Equipping Speech-Language Clinicians for the Critical Appraisal of an Artificial Intelligence--Driven, Evidence-Based Future.

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Bibliographic Details
Title: Equipping Speech-Language Clinicians for the Critical Appraisal of an Artificial Intelligence--Driven, Evidence-Based Future.
Authors: Benway, Nina R.1 benway@umd.edu, Preston, Jonathan L.2
Source: Language, Speech & Hearing Services in Schools. Jul2025, Vol. 56 Issue 3, p442-468. 27p.
Subject Terms: *Artificial intelligence, *Professional employee training, *Machine learning, *Automation, *Speech therapy, *Algorithms, Automatic speech recognition, Medical protocols, Data security, Digital technology, Medical care use, Professional practice, Organizational ethics, Research evaluation, Conceptual structures, Evidence-based medicine, Sensitivity & specificity (Statistics)
Abstract: Purpose: Artificial intelligence (AI) is more capable and accessible than ever before. But what does this mean for clinical practice? How can speechlanguage clinicians evaluate the efficacy, validity, and reliability of AI and machine learning tools for automating assessment and treatment? How can speech-language clinicians ethically use these clinical AI technologies? We contend that clinical AI will best serve clinicians and clients when aligned with an evidence-based framework. Therefore, this tutorial presents guidelines for the critical appraisal of clinical AI through the lens of validity, reliability, ethical use, and equitable use, facilitated by the Critical Appraisal Rubric for Ethical and Equitable Clinical Artificial Intelligence. Similarly, in order for developers of clinical AI to meet the needs of the profession, these principles should guide the development and assessment of new clinical technologies. Conclusions: The questions of efficacy, validity, reliability, ethical use, and equitable use of clinical AI can be answered through the examination of a specific clinical AI for a given user, as emphasized by culturally responsive professional practice. A framework is provided to assist clinicians in the critical appraisal of clinical AI tools. [ABSTRACT FROM AUTHOR]
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Database: Education Research Complete
Description
Abstract:Purpose: Artificial intelligence (AI) is more capable and accessible than ever before. But what does this mean for clinical practice? How can speechlanguage clinicians evaluate the efficacy, validity, and reliability of AI and machine learning tools for automating assessment and treatment? How can speech-language clinicians ethically use these clinical AI technologies? We contend that clinical AI will best serve clinicians and clients when aligned with an evidence-based framework. Therefore, this tutorial presents guidelines for the critical appraisal of clinical AI through the lens of validity, reliability, ethical use, and equitable use, facilitated by the Critical Appraisal Rubric for Ethical and Equitable Clinical Artificial Intelligence. Similarly, in order for developers of clinical AI to meet the needs of the profession, these principles should guide the development and assessment of new clinical technologies. Conclusions: The questions of efficacy, validity, reliability, ethical use, and equitable use of clinical AI can be answered through the examination of a specific clinical AI for a given user, as emphasized by culturally responsive professional practice. A framework is provided to assist clinicians in the critical appraisal of clinical AI tools. [ABSTRACT FROM AUTHOR]
ISSN:01611461
DOI:10.1044/2025_LSHSS-24-00085