The use of machine learning (ML) in healthcare raises numerous ethical concerns,
especially as models can amplify existing health inequities. Here, we outline ethical …

Algorithms are ubiquitous and critical sources of information online, increasingly acting as
gatekeepers for users accessing or sharing information about virtually any topic, including …

A recent normative turn in computer science has brought concerns about fairness, bias, and
accountability to the core of the field. Yet recent scholarship has warned that much of this …

Background The field of oncology is at the forefront of advances in artificial intelligence (AI)
in health care, providing an opportunity to examine the early integration of these …

As a descriptor, artificial intelligence (AI) is polysemous and problematic. Like the muddled
“big data” before it, this term du jour tends to be invoked broadly and haphazardly, by …

Treating health disparities with artificial intelligence | Nature Medicine Skip to main content
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Recent developments in image classification and natural language processing, coupled with
the rapid growth in social media usage, have enabled fundamental advances in detecting …

Artificial intelligence (AI) offers much promise for improving healthcare. However, it runs the
looming risk of causing individual and societal harms; for instance, exacerbating inequalities …

Many people use the internet to seek information that will help them understand their body
and their health. Motivations for such behaviors are numerous. For example, users may wish …

To design effective vaccine policies, policymakers need detailed data about who has been
vaccinated, who is holding out, and why. However, existing data in the US are insufficient …