Human-Sensing Platforms and Ethical Considerations Throughout Their Data Life-Cycles

Abstract

Human-sensing platforms, encompassing digitized biometrics, activity sensing, and virtual human modeling, play a pivotal role in leveraging human-related data within the digital realm. With the swift progress of AI techniques, the promising opportunities brought about by these platforms are counterbalanced by the ethical challenges they pose. In considering these challenges, it is necessary to comprehend the characteristics of these platforms from data-centric viewpoints to understand their data management practices throughout their life-cycles. In this study, we first provide a comprehensive overview of various human-sensing platforms, highlighting the range of techniques utilized and the corresponding issues at each stage of the data lifecycle. Based on existing and emerging standards and frameworks on ethics in AI, we show the ethical issues and challenges in each phase in these data life-cycles. By providing this holistic perspective, our research contributes to the ongoing dialogue surrounding responsible data practices in the realm of human-sensing platforms.