  Artificial intelligence is already ubiquitous, and is increasingly being used
to autonomously make ever more consequential decisions. However, there has been
relatively little research into the existing and possible consequences for
population health equity. A narrative review was undertaken using a hermeneutic
approach to explore current and future uses of narrow AI and automated decision
systems (ADS) in medicine and public health, issues that have emerged, and
implications for equity. Accounts reveal a tremendous expectation on AI to
transform medical and public health practices. Prominent demonstrations of AI
capability - particularly in diagnostic decision making, risk prediction, and
surveillance - are stimulating rapid adoption, spurred by COVID-19. Automated
decisions being made have significant consequences for individual and
population health and wellbeing. Meanwhile, it is evident that hazards
including bias, incontestability, and privacy erosion have emerged in sensitive
domains such as criminal justice where narrow AI and ADS are in common use.
Reports of issues arising from their use in health are already appearing. As
the use of ADS in health expands, it is probable that these hazards will
manifest more widely. Bias, incontestability, and privacy erosion give rise to
mechanisms by which existing social, economic and health disparities are
perpetuated and amplified. Consequently, there is a significant risk that use
of ADS in health will exacerbate existing population health inequities. The
industrial scale and rapidity with which ADS can be applied heightens the risk
to population health equity. It is incumbent on health practitioners and policy
makers therefore to explore the potential implications of using ADS, to ensure
the use of artificial intelligence promotes population health and equity.
