… and management of the data used by the algorithm (phase 2… on patients, populations, and
society, including data privacy … marginalized populations such as racial and ethnic minoritized …

… with racial and ethnic bias mitigation in algorithms used either to … population health goals,
such as efficiently allocating health … Towards a standard for identifying and managing bias in …

… information from stakeholders on racial and ethnic bias related to health care algorithms. …
Dissecting racial bias in an algorithm used to manage the health of populations. Science. …

… apply in healthcare, where predictive algorithms are being … though the algorithm was “race-unaware”—ie,
race was not … a larger role for population health management in accountable …

… and ethnic composition of the population used in model … disparities as an approach to reduce
racial and ethnic bias in algorithm … the actual use of algorithms to manage patients. Rather, …

… , for learning personalized management and treatment plans by … which the algorithm worked
in the original population are not … populations based on factors such as race and ethnicity is …

… population level, the consequences of discrimination include worse health outcomes from
birth to death for certain ethnic … The Optum algorithm, which was deployed on many millions of …

… of AI/ML and racial disparities in healthcare: an issue that … for all populations. We unpack
the challenge of algorithmic … analytical process used to build and deploy AI/ML algorithms and …

… In this case, the translation of healthcare algorithms built from bad data or racially biased
research into … Dissecting racial bias in an algorithm used to manage the health of populations. …

… ,” to use his term for policy and public management challenges related … data are used to train
algorithms used for entire populations, … 200 million people, had substantial racial bias. The …