The authors’ proposed alternative is straightforward: rather than asking authors to change how they write, the field should emphasize and demand transparency about AI use. This means clear authorship guidelines and explicit journal policies governing the use of generative AI, together with education for scholars on the importance of disclosure. Transparency, in this framing, addresses the actual problem, which is undisclosed machine assistance, rather than punishing stylistic expression that happens to overlap with the output of language models. The approach aligns with emerging guidance in medical education publishing, including recent international guidance on when and how to disclose AI use in academic publishing.

At the same time, the correspondence does not dismiss the need for safeguards. Smith and Aggarwal acknowledge that protections surrounding AI use are vitally necessary to prevent the field from becoming over-reliant on technology, with the risks to originality, accountability, and scientific integrity that such reliance would entail. Their argument is one of proportion: safeguards should target disclosure and integrity, not the erosion of individual voice. The distinction matters because style-based policing is both ineffective, given the weakness of the evidence linking any single feature to AI, and corrosive, given that it teaches a generation of writers to flatten their prose into something inoffensive and anonymous.

The em dash controversy is a small episode with outsized symbolic weight. It captures a moment in which institutions, reviewers, and writers themselves are groping toward norms for a technology that arrived faster than the rules governing it. The message from these psychiatry educators is a caution against premature judgment: with imperfect detection software, even less accurate human judgment, and only a weak and largely anecdotal association between a punctuation mark and machine text, the field should not allow a perceived association to change how people write. How we communicate, they argue, is too important to be dictated by suspicion of a dash.

Subject of Research: The impact of perceived AI-associated writing styles on academic authorship and publishing

Article Title: The Em Dash—Should We Allow AI to Change Our Writing Styles?

Article References: Smith, A. C., & Aggarwal, R. (2026). The Em Dash—Should We Allow AI to Change Our Writing Styles?. Academic Psychiatry. https://doi.org/10.1007/s40596-026-02435-4

Image Credits: AI Generated

DOI: 10.1007/s40596-026-02435-4

Keywords: em dash, artificial intelligence, academic writing, AI detection, writing style, academic publishing, authorship, transparency, psychiatry education, generative AI, scholarly voice, peer review