Accountable AI for Healthcare IoT Systems 


Various AI systems have taken a unique space in our daily lives, 
helping us in decision-making in critical as well as non-critical 
scenarios. Although these systems are widely adopted across 
different sectors, they have not been used to their full potential 
in critical domains such as the healthcare sector enabled by the 
Internet of Things (IoT). One of the important hindering factors 
for adoption is the implication for accountability of decisions 
and outcomes affected by an AI system, where the term 
accountability is understood as a means to ensure the performance 
of a system. However, this term is often interpreted differently 
in various sectors. Since the EU GDPR regulations and the US 
congress have emphasised the importance of enabling accountability 
in AI systems, there is a strong demand to understand and 
conceptualise this term. It is crucial to address various aspects 
integrated in accountability and understand how it affects the 
adoption of the AI systems. In this paper, we conceptualise these 
factors affecting accountability and how it contributes to a 
trustworthy healthcare AI system. By focusing on healthcare IoT 
systems, our conceptual mapping will help the readers understand 
what system aspects those factors are contributing to and how they 
affect the system trustworthiness. Besides illustrating 
accountability in detail, we also share our vision towards causal 
interpretability as a means to enhance accountability for 
healthcare AI systems. The insights of this paper shall contribute 
to the knowledge of academic research on accountability, and 
benefit AI developers and practitioners in the healthcare sector.

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IEEE Library Access

author={Bagave, Prachi and Westberg, Marcus and Dobbe, Roel and Janssen, Marijn and Ding, Aaron Yi }, 
booktitle={Fourth IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA)}, 
title={Accountable AI for Healthcare IoT Systems},
How to cite:

Prachi Bagave, Marcus Westberg, Roel Dobbe, Marijn Janssen, Aaron Yi Ding, "Accountable AI for Healthcare IoT Systems", in Proceedings of the Fourth IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA), 2022.