Artificial intelligence has become a societal disruptor. Generative AI tools like ChatGPT have reached across society, giving everyone with a smartphone the opportunity to interact with AI in new ways. With such capabilities now in the mainstream, though, the tasks that AI systems can deliver means that the list of jobs at risk for elimination is long and growing. AI systems are poised to transform and subsume jobs that involve repetitive tasks that can be learned.

Here is a list of four such tasks that place their associated jobs at risk.

Translation: When people from different countries interact, language can be a barrier. Many countries around the world teach English as a second language, but when groups with different languages must interact, speaking in your native voice is nearly always preferred. AI systems like Google Translate and DeepL seamlessly provide real-time translation between a multitude of languages. This facilitates more fluid communication, effectively widening the footprint for global economics and education.

While most human translators have a limited set of languages that they can translate from and into, AI translator systems can work across as many as 200 languages, providing an efficient vehicle to bridge people and eliminate language barriers.

Courtroom recording: Every courtrooms has a person busily typing on what looks like a miniature typewriter. They are responsible for recording every word spoken during the proceeding. Their skills are immense, given the speed at which they must work and the accuracy demanded of them. An AI system can be designed to record the information being discussed and communicated during such proceedings. Court reporter roles are likely to be transformed by AI, with a new generation of court reporters used to vet and ensure the integrity of the court proceedings produced by AI systems. Because multiple AI systems can simultaneously transcribe court proceedings, such duplication can cost-effectively provide the necessary accuracy demanded by the legal system.

Copy editing: Newspapers and publishers use copy editors to edit articles and books. AI systems are well-suited for this task; learning grammar and tapping into a nearly unlimited number of words allows AI systems to polish the roughest first drafts of any manuscript. Moreover, revisions by AI could be be done nearly instantaneously. Every newspaper and publisher can benefit from such a product. Instead of having a group of copy editors on staff, a single IT person can manage the flow of manuscripts being edited by AI systems.

Legal support: Every law firm uses junior lawyers, often directly out of law school, to do numerous tasks, including case research, preparing briefings and supporting expert witness declarations. Because the format and style of many of the resulting documents are similar, AI systems are well suited to create them. This would reduce the number of junior lawyers required to handle cases, and thus the cost of legal services for clients. It would also create a new breed of paralegals, with significant IT skills to oversee AI systems that produce all such documents.

Before permitting AI systems to generate pink slips for these workers, though, one must look at the entire gestalt of their jobs.

Translator and court reporter tasks can certainly be done by AI systems, significantly reducing the number of people in these jobs and saving organizations both time and money. Yet the human element of capturing how people interact would be missed by such a system; the same words when spoken together can mean different things, for example, based on the tone or context in which it is spoken. This is certain to create misunderstandings.

Some of the jobs at risk of elimination also provide training, serving as stepping stones for higher positions that could not be replaced by AI systems. Editors and managing editors may begin their careers as copy editors. The same holds true with lawyers, who must go through perfunctory roles as junior lawyers before assuming the responsibilities of overseeing large and complex cases.

AI systems will continue to push into new domains and transform how work is executed. Much like when U.S. companies move their manufacturing operations overseas to take advantage of lower labor costs, replacing people by AI systems can also save money. However, the price paid for indiscriminately reducing workforces to save money will have unintended downstream consequences.

Instead of fearing what AI will take away, embrace the new opportunities that AI will provide. Training people to be part of AI systems has already become a growth industry. The challenge is how to include a larger footprint of the workforce and give them the skills to be part of this burgeoning new economy.

Change is never easy. With each new job impacted by AI systems, new opportunities are certain to emerge. But simply replacing people with AI systems to save money today will create human capital talent voids in the future that AI systems may be unable to fill. Indeed, a penny saved by AI today may end up costing many dollars in lost human capital talent in the future.

____

Sheldon H. Jacobson, Ph.D., is a professor of computer science in the Grainger College of Engineering at the University of Illinois Urbana-Champaign. He has researched risk-based aviation security for over 25 years, which provided the technical justification for TSA PreCheck. This piece was originally published by The Hill.

____

©2025 Tribune Content Agency, LLC.