Borda, Ann;
Molnar, Andreea;
Neesham, Cristina;
Kostkova, Patty;
(2022)
Ethical Issues in AI-Enabled Disease Surveillance: Perspectives from Global Health.
Applied Sciences
, 12
(8)
, Article 3890. 10.3390/app12083890.
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Abstract
Infectious diseases, as COVID-19 is proving, pose a global health threat in an interconnected world. In the last 20 years, resistant infectious diseases such as severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), H1N1 influenza (swine flu), Ebola virus, Zika virus, and now COVID-19 have been impacting global health defences, and aggressively flourishing with the rise of global travel, urbanization, climate change, and ecological degradation. In parallel, this extraordinary episode in global human health highlights the potential for artificial intelligence (AI)-enabled disease surveillance to collect and analyse vast amounts of unstructured and real-time data to inform epidemiological and public health emergency responses. The uses of AI in these dynamic environments are increasingly complex, challenging the potential for human autonomous decisions. In this context, our study of qualitative perspectives will consider a responsible AI framework to explore its potential application to disease surveillance in a global health context. Thus far, there is a gap in the literature in considering these multiple and interconnected levels of disease surveillance and emergency health management through the lens of a responsible AI framework.
| Type: | Article |
|---|---|
| Title: | Ethical Issues in AI-Enabled Disease Surveillance: Perspectives from Global Health |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.3390/app12083890 |
| Publisher version: | http://doi.org/10.3390/app12083890 |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third-party material in this article are included in the Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
| Keywords: | Science & Technology, Physical Sciences, Technology, Chemistry, Multidisciplinary, Engineering, Multidisciplinary, Materials Science, Multidisciplinary, Physics, Applied, Chemistry, Engineering, Materials Science, Physics, AI, disease surveillance, pandemics, global public health, ethics, ARTIFICIAL-INTELLIGENCE, SOCIAL MEDIA, COVID-19, SYSTEMS, TIME |
| UCL classification: | UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Inst for Risk and Disaster Reduction UCL > Provost and Vice Provost Offices > UCL BEAMS UCL |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10148168 |
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