A University of Cincinnati study led by associate professor Nelly Elsayed examined the reliability of AI speech-to-text tools in clinical settings, prompted by a fictional scenario on the medical drama “The Pitt” where a tool misheard a patient’s medication name. Elsayed’s paper, “Socio-technical risks of clinical speech-to-text systems: Transparency, privacy, and reliability challenges in AI-driven documentation,” published in the International Journal of Medical Informatics, analyzed existing research, ethical guidelines and government regulations to assess how AI adoption is outpacing oversight. The study identified five key risks: inconsistent disclosure and consent practices; decreased performance for accented and disordered speech; extraneous noises at clinical facilities lowering the accuracy of AI; lack of human review over AI-generated text leading to unchecked mistakes; and unclear accountability for errors. Elsayed emphasized that having a human review data before it is finalized can reduce concerns, stating, “We need to have a human in the loop to check whether the text is exactly what has been spoken... for the entire text, not just for the first couple statements.”