The Daily UbuntuThread 02 · Technology and Dehumanization · September 25, 2026
Measuring illness in dollars
A U.S. health algorithm judged patients' needs by their past spending; Black patients, who received less care, therefore seemed less sick.
1 · The scene
In the waiting room of a clinic in Montréal-Nord, Ginette, a patient care attendant, chats with the woman in the next seat. She hasn't seen a doctor in four years: two jobs, no time, no family doctor.
"At least I don't cost the system much," she says with a laugh. Her neighbour doesn't laugh. Costing little is not the same thing as being well.
Original vignette
2 · The documented case
The algorithm that confused costs with needs
On October 25, 2019, the journal Science published the study by Ziad Obermeyer, Brian Powers, Christine Vogeli and Sendhil Mullainathan. They examined a commercial algorithm widely used by U.S. health systems to identify patients with complex needs and offer them extra follow-up. According to the researchers, this category of tools influences decisions for more than 100 million Americans.
Analyzing the records of 43,539 white patients and 6,079 Black patients at a large academic hospital, they found that at the same risk score, Black patients were markedly sicker. The reason: the algorithm predicts future health spending, not illness. But because of unequal access to care, less is spent treating Black patients. Lower past spending created the illusion of lower needs.
Correcting this bias would raise the share of Black patients receiving extra help from 17.7% to 46.5%. Better still: the researchers worked with the manufacturer, which confirmed their results. Together, they showed that by taking actual health needs into account, racial bias could be reduced by 84%.
The machine was not malicious; it had learned from an unequal world. And when researchers and a company agree to look at the problem together, correction becomes possible.
3 · The voice
“Algorithms by themselves are neither good nor bad.”
4 · The question
In our own numbers, at work and in our public services, what truly measures a person's needs, and what only measures what they have already been given?
Sources
- Z. Obermeyer, B. Powers, C. Vogeli and S. Mullainathan, "Dissecting racial bias in an algorithm used to manage the health of populations," Science, vol. 366, October 25, 2019. escholarship.org
- University of California, Berkeley, "Widely used health care prediction algorithm biased against black people," October 24, 2019. news.berkeley.edu
- Princeton University, RRAPP, "Algorithms Can Replicate or Remedy Racial Biases in Healthcare Resource Allocation." rrapp.spia.princeton.edu
Every figure on this page links to a verifiable public source.
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