The federal judiciary is contemplating something it has never done before: writing a nationwide rule to regulate the introduction of artificial intelligence–generated evidence at trial. Earlier this month, the U.S. Judicial Conference’s Advisory Committee on Evidence Rules held a public hearing on a proposal that would subject certain forms of machine-generated evidence to the same reliability standards that govern expert witnesses under Rule 702 of the Federal Rules of Evidence. Under the draft, if a party seeks to introduce AI-generated or other machine-produced evidence without a sponsoring expert, the court would be required to scrutinize the reliability of the system itself. The proposal would exempt “basic scientific instruments,” but its clear target is the expanding use of opaque, algorithmic tools in litigation. Though framed as a response to emerging technologies, the rule carries a deeper implication: the federal courts are formally acknowledging that machine output is not neutral, not self-authenticating, and not inherently trustworthy.
At first glance, the proposal appears to be about courtroom exhibits of the future: algorithmic reconstructions, automated pattern analysis, AI-generated images, and machine-produced reports. But beneath the surface, it touches a far older question—what it means for a court record to be reliable. For more than a century, the American legal system has relied on a simple premise: when the official record of a proceeding is created by a sworn, licensed officer of the court, its reliability is built into the process itself. The transcript is not treated as a technological artifact but as a human-governed legal document. Its authority flows from the person who created it, not from the device used to capture it. By proposing a new rule that treats certain machine outputs as functional equivalents of expert testimony, the judiciary is drawing a line between records created under human accountability and outputs generated by autonomous systems.
That distinction matters profoundly for court reporting. A certified stenographic transcript has never been forced through the evidentiary gauntlet reserved for expert opinions. It is not admitted because a judge conducts a Daubert analysis of a machine, but because a licensed reporter was present, sworn, and responsible for producing a verbatim record. The safeguards are structural and front-loaded: licensing, ethics codes, statutory duties, professional discipline, and the real-time human act of hearing, interpreting, and recording speech. The reporter is not offering an opinion; the reporter is creating the record. The equipment is merely an instrument, subordinate to a human who can be examined, questioned, sanctioned, and held accountable. This is why, historically, courts have not asked whether a transcript is reliable in the abstract; they have asked whether it was produced by a duly authorized court reporter.
The proposed AI evidence rule implicitly affirms this architecture by contrast. Its premise is that when evidence is produced by a machine operating without a human expert, the court must step in as a gatekeeper. The system itself becomes the witness. Judges would be asked to evaluate methodology, error rates, validation processes, and technical assumptions that no juror can independently observe. The machine’s output would not be treated as a neutral fact but as a claim requiring proof. This is a quiet but consequential shift, because it recognizes that algorithmic systems introduce a new kind of evidentiary risk: they perform cognitive functions—recognition, classification, synthesis—that were once the exclusive domain of human actors. When those functions are outsourced to software, the traditional mechanisms of cross-examination and observation break down.
Court reporting exists precisely to prevent that breakdown at the foundation of the justice system. A stenographic reporter does not merely capture sound. The reporter performs continuous human judgment: distinguishing speakers, resolving ambiguities, flagging inaudibles, managing interruptions, and ensuring that what is preserved reflects what occurred in the room. That process is observable, interruptible, and governed by professional standards. If a dispute arises, the reporter can be questioned about the circumstances of the record’s creation. The source of the record is not a vendor’s proprietary model but a person who took an oath. The transcript is therefore not “machine-generated evidence” in the sense contemplated by the proposed rule; it is a human-generated legal record produced with the assistance of tools.
By contrast, automated speech recognition systems and AI-driven courtroom recording platforms collapse this distinction. They produce outputs that appear textual and authoritative but are, in fact, algorithmic interpretations of audio. Their errors are not merely typographical; they are epistemic. They substitute statistical inference for human perception, often without leaving a transparent, inspectable trail of how a particular word, speaker attribution, or phrase was determined. When they fail, the fallback is frequently a return to raw audio, not to a contemporaneous human record. In evidentiary terms, this means the “transcript” becomes a derivative product of a proprietary system. Under the logic now being articulated by the federal judiciary, such an output begins to resemble expert evidence: dependent on methodology, subject to validation, and contestable at the level of process rather than mere accuracy.
The proposed rule thus exposes an uncomfortable tension in the current push toward digital and AI-assisted courtrooms. If a machine-produced output requires Rule 702-level scrutiny to be admitted as evidence, how can an AI-generated “record” function as the unquestioned backbone of appellate review? Trial transcripts are not peripheral exhibits; they are the substrate of due process. They determine what arguments can be raised, what errors can be claimed, and what facts are preserved for history. Introducing a record that, by the judiciary’s own emerging logic, belongs in the category of machine-generated evidence would invite a level of foundational litigation incompatible with the role the record must play. Every proceeding would carry the latent risk of becoming a technical hearing on the reliability of the recording system itself.
This is not a hypothetical concern. The very reasons the Advisory Committee is considering a new rule—opacity, rapid evolution, vendor control, and methodological uncertainty—are present in many automated transcription systems already being deployed in legal settings. These systems are trained on massive datasets, updated without courtroom oversight, and governed by corporate decisions invisible to litigants. Their outputs cannot be meaningfully cross-examined without expert testimony, discovery into proprietary processes, and an understanding of machine learning that few courts possess. If such outputs are to be treated honestly, they fall squarely within the domain the proposed rule seeks to regulate. They are not neutral instruments; they are algorithmic actors.
Seen in this light, the judiciary’s move is less an embrace of AI than an institutional caution. By insisting that machine-generated evidence be subjected to the same reliability standards as expert witnesses, the courts are reaffirming a foundational principle: evidence must be anchored in accountable human processes. That principle has long been embodied in the court reporting profession. The stenographic reporter is a living chain of custody, a real-time auditor of the proceeding, and a point of legal responsibility. The reliability of the transcript is not an after-the-fact question but a condition of its creation. The proposed rule does not diminish that model; it underscores why it has endured.
The broader implication is that the debate over AI in the courtroom is not merely about efficiency or modernization. It is about whether the justice system will continue to insist on human governance at the point where reality is converted into record. The Advisory Committee’s proposal suggests that, at least for now, the federal judiciary recognizes the danger of allowing machines to occupy that role unexamined. In doing so, it inadvertently casts the court reporter not as a legacy feature, but as a structural safeguard—one that keeps the official record out of the evidentiary category now being carved out for AI. As courts navigate the future, the question will not only be what technology can do, but what functions must remain, in the deepest sense, human.
Disclaimer
This article is for general informational and educational purposes only and does not constitute legal advice. It reflects analysis and commentary on public developments concerning evidence rules and courtroom technology. Readers should consult qualified legal counsel regarding the application of any laws, rules, or proposals discussed herein to specific circumstances.
STENOIMPERIUM 
I appreciate your line of reasoning… The authority of the certified record flows from the person who created it, not from the device used to capture it.
Yes… the record actually does come through the person who created it, through several parts of the human mind, and is then output by and through the human body and mind, and the information gone through again by a human mind, utilizing (under the circumstances of a record created via hand/stenographic methods of data entry) a lifetime of skill and experience of a highly-trained and well-seasoned professional certified shorthand reporter. Every piece of information passes through a human mind and also human hands. So in the scenario of calling a record “certified” or “uncertified,” who is the one verifying the thing behind the thing?, I feel is your point. As in the instance of something as apparently benign as an audio digital recording of courtroom proceedings whose audio is captured by an audio recording digital device operated or run by a human employed by the court and then later transcribed into a “certified” record by someone else who cannot personally verify the integrity and/or the chain of custody of the digital audio recording of courtroom proceedings that is now being transcribed as a “certified” record, I ask the following…. Was there a second operator present while the digital recorder captured the audio of the courtroom proceedings, and then listening to the captured audio of courtroom proceedings at a slight delay from the source recording that was captured by the courthouse employee that operates and runs the digital recording device, to ensure every word and sound has been verified as preserved, accurate and reliably heard and understood from this quality control process (equaling two employees, at this point, not one court reporter)? Answer: no. But as a certified shorthand reporter, every aspect of the process is verified emotionally, physically, intellectually and visually, as these professionals use all of their senses and physical skillsets and are, thankfully, human beings possessing and utilizing these capabilities. “When they fail, the fallback is frequently a return to raw audio, not to a contemporaneous human record.” “The reliability of the transcript is not an after-the-fact question but a condition of its creation. The proposed rule does not diminish that model; it underscores why it has endured.” This is by and large an overlooked aspect of why the Scribe exists in the first place, dating back to the most ancient times. Certified shorthand reporters advocate for the due process and respect the record, a record that by just by its own existent nature itself deserves. This is an integral aspect of our job responsibilities, that we’re not afraid or shrink from having what some may deem as a “difficult conversation.” It’s not difficult at all for certified shorthand reporters — it’s what we signed up for — to protect the record as a public servant, a Guardian of the Record.
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