Ethical Issues in AI-Enabled Disease Surveillance: Perspectives from Global Health
Source abstract
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.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Data-Driven Disease Surveillance · COVID-19 epidemiological studies · Viral Infections and Outbreaks Research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Centre for Digital Transformation of Health, University of Melbourne, Parkville, VIC 3010, Australia
Department of Information Studies, University College London, London WC1E 6BT, UK
Department of Computing Technologies, Swinburne University of Technology, Hawthorn, VIC 3122, Australia
Newcastle University Business School, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
Institute for Risk and Disaster Reduction, University College London, London WC1E 6BT, UK
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