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Equipping Speech-Language Clinicians for the Critical Appraisal of an Artificial Intelligence-Driven, Evidence-Based
Nina R Benway1, Jonathan L Preston2
1Department of Electrical and Computer Engineering, University of Maryland, College Park.
Purpose:
Artificial intelligence (AI) is more capable and accessible than ever before. But what does this mean for clinical practice? How can speech-language 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.
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