
The question appeared on LinkedIn with a familiar undertone of frustration.
“How did you address the elephant in our space—AI? I know human captioners are 100 percent better, but selling that idea to some groups is difficult.”
It is a fair question, and one that professionals across court reporting, captioning, and legal transcription are now being asked with increasing frequency. It is also a question framed in a way that almost guarantees the wrong answer.
For several years, skilled human professionals have been placed in a defensive position, asked to justify their continued relevance in the face of rapid advances in artificial intelligence. The implicit challenge is often the same: prove that humans are better than machines, or accept that automation is inevitable.
But that framing misunderstands how decisions are actually made in regulated environments. And it misidentifies what is truly at issue.
This moment is not about whether artificial intelligence is impressive. It is about risk, accountability, and responsibility for the record.
The Problem With “Selling” Human Superiority
Assertions that “humans are better” may feel intuitively true to those who work daily with language, nuance, and accuracy. But in professional settings—particularly legal and governmental ones—absolutist claims are rarely persuasive.
They invite rebuttal. They trigger debates over metrics and edge cases. They shift attention away from the practical concerns that matter most to decision-makers.
More importantly, they frame the discussion as a competition between humans and technology, when that is not how institutions actually evaluate tools.
Judges, attorneys, and administrators do not ask whether a technology is impressive. They ask what happens when it fails.
A Different Way to Frame the Conversation
The most effective response to the LinkedIn question did not attempt to prove human superiority. Instead, it reframed the issue entirely.
“I don’t try to sell the idea that humans are better in the abstract,” the response explained. “I frame it around use-case and risk.”
That distinction is subtle, but critical.
Artificial intelligence can be useful in many contexts. It can provide rough reference text, assist with post-event review, or support accessibility overlays. In informal or low-risk settings, it may offer meaningful efficiencies.
But when the record carries legal, financial, or reputational consequences, the calculus changes.
At that point, the relevant question is not whether the technology is innovative. It is who is responsible for the output.
Accountability, Not Accuracy, Is the Real Issue
Accuracy matters, but accuracy alone is not what gives a record its authority.
Certified court reporters and professional captioners operate within a framework of accountability. They are trained to recognize ambiguity, resolve conflicts in speech, and preserve context. They certify their work. They correct errors. They are subject to professional discipline. They can be questioned, audited, and, if necessary, sanctioned.
Automated systems do none of these things.
Artificial intelligence does not hold a license. It does not swear an oath. It does not carry professional insurance. It does not appear in court to explain why a particular word choice was made or why a speaker was attributed incorrectly.
When AI systems fail—as all systems eventually do—responsibility becomes diffuse. Vendors disclaim liability. Errors are described as “limitations.” The burden shifts quietly to the end user, who is left to absorb the consequences.
That is not a technological flaw. It is a structural one.
Why This Matters More Than Innovation
In regulated environments, structure matters more than novelty.
Courts, agencies, and law firms operate within systems designed to allocate responsibility clearly. The integrity of the record depends not just on how it is produced, but on who stands behind it.
This is why the debate shifts so quickly once accountability enters the conversation. When decision-makers realize that adopting automation may also mean assuming new and undefined risks, enthusiasm often gives way to caution.
The issue stops being humans versus AI and becomes something far more practical: appropriate tool versus inappropriate substitution.
The Parallel Attorneys Instinctively Understand
For lawyers, this distinction is already familiar.
Attorneys rely heavily on technology. They use research platforms, document automation, analytics, and increasingly, AI-assisted drafting tools. But they do not outsource responsibility to software.
When a brief contains an error, the attorney signs it anyway. When a filing is defective, the attorney answers for it. Technology assists the work, but the professional remains accountable.
The same principle applies to the creation of the record.
An AI system may generate text, but it cannot certify it. It cannot contextualize it. It cannot be cross-examined. And it cannot bear the consequences when that text is relied upon in litigation.
Once that parallel is drawn, the conversation becomes far less abstract—and far more persuasive.
Accessibility Should Not Mean “Good Enough”
One of the more troubling aspects of the AI debate is the way accessibility is sometimes invoked as justification for automation without adequate scrutiny.
Artificial intelligence is often promoted as “good enough” for accessibility needs, even though error rates disproportionately affect speakers with accents, technical vocabulary, overlapping speech, or non-standard cadence.
Human professionals do not eliminate these challenges. But they can recognize them, correct them, and explain them. More importantly, they can be held accountable for doing so.
Accessibility should not mean the lowest-cost approximation of access. It should mean reliable access to information that people can trust.
That requires standards. Standards require accountability. And accountability requires humans.
The Market Is Already Adjusting
Despite the intensity of the public debate, there are signs that institutions are beginning to recalibrate.
Courts are issuing guidance. Agencies are revisiting policies. Attorneys are asking more pointed questions about admissibility, consent, data retention, and error correction. Even technology vendors are quietly adding disclaimers that acknowledge what earlier marketing materials did not.
This is how automation waves historically mature—not through wholesale rejection, but through constraint and clarification.
The professions that endure are those that stop resisting the existence of technology and start articulating where it does not belong.
A Better Answer to the AI Question
So how should professionals respond when asked how to “sell” the value of humans in an AI-driven world?
They should not sell superiority. They should explain responsibility.
They should acknowledge that AI is a powerful tool with legitimate uses. And then they should draw a clear line: when accuracy, context, and accountability matter, decision-makers still need a professional who can stand behind the record.
That is not fear of innovation. It is an understanding of risk.
And in law, risk—not hype—is what ultimately governs decisions.
The real elephant in the room is not artificial intelligence. It is the assumption that automation can replace responsibility.
Once that assumption is challenged, the conversation becomes far clearer—for everyone involved.
Disclosure
This article reflects the author’s professional analysis and opinion based on industry experience. It is not legal advice, does not reference confidential matters, and does not allege wrongdoing by any specific company or technology provider. References to AI and automation are general and intended to discuss risk, accountability, and appropriate use in regulated settings.