*Result*: The Application of Artificial Intelligence in Speech and Language Therapy: Attitudes and Expectations.
Original Publication: London : Taylor & Francis for the Royal College of Speech & Language Therapists, c1998-
Alsobhi, M., H. S. Sachdev, M. F. Chevidikunnan, et al. 2022. “Facilitators and Barriers of Artificial Intelligence Applications in Rehabilitation: A Mixed‐Method Approach.” International Journal of Environmental Research and Public Health 19, no. 23: 15919. https://doi.org/10.3390/ijerph192315919.
AlZaabi, A., S. AlMaskari, and A. AalAbdulsalam. 2023. “Are Physicians and Medical Students Ready for Artificial Intelligence Applications in Healthcare?” Digital Health 9: 20552076231152167. https://doi.org/10.1177/20552076231152167.
Amann, J., E. Vayena, K. E. Ormond, D. Frey, V. I. Madai, and A. Blasimme. 2023. “Expectations and Attitudes towards Medical Artificial Intelligence: A Qualitative Study in the Field of Stroke.” PLoS ONE 18, no. 1: e0279088. https://doi.org/10.1371/journal.pone.0279088.
Azevedo, N., E. Kehayia, G. Jarema, G. Le Dorze, C. Beaujard, and M. Yvon. 2024. “How Artificial Intelligence (AI) Is Used in Aphasia Rehabilitation: A Scoping Review.” Aphasiology 38, no. 2: 305–336. https://doi.org/10.1080/02687038.2023.2189513.
Bhamidipaty, V., B. Botchu, D. L. Bhamidipaty, I. Guntoory, and K. P. Iyengar. 2025. “ChatGPT for Speech‐Impaired Assistance.” Disability and Rehabilitation: Assistive Technology 20, no. 6: 1–3. https://doi.org/10.1080/17483107.2025.2483300.
European Union (EU) 2024. Regulation 2024/1689 of the European Union Parliament and of the Council laying down Harmonised rules on Artificial Intelligence and Amending Regulations (Artificial Intelligence Act).
Fritsch, S. J., A. Blankenheim, A. Wahl, et al. 2022. “Attitudes and Perception of Artificial Intelligence in Healthcare: A Cross‐Sectional Survey Among Patients.” Digital Health 8: 205520762211167. https://doi.org/10.1177/20552076221116772.
Georgieva‐Tsaneva, G., A. Andreeva, P. Tsvetkova, et al. 2023. “Exploring the Potential of Social Robots for Speech and Language Therapy: A Review and Analysis of Interactive Scenarios.” Machines 11, no. 7: 693. https://doi.org/10.3390/machines11070693.
Girardi, A. M., E. A. Cardell, and S. P. Bird. 2023. “Artificial Intelligence in the Interpretation of Videofluoroscopic Swallow Studies: Implications and Advances for Speech–Language Pathologists.” Big Data and Cognitive Computing 7, no. 4: 178. https://doi.org/10.3390/bdcc7040178.
Grote, T., and P. Berens. 2020. “On the Ethics of Algorithmic Decision‐Making in Healthcare.” Jorunal of Medical Ethics 46: 205–211. https://doi.org/10.1136/medethics‐2019‐105586.
Hegde, S., S. Shetty, S. Rai, and T. Dodderi. 2019. “A Survey on Machine Learning Approaches for Automatic Detection of Voice Disorders.” Journal of Voice 33, no. 6: 947.e11–947.e33. https://doi.org/10.1016/j.jvoice.2018.07.014.
Hogg, H. D. J., M. Al‐Zubaidy, T. E. M. S. S. R. Group, et al. 2023. “Stakeholder Perspectives of Clinical Artificial Intelligence Implementation: Systematic Review of Qualitative Evidence.” Journal of Medical Internet Research 25, no. 1: e39742. https://doi.org/10.2196/39742.
Kumar, R., M. Tripathy, N. Kumar, and R. S. Anand. 2022. “Management of Parkinson's Disease Dysarthria: Can Artificial Intelligence Provide the Solution?” Annals of Indian Academy of Neurology 25, no. 5: 810–816. https://doi.org/10.4103/aian.aian_554_22.
Lammert, J. M., A. C. Roberts, K. McRae, L. J. Batterink, and B. E. Butler. 2025. “Early Identification of Language Disorders Using Natural Language Processing and Machine Learning: Challenges and Emerging Approaches.” Journal of Speech, Language, and Hearing Research 68, no. 2: 705–718. https://doi.org/10.1044/2024_JSLHR‐24‐00515.
Lupyan, G. 2016. “The Centrality of Language in Human Cognition.” Language Learning 66, no. 3: 516–553. https://doi.org/10.1111/lang.12155.
Maassen, O., S. Fritsch, J. Palm, et al. 2021. “Future Medical Artificial Intelligence Application Requirements and Expectations of Physicians in German University Hospitals: Web‐Based Survey.” Journal of Medical Internet Research 23, no. 3: e26646. https://doi.org/10.2196/26646.
Mayring, P. 2022. Qualitative Content Analysis. A Step‐by‐Step Guide. Sage.
McCradden, M. D., A. Baba, A. Saha, et al. 2020. “Ethical Concerns Around Use of Artificial Intelligence in Health Care Research From the Perspective of Patients With Meningioma, Caregivers and Health Care Providers: A Qualitative Study.” Canadian Medical Association Open Access Journal 8, no. 1: E90–E95. https://doi.org/10.9778/cmajo.20190151.
Mousavi Baigi, S. F., M. Sarbaz, K. Ghaddaripouri, M. Ghaddaripouri, A. S. Mousavi, and K. Kimiafar. 2023. “Attitudes, Knowledge, and Skills towards Artificial Intelligence Among Healthcare Students: A Systematic Review.” Health Science Reports 6, no. 3: e1138. https://doi.org/10.1002/hsr2.1138.
Murphy, K., E. Di Ruggiero, R. Upshur, et al. 2021. “Artificial Intelligence for Good Health: A Scoping Review of the Ethics Literature.” BMC Medical Ethics 22, no. 1: 14. https://doi.org/10.1186/s12910‐021‐00577‐8.
Pinto‐Coelho, L. 2023. “How Artificial Intelligence Is Shaping Medical Imaging Technology: A Survey of Innovations and Applications.” Bioengineering 10, no. 12: 1435. https://doi.org/10.3390/bioengineering10121435.
Pinto dos Santos, D., D. Giese, S. Brodehl, et al. 2019. “Medical Students' Attitude Towards Artificial Intelligence: A Multicentre Survey.” European Radiology 29, no. 4: 1640–1646. https://doi.org/10.1007/s00330‐018‐5601‐1.
Prakash, S., J. N. Balaji, A. Joshi, and K. M. Surapaneni. 2022. “Ethical Conundrums in the Application of Artificial Intelligence (AI) in Healthcare—A Scoping Review of Reviews.” Journal of Personalized Medicine 12, no. 11: 1914. https://doi.org/10.3390/jpm12111914.
Purohit, A. K., A. Upadhyaya, and A. Holzer. 2023. “ChatGPT in Healthcare: Exploring AI Chatbot for Spontaneous Word Retrieval in Aphasia.” In Companion Publication of the 2023 Conference on Computer Supported Cooperative Work and Social Computing, 1–5. ACM. https://doi.org/10.1145/3584931.3606993.
Richardson, J. P., C. Smith, S. Curtis, et al. 2021. “Patient Apprehensions About the Use of Artificial Intelligence in Healthcare.” Npj Digital Medicine 4, no. 1: 140. https://doi.org/10.1038/s41746‐021‐00509‐1.
Sakai, K., S. Gilmour, E. Hoshino, et al. 2021. “A Machine Learning‐Based Screening Test for Sarcopenic Dysphagia Using Image Recognition.” Nutrients 13, no. 11: 4009. https://doi.org/10.3390/nu13114009.
Secinaro, S., D. Calandra, A. Secinaro, V. Muthurangu, and P. Biancone. 2021. “The Role of Artificial Intelligence in Healthcare: A Structured Literature Review.” BMC Medical Informatics and Decision Making 21, no. 1: 125. https://doi.org/10.1186/s12911‐021‐01488‐9.
Terry, A. L., J. K. Kueper, R. Beleno, et al. 2022. “Is Primary Health Care Ready for Artificial Intelligence? What do Primary Health Care Stakeholders Say?” BMC Medical Informatics and Decision Making 22, no. 1: 237. https://doi.org/10.1186/s12911‐022‐01984‐6.
Vayena, E., A. BlasimmeI, and Cohen. 2018. “Machine Learning in Medicine: Addressing Ethical Challenges.” Plos Medicine 15, no. 11. https://doi.org/10.1371/journal.pmed.1002689.
World Health Organization . 2021. Ethics and Governance of Artificial Intelligence for Health. World Health Organization. Licence: CC BY‐NC‐SA 3.0 IGO.
Zandi, D., A. Reis, E. Vayena, and K. Goodman. 2019. “New Ethical Challenges of Digital Technologies, Machine Learning and Artificial Intelligence in Public Health: A Call for Papers.” Bulletin of the World Health Organization 97, no. 1: 2. https://doi.org/10.2471/BLT.18.227686.
*Further Information*
*Background: Artificial intelligence (AI) shows promise to support the prevention, diagnosis, and treatment of diseases in medicine and therapy. However, ethics is a priority concern in the development and implementation of AI across sectors. Common ethical themes in the healthcare literature of the last 5 years surround algorithmic bias, accountability, privacy, transparency and trust issues. The question arises how these challenges apply to speech and language therapy (SLT). Stakeholder attitudes towards the use of AI in healthcare have been investigated for the populations of physicians, medical students, and patients. However, no study has yet addressed the specific perspective of speech and language therapists on this technology.
Aims: Therefore, the aim was to gather insights on the attitudes, hopes and concerns towards the (future) use of artificial intelligence from speech and language therapists working in clinical practice or research.
Method and Procedures: An online survey with 11 closed and three open-ended questions was conducted in four German speaking countries. The quantitative analysis of the results involved correlating demographic factors, such as age, with the responses. The qualitative analysis compared the responses to this survey with the findings of healthcare literature and studies addressing other healthcare stakeholders.
Outcomes and Results: Five hundred eighty-seven professionals from Germany, Switzerland, Austria and Liechtenstein answered the questionnaire. In the results all but 3% of the participants expect that AI will be applied at least to some extend in SLT in the future. The majority of the participants (65%) are open-minded towards the application of AI in SLT. Perceived potential benefits show a larger overlap than identified challenges with the existing literature. The possible loss of the 'human-factor' in assessment and therapy is by far the most frequent concern (41%) the participating speech and language therapists have towards the use of AI. Results further reflect the current level of knowledge about this technology in our profession.
Conclusions and Implications: The use of AI in SLT can have a positive impact, but many factors need to be considered to prepare our profession for this type of technology. These include the expansion of education, the development of guidelines and the establishment of interdisciplinary collaborations all aiming to develop, implement and enable the use of truly beneficial AI-tools for assessment and intervention in SLT.
What This Paper Adds: What is already known on this subject Stakeholder involvement is important in the development and implication of artificial intelligence in health care. Stakeholder attitudes towards the use of AI in healthcare have been investigated for the populations of physicians, medical students and patients. However, no study has yet addressed the specific perspective of speech and language therapists on this technology. What this paper adds to existing knowledge The majority of the participants are open-minded towards the application of AI in SLT and think that it will be used in our profession in the future. Perceived potential benefits and challenges align with the literature to some degree. One aspect that is especially emphasised by the participants is the potential loss of 'human-factor' in SLT. Results reflect participants' knowledge on AI as well as a specific therapeutic view on healthcare and intervention. What are the potential or actual clinical implications of this work? AI application in SLT has great potential, but also comes with challenges. Speech and language therapists need to expand their knowledge on this technology, prepare specific guidelines and engage in interdisciplinary collaborations to specify their perspective and needs in developing and implementing AI-software. Only then will it become truly useful for clinicians and they will be able to use it in a responsible and informed way.
(© 2025 Royal College of Speech and Language Therapists.)*