… disparities perpetuating this bias. We investigate the effects of algorithmic bias stemming from
… predictions provides a novel way to use algorithms as a means of detecting inequities that …

… health equity, racial justice, and ethical AI principles into technology development to address
health inequities. … This step aims to promote and correct internal algorithmic bias in a way …

… examples of algorithmic bias in this paper still leaves open a critical question of whether
computers or humans are the culprits in engineering many of these systemic inequalities online. …

… Such biases are especially troubling in the context of underdiagnosis, whereby the AI … as
healthy, potentially delaying access to care. Here, we examine algorithmic underdiagnosis in …

… /untreated cancer cases, worsening health inequity for an already … bias will be pivotal to
improving healthcare outcomes. … indicative of algorithmic bias, but expecting completely bias-free …

… healthcare inequity caused by a history of structural racism in the US, and the encoding of
inequity in many healthcare … variable is wholly untainted by bias and inequity, we felt deaths …

… perpetuate or exacerbate inequities if they are not … “algorithmic bias playbook” [32]:
step-by-step instructions for organizations to identify, improve, and protect against biased algorithms …

… exacerbate the systemic healthcare inequalities we are currently seeing, which stem from
socioeconomic inequalities, differential health literacy and access to healthcare, and various …

… e emergence and growth of research on issues of ethics in Arti cial Intelligence, and in
particular algorithmic fairness, has roots in an essential observation that structural inequalities in …

… inequities, as well as group biases from the perpetuation of cultural stereotypes1–4. Though
traditionally viewed … In training algorithms on data that have internalized historical biases, …