Court Reporters and Simultaneous Captioners

Use verbatim methods and equipment to capture, store, retrieve, and transcribe pretrial and trial proceedings or other information. Includes stenocaptioners who operate computerized stenographic captioning equipment to provide captions of live or prerecorded broadcasts for hearing-impaired viewers.

The occupation "Court Reporters and Simultaneous Captioners" faces a relatively high automation risk of 79.8%. This figure is just slightly below the base risk of 80.4%, indicating that much of the work in this field is susceptible to automation. The core reason is that many tasks are routine, repetitive, and technology-friendly, making them ideal candidates for advancements in speech recognition and transcription software. Modern AI systems can now transcribe spoken words with impressive speed and accuracy, reducing the need for manual verbatim recording. As this technology continues to improve and costs decline, automation is becoming more feasible for many organizations seeking efficiency and cost savings. The most automatable tasks for this profession underscore this trend. Tasks such as "record verbatim proceedings of courts, legislative assemblies, committee meetings, and other proceedings, using computerized recording equipment, electronic stenograph machines, or stenomasks" can readily be performed by advanced transcription software. Similarly, "proofreading transcripts for correct spelling of words" is highly susceptible to automation using natural language processing tools. Even the process of asking speakers to clarify inaudible statements may soon be addressed by adaptive AI that can prompt for clarification or use enhanced audio restoration algorithms. As a result, the majority of this occupation’s workload may soon be streamlined through emerging technologies. However, there are some inherent bottlenecks that provide resistance against full automation. The most resistant tasks—such as recording depositions and other proceedings for attorneys, typing court orders for judges, and taking shorthand notes—often require a nuanced understanding, quick decision-making, and a degree of real-time adaptability not yet matched by AI. The bottleneck skill of originality, though measured at low levels (1.9% and 1.1%), still poses a challenge for automation, as handling unpredictable or sensitive human interactions calls for contextual judgment. These human-centric functions, particularly in legal environments where precision and confidentiality are critical, ensure that some elements of the occupation remain resistant to complete automation for the foreseeable future.