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Defining ethical standards for the application of digital tools to population health research

Research output: Contribution to journalArticlepeer-review

Original languageSpanish
Pages (from-to)239-244
Number of pages6
JournalBulletin of the World Health Organization
Issue number4
PublishedApr 2020

King's Authors


There is growing interest in population health research which uses methods based
on artificial intelligence. Such research draws on a range of clinical and non-clinical
data to make predictions about health risks, such as identifying epidemics and
monitoring disease spread. Much of this research uses data from social media in the
public domain or anonymous secondary health data and is therefore exempt from
ethics committee scrutiny. While the ethical use and regulation of digital-based
research has been discussed, little attention has been given to the ethics
governance of such research in higher education institutions in the field of population
health. Such governance is essential to how scholars make ethical decisions and
provides assurance to the public that researchers are acting ethically. We propose a
process of ethics governance for population health research in higher education
institutions. The approach takes the form of review after the research has been
completed, with particular focus on the role artificial intelligence algorithms play in
augmenting decision-making. The first layer of review could be national, openscience repositories for open-source algorithms and affiliated data or information
which are developed during research. The second layer would be a sector-specific
validation of the research processes and algorithms by a committee of academics
and stakeholders with a wide range of expertise across disciplines. The committee
could be created as an off-shoot of an already functioning national oversight body or
health technology assessment organization. We use case studies of good practice to
explore how this process might operate.

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