Privacy, ethics, transparency, and accountability in AI systems for wearable devices

The integration of artificial intelligence (AI) and machine learning (ML) into wearable sensor technologies has substantially advanced health data science, enabling continuous monitoring, personalised interventions, and predictive analytics. However, the fast advancement of these technologies has raised critical ethical and regulatory concerns, particularly around data privacy, algorithmic bias, informed consent, and the opacity of automated decision-making. This study undertakes a systematic examination of these challenges, highlighting the risks posed by unregulated data aggregation, biased model training, and inadequate transparency in AI-powered health applications. Through an analysis of current privacy…

• BA
  Bill and Melinda Gates Foundation

  Award: INV-057591
• EA
  Engineering and Physical Sciences Research Council

  Award: EP/S035362/1