Ethical Concerns in AI-Driven Physiotherapy, Data Privacy and Security

Abstract

This chapter examines the ethical challenges associated with the integration of artificial intelligence into physiotherapy, with particular emphasis on data privacy, security, algorithmic bias, and patient confidentiality. It discusses the growing use of artificial intelligence and machine learning in healthcare, particularly in collecting, processing, and analysing sensitive patient information through wearable sensors, motion-tracking devices, and tele-rehabilitation platforms. The chapter highlights concerns regarding informed consent, data ownership, unauthorized access, cybersecurity threats, and the potential for biased algorithms to produce unequal treatment recommendations. It also explores privacy-enhancing technologies, including federated learning, differential privacy, blockchain-based data protection, and synthetic data generation. Furthermore, it emphasizes the importance of transparency, accountability, ethical guidelines, and legal frameworks in ensuring responsible AI implementation. The chapter concludes by highlighting the need for collaboration among healthcare professionals, AI developers, policymakers, and patients to promote safe, equitable, transparent, and patient-centred AI-driven physiotherapy.