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- Title
Perceptions of Artificial Intelligence and ChatGPT by Speech-Language Pathologists and Students.
- Authors
Austin, Julianna; Benas, Keith; Caicedo, Sara; Imiolek, Emily; Piekutowski, Anna; Ghanim, Iyad
- Abstract
Purpose: This project explores the perceived implications of artificial intelligence (AI) tools and generative language tools, like ChatGPT, on practice in speechlanguage pathology. Method: A total of 107 clinician (n = 60) and student (n = 47) participants completed an 87-item survey that included Likert-style questions and open-ended qualitative responses. The survey explored participants' current frequency of use, experience with AI tools, ethical concerns, and concern with replacing clinicians, as well as likelihood to use in particular professional and clinical areas. Results were analyzed in the context of qualitative responses to typed-response open-ended questions. Results: A series of analyses indicated participants are somewhat knowledgeable and experienced with GPT software and other AI tools. Despite a positive outlook and the belief that AI tools are helpful for practice, programs like ChatGPT and other AI tools are infrequently used by speech-language pathologists and students for clinical purposes, mostly restricted to administrative tasks. Conclusion: While impressions of GPT and other AI tools cite the beneficial ways that AI tools can enhance a clinician's workloads, participants indicate a hesitancy to use AI tools and call for institutional guidelines and training for its adoption.
- Subjects
SPEECH therapists; GENERATIVE artificial intelligence; SCALE analysis (Psychology); CRONBACH'S alpha; DATA analysis; HEALTH occupations students; GRADUATE students; DESCRIPTIVE statistics; ATTITUDES of medical personnel; SPEECH-language pathology assistants; STATISTICS; ONE-way analysis of variance; STUDENT attitudes; SPEECH therapy; PSYCHOSOCIAL factors
- Publication
American Journal of Speech-Language Pathology, 2025, Vol 34, Issue 1, p174
- ISSN
1058-0360
- Publication type
Academic Journal
- DOI
10.1044/2024_AJSLP-24-00218