@inproceedings{bc04ebb347b9475fb0c187f4d7c1d5a1,
title = "Responsibility and Regulation: Exploring Social Measures of Trust in Medical AI",
abstract = "This paper explores expert accounts of autonomous systems (AS) development in the medical device domain (MD) involving applications of artificial intelligence (AI), machine learning (ML), and other algorithmic and mathematical modelling techniques. We frame our observations with respect to notions of responsible innovation (RI) and the emerging problem of how to do RI in practice. In contribution to the ongoing discourse surrounding trustworthy autonomous system (TAS) [29], we illuminate practical challenges inherent in deploying novel AS within existing governance structures, including domain specific regulations and policies, and rigorous testing and development processes, and discuss the implications of these for the distribution of responsibility in novel AI deployment.",
keywords = "Ethnography, Medical AI, Responsible AI, SaMD, Trustworthy Autonomous Systems",
author = "Glenn McGarry and Andy Crabtree and Lachlan Urquhart and Alan Chamberlain",
note = "Publisher Copyright: {\textcopyright} 2024 Copyright held by the owner/author(s).; 2nd International Symposium on Trustworthy Autonomous Systems, TAS 2024 ; Conference date: 15-09-2024 Through 18-09-2024",
year = "2024",
month = sep,
day = "16",
doi = "10.1145/3686038.3686041",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
booktitle = "TAS 2024 - Proceedings of the 2nd International Symposium on Trustworthy Autonomous Systems",
address = "United States of America",
}