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The algorithm predicts how much patients would cost the health-care system in the future. However, cost is not race-neutral, as black patients incurred about $1,800 less in medical costs per year than white patients with the same number of chronic conditions, which led to the algorithm scoring white patients as equally at risk of future health ...
There's more evidence of algorithms demonstrating racial bias. Researchers have determined that a "widely used" risk prediction algorithm from a major (but unnamed) healthcare provider had a ...
Disparate impacts: The algorithms systematize biases that have been measured externally and are known to impact disadvantaged groups such as racial minorities and women. Because the algorithms are proprietary, they cannot be tested for built-in human bias. Arbitrary: Research shows that there is substantial variation in scoring based on audits.
Addressing these structural issues is crucial for improving health equity and reducing the systemic disadvantages faced by racial and ethnic minorities. [21] Macias-Konstantopoulos et al. (2023) highlight how these factors disproportionately affect Black, Indigenous, and People of Color (BIPOC), leading to significant health-care inequities.
California Atty. Gen. Rob Bonta sent a letter to hospital CEOs requesting a list of all their algorithmic software in an investigation of racial bias.
The same article puts forward the claim, "Bias occurs because the algorithm uses health costs as a proxy for health needs," as African Americans have been found to face disproportionate poverty levels in the United States and are forced to spend less on healthcare than white patients. [106]
Health inequities can manifest as disparities in several aspects of health such as quality of healthcare, incidence and outcome of disease or disorders, life span, infant mortality, health and sexual education, exercise, and drug use. Furthermore, racism itself is thought to have a negative impact on both mental and physical health.
Coded Bias says that there is a lack of legal structures for artificial intelligence, and that as a result, human rights are being violated. It says that some algorithms and artificial intelligence technologies discriminate by race and gender statuses in domains such as housing, career opportunities, healthcare, credit, education, and ...