Governance of artificial intelligence and personal health information. Issue 3 (13th May 2019)
- Record Type:
- Journal Article
- Title:
- Governance of artificial intelligence and personal health information. Issue 3 (13th May 2019)
- Main Title:
- Governance of artificial intelligence and personal health information
- Authors:
- Winter, Jenifer Sunrise
Davidson, Elizabeth - Abstract:
- Abstract : Purpose: This paper aims to assess the increasing challenges to governing the personal health information (PHI) essential for advancing artificial intelligence (AI) machine learning innovations in health care. Risks to privacy and justice/equity are discussed, along with potential solutions. Design/methodology/approach: This conceptual paper highlights the scale and scope of PHI data consumed by deep learning algorithms and their opacity as novel challenges to health data governance. Findings: This paper argues that these characteristics of machine learning will overwhelm existing data governance approaches such as privacy regulation and informed consent. Enhanced governance techniques and tools will be required to help preserve the autonomy and rights of individuals to control their PHI. Debate among all stakeholders and informed critique of how, and for whom, PHI-fueled health AI are developed and deployed are needed to channel these innovations in societally beneficial directions. Social implications: Health data may be used to address pressing societal concerns, such as operational and system-level improvement, and innovations such as personalized medicine. This paper informs work seeking to harness these resources for societal good amidst many competing value claims and substantial risks for privacy and security. Originality/value: This is the first paper focusing on health data governance in relation to AI/machine learning.
- Is Part Of:
- Digital policy, regulation and governance. Volume 21:Issue 3(2019)
- Journal:
- Digital policy, regulation and governance
- Issue:
- Volume 21:Issue 3(2019)
- Issue Display:
- Volume 21, Issue 3 (2019)
- Year:
- 2019
- Volume:
- 21
- Issue:
- 3
- Issue Sort Value:
- 2019-0021-0003-0000
- Page Start:
- 280
- Page End:
- 290
- Publication Date:
- 2019-05-13
- Subjects:
- Big data -- Governance -- Artificial intelligence -- Deep learning -- Personal health information
Telecommunication -- Economic aspects -- Periodicals
384.04105 - Journal URLs:
- http://www.emeraldinsight.com/loi/dprg ↗
http://www.emeraldinsight.com/ ↗ - DOI:
- 10.1108/DPRG-08-2018-0048 ↗
- Languages:
- English
- ISSNs:
- 2398-5038
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 11194.xml