How to replace a physiotherapist: artificial intelligence and the redistribution of expertise. - Rowe, Michael; Nicholls, David A.; Shaw, James (Physiotherapy Theory & Practice, 2022)
The convergence of large datasets, increased computational power, and enhanced algorithm design has led to the increased success of machine learning (ML) and artificial intelligence (AI) across a wide variety of healthcare professions but which, so far, have eluded formal discussion in physiotherapy. This is a concern as we begin to see accelerating performance improvements in AI research in general, and specifically, an increase in competence within narrow domains of practice in clinical AI. In this paper we argue that the introduction of AI-based systems within the health sector is likely to have a significant influence on physiotherapy practice, leading to the automation of tasks that we might consider to be core to the discipline. We present examples of some of these AI-based systems in clinical practice, specifically video analysis, natural language processing (NLP), robotics, personalized healthcare, expert systems, and prediction algorithms. We address some of the key ethical implications of these emerging technologies, discuss the implications for physiotherapists, and explore how the resultant changes may challenge some long-held assumptions about the status of the profession in society.