The rapid adoption of artificial intelligence (AI) tools is shaking the foundations of industries that rely heavily on authenticity and precision. From unpublished manuscripts to courtroom citations, AI is complicating traditional workflows, leading to serious questions about trust and ethical standards.

The Publishing Controversy

One of the most striking examples of AI creating trust issues comes from the literary world. A major American publisher, Hachette Book Group, recently canceled plans to release Shy Girl, a much-anticipated horror novel by indie author Mia Ballard, following allegations that portions of the book were AI-generated. Originally self-published, the novel gained viral attention through TikTok's BookTok community, which praised its pacing and engaging writing.

After acquiring the publishing rights to Shy Girl, Hachette released copies in the UK, receiving positive initial reception. However, critics began to notice odd linguistic choices, repetitive phrasing, and unusually constructed similes that raised suspicions. These hallmarks are often associated with AI-generated text, prompting scrutiny.

According to an NBC News report, Hachette later pulled the book from UK shelves and dropped plans to publish it in the U.S. The company stated its commitment to protecting original creative expression and storytelling. Ballard denied personally using AI to craft the novel and attributed the use of AI to an acquaintance she hired as an editor for the self-published version.

Publishing industry expert Jane Friedman expressed concerns about what this case means for the sector. “If the books that make it to market show insufficient diligence during the editorial process, readers may grow cynical toward what they find in bookstores,” she warned. This sentiment highlights the precarious position publishers now find themselves in, as AI blurs the line between human creativity and automated generation.

AI’s Impact in Legal Practice

The challenge AI presents is not confined to literature. In the legal field, instances of lawyers using AI tools for research have resulted in "hallucinations"—a term describing AI-generated false information that appears credible on the surface.

A notable case unfolded in Georgia, where a Supreme Court judge confronted state prosecutor Deborah Leslie regarding fabricated case citations in her court brief. The judge pointed to several non-existent case references and others that were misapplied. While Leslie neither admitted to nor was directly accused of using AI, the incident prompted her office to investigate whether these errors stemmed from reliance on generative AI.

Legal researcher Damien Charlatan has been documenting such occurrences in what he calls "legal hallucinations." In 2024, his database recorded 35 cases in which fabricated citations appeared in U.S. court documents. That number grew exponentially to 489 in 2025, with more than 250 incidents already reported this year. Charlatan notes that many fabricated citations go undetected unless flagged during the judicial process, posing serious risks for the legal system's integrity.

The situation underscores a growing uneasiness about how legal tools based on generative AI can distort or undermine the adversarial process in courtrooms. One concern is that AI tools, designed to mimic authority, might concoct case law in their effort to "satisfy" user queries, particularly under vague instructions.

The Core Problem: Trust and Oversight

The issues arising in both publishing and law point to an underlying challenge: AI’s ability to produce plausible but inaccurate content. In both industries, stakeholders are questioning how such technologies have bypassed traditional vetting processes and who ultimately bears responsibility for errors.

In publishing, the advent of AI-mediated editing has shaved time off the editorial process for self-published works, accelerating their path to traditional markets. Yet, as the Shy Girl controversy demonstrates, this lack of thorough review can result in reputational damage not just for authors but also for publishers. Readers may lose faith in the quality and originality of what they purchase if they sense that AI is producing subpar material.

In the legal field, the stakes are even higher. A mistaken citation of non-existent case law can lead to judicial consequences well beyond a lawyer’s reputation. Charlatan warns that unchecked reliance on AI "could distort the foundation of legal systems," particularly if mistakes are only caught after major rulings are made or precedents set.

Where Do Industries Go from Here?

Addressing these emerging trust issues requires stronger organizational safeguards and public accountability. For publishers, that might mean stricter assessments of manuscripts for signs of AI influence or outright banning AI-crafted content in books marketed as human-authored. Similarly, the legal industry may need to implement ethical guidelines specifically tailored to the use of AI tools, ensuring automated legal research remains supplementary rather than primary.

Friedman identifies a broader concern. "Traditional gatekeeping roles," she argues, "are eroding." If industries fail to adapt quickly, they risk alienating their core audiences. Legal practitioners who misuse AI and publishers who approve suspicious texts could see long-term harm to their brands.

The Broader AI Context

Some hail AI as a revolutionary tool that will streamline processes, reduce costs, and boost efficiency across sectors. But these cases highlight how little the technology’s creators and adopters understand its unintended consequences. Many experts emphasize that investments in AI must be matched by robust safeguards. This means training users on the limits of AI, establishing verification checks, and maintaining transparency around the use of automated systems. Without such measures, the risks to trust—and the industries themselves—will only compound.

As industries like publishing and law work to recalibrate, the fundamental question remains: how can AI be used responsibly while preserving authenticity, credibility, and trust in the very systems it touches?