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An AI Tutorial for Speech and Language Therapists: Translating Concepts From the AI Literature Into Accessible
Ana Oliveira-Buckley1, Barry O'Sullivan2, Cristina McKean3
1Department of Speech and Hearing Sciences, University College Cork, Cork, Ireland.
This tutorial explains Artificial Intelligence (AI) for speech and language therapists (SLTs), demystifying AI techniques, capabilities, and applications in clinical practice. It promotes ethical AI use to support, not replace, SLTs.
Area of Science:
- Speech and Language Therapy (SLT)
- Artificial Intelligence (AI)
Background:
- Clinical adoption of AI in SLT is hindered by low AI literacy among clinicians.
- AI terminology is often abstract and difficult for non-technical healthcare professionals to understand.
Purpose of the Study:
- To provide foundational AI knowledge tailored for SLTs.
- To organize AI concepts into techniques, capabilities, and clinical applications.
- To facilitate the understanding and adoption of AI in SLT practice.
Main Methods:
- Synthesizing foundational AI literature, taxonomies, and SLT research.
- Utilizing clinical analogies to explain complex AI concepts.
- Providing practical examples relevant to paediatric SLT.
Main Results:
- A clinician-focused interpretation of the EU AI Act definition.
- Structured explanation of AI techniques, capabilities, and applications.
- A model for aligning clinical needs with AI design.
- Discussion of ethical and regulatory considerations for AI in SLT.
Conclusions:
- AI comprises techniques enabling capabilities that support clinical applications in SLT.
- This tutorial promotes safe, ethical, and accountable AI integration.
- AI should be viewed as a supportive tool for clinicians, not a replacement.
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