Litcius/Paper detail

AI, Explainability, and Safeguarding Patient Safety in Europe

Barry Solaiman, Mark G. Bloom

2022Cambridge University Press eBooks17 citationsDOIOpen Access PDF

Abstract

This chapter explores the efforts made by regulators in Europe to develop standards concerning the explainability of artificial intelligence (AI) systems used in wearables. Diagnostic health devices such as fitness trackers, smart health watches, ECG and blood pressure monitors, and other biosensors are becoming more user-friendly, computationally powerful, and integrated into society. They are used to track the spread of infectious diseases, monitor health remotely, and predict the onset of illness before symptoms arise. At their foundation are complex neural networks making predictions from a plethora of data. While their use has been growing, the COVID-19 pandemic will likely accelerate that rise as governments grapple with monitoring and containing the spread of infectious diseases. One key challenge for scientists and regulators is to ensure that predictions are understood and explainable to legislators, policymakers, doctors, and patients to ensure informed decision making.

Topics & Concepts

SafeguardingAgency (philosophy)Engineering ethicsField (mathematics)AccountabilityWearable computerTrustworthinessPolitical sciencePublic relationsEngineeringBusinessKnowledge managementComputer securityComputer scienceMedicineLawSociologyNursingSocial scienceEmbedded systemMathematicsPure mathematicsArtificial Intelligence in Healthcare and Education