AI and Patients’ Rights : Transparency and information flows as situated principles in public health care
Högberg, Charlotte LU
and Larsson, Stefan
LU
(2022)
In De Lege
2021.
p.401-429
- Abstract
- The development of artificial intelligence (AI) for medicine and health care is rapidly evolving. However, the automation, scale and data dependency of AI-driven decision-making and decision-support calls for a reassessment of principal ethical and legal norms of transparency, in the light of these novel methodologies. The quality of AI-driven health care, we argue, is depending on it. In this chapter, we provide an overview of novelties that AI in health care bring about, in order to identify key aspects potentially affecting current legal and normative (medical ethical) principles related to transparency and explainability. We develop a conceptual framework on transparency in general and explainability in particular, in relation to AI in... (More)
- The development of artificial intelligence (AI) for medicine and health care is rapidly evolving. However, the automation, scale and data dependency of AI-driven decision-making and decision-support calls for a reassessment of principal ethical and legal norms of transparency, in the light of these novel methodologies. The quality of AI-driven health care, we argue, is depending on it. In this chapter, we provide an overview of novelties that AI in health care bring about, in order to identify key aspects potentially affecting current legal and normative (medical ethical) principles related to transparency and explainability. We develop a conceptual framework on transparency in general and explainability in particular, in relation to AI in health care. Further, we analyse principal and normative legal frameworks of patients’ rights relating to transparency and explainability – e.g., right to information, autonomy and privacy – within Sweden and the EU. Doing so, we outline main challenges in the implementation of AI in, primarily public, health care. We argue that there is an interdependency between health care quality and transparency. As transparency is not a binary state, but something that is situated in information practices, it is important to consider what kind of transparency is needed to safeguard the best possible health care. We find that meaningful and contextual transparency and explainability of AI-systems and methodologies is necessary to adhere to the basic principles of normative and legal frameworks of Swedish health care, including patient autonomy. In addition, meaningful and contextual transparency is also a prerequisite for assessing if the best possible care is given to the one most in need. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/241700df-76f2-4491-8679-5e9932e9b8a1
- author
- Högberg, Charlotte
LU
and Larsson, Stefan
LU
- organization
- publishing date
- 2022-04-05
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- public health care, patient rights, information flows, transparency, AI, AI in medicine, AI-driven decision-making, medical ethics, explainability, right to information, situatedness
- host publication
- De Lege – Yearbook Uppsala Faculty of Law 2021 : Law, AI & Digitalization - Law, AI & Digitalization
- series title
- De Lege
- editor
- de Vries, Katja and Dahlberg, Mattias
- volume
- 2021
- pages
- 28 pages
- publisher
- Iustus förlag
- ISSN
- 1102-3317
- ISBN
- 978-91-7737-167-0
- project
- The Automated Administration: Governance of ADM in the public sector
- AI-förordningen - mellan fixering och flexibilitet
- Medical humanities research node
- AIR Lund - Artificially Intelligent use of Registers
- Automated decision-making – Nordic perspectives
- AI in the Name of the Common Good - Relations of data, AI and humans in health and public sector
- Mammography Screening with Artificial Intelligence
- Lund University AI Research
- language
- English
- LU publication?
- yes
- id
- 241700df-76f2-4491-8679-5e9932e9b8a1
- date added to LUP
- 2021-12-01 09:28:41
- date last changed
- 2023-11-08 05:33:08
@inbook{241700df-76f2-4491-8679-5e9932e9b8a1,
abstract = {{The development of artificial intelligence (AI) for medicine and health care is rapidly evolving. However, the automation, scale and data dependency of AI-driven decision-making and decision-support calls for a reassessment of principal ethical and legal norms of transparency, in the light of these novel methodologies. The quality of AI-driven health care, we argue, is depending on it. In this chapter, we provide an overview of novelties that AI in health care bring about, in order to identify key aspects potentially affecting current legal and normative (medical ethical) principles related to transparency and explainability. We develop a conceptual framework on transparency in general and explainability in particular, in relation to AI in health care. Further, we analyse principal and normative legal frameworks of patients’ rights relating to transparency and explainability – e.g., right to information, autonomy and privacy – within Sweden and the EU. Doing so, we outline main challenges in the implementation of AI in, primarily public, health care. We argue that there is an interdependency between health care quality and transparency. As transparency is not a binary state, but something that is situated in information practices, it is important to consider what kind of transparency is needed to safeguard the best possible health care. We find that meaningful and contextual transparency and explainability of AI-systems and methodologies is necessary to adhere to the basic principles of normative and legal frameworks of Swedish health care, including patient autonomy. In addition, meaningful and contextual transparency is also a prerequisite for assessing if the best possible care is given to the one most in need.}},
author = {{Högberg, Charlotte and Larsson, Stefan}},
booktitle = {{De Lege – Yearbook Uppsala Faculty of Law 2021 : Law, AI & Digitalization}},
editor = {{de Vries, Katja and Dahlberg, Mattias}},
isbn = {{978-91-7737-167-0}},
issn = {{1102-3317}},
keywords = {{public health care; patient rights; information flows; transparency; AI; AI in medicine; AI-driven decision-making; medical ethics; explainability; right to information; situatedness}},
language = {{eng}},
month = {{04}},
pages = {{401--429}},
publisher = {{Iustus förlag}},
series = {{De Lege}},
title = {{AI and Patients’ Rights : Transparency and information flows as situated principles in public health care}},
url = {{https://lup.lub.lu.se/search/files/117236020/H_gberg_Larsson_2022_AI_and_Patients_Rights.pdf}},
volume = {{2021}},
year = {{2022}},
}