This is the second entry in a two-part op-ed series on institutional racism in American medicine.
A little over a year before the coronavirus pandemic reached our shores, the racism problem in U.S. health care was making big headlines.
But it wasn't doctors or nurses being accused of bias. Rather, a study published in Science concluded that a predictive health care algorithm had, itself, discriminated against Black patients.
The story originated with Optum, a subsidiary of insurance giant UnitedHealth Group, which had designed an application to identify high-risk patients with untreated chronic diseases. The company's ultimate goal was to help re-distribute medical resources to those who'd benefit most from added care. And to figure out who was most in need, Optum's algorithm assessed the cost of each patient's past treatments.
Unaccounted for in the algorithm's design was this essential fact: The average Black patient receives $1,800 less per year in total medical care than a white person with the same set of health problems. And, sure enough, when the researchers went back and re-ranked patients by their illnesses (rather than the cost of their care), the percentage of Black patients who should have been enrolled in specialized care programs jumped from 18 percent to 47 percent.
Journalists and commentators pinned the blame for racial bias on Optum's algorithm. In reality, technology wasn't the problem. At issue were the doctors who failed to provide sufficient medical care to the Black patients in the first place. Meaning, the data was faulty because humans failed to provide equitable care.
Artificial intelligence and algorithmic approaches can only be as accurate, reliable and helpful as the data they're given. If the human inputs are unreliable, the data will be, as well.
Let's use the identification of breast cancer as an example. As much as one-third of the time, two radiologists looking at the same mammogram will disagree on the diagnosis. Therefore, if AI software were programmed to act like humans, the technology would be wrong one-third of the time.
Instead, AI can store and compare tens of thousands of mammogram images — comparing examples of women with cancer and without — to detect hundreds of subtle differences that humans often overlook. It can remember all those tiny differences when reviewing new mammograms, which is why AI is already estimated to be 10 percent more accurate than the average radiologist.
What AI can't recognize is whether it's being fed biased or incorrect information. Adjusting for bias in research and data aggregation requires that humans acknowledge their faulty assumptions and decisions, and then modify the inputs accordingly.
Correcting these types of errors should be standard practice by now. After all, any research project that seeks funding and publication is required to include an analysis of potential bias, based on the study's participants. As an example, investigators who want to compare people's health in two cities would be required to modify the study's design if they failed to account for major differences in age, education or other factors that might inappropriately tilt the results.
Given how often data is flawed, the possibility of racial bias should be explicitly factored into every AI project. With universities and funding agencies increasingly focused on racial issues in medicine, this expectation has the potential to become routine in the future. Once it is, AI will force researchers to confront bias in health care. As a result, the conclusions and recommendations they provide will be more accurate and equitable.
Thirteen months into the pandemic, Covid-19 continues to kill Black individuals at a rate three times higher than white people. For years, health plans and hospital leaders have talked about the need to address health disparities like these. And yet, despite good intentions, the solutions they put forth always look a lot like the failed efforts of the past.
Addressing systemic racism in medicine requires that we analyze far more data (all at once) than we do today. AI is the perfect application for this task. What we need is a national commitment to use these types of technologies to answer medicine's most urgent questions.
There is no antidote to the problem of racism in medicine. But combining AI with a national commitment to root out bias in health care would be a good start, putting our medical system on a path toward antiracism.
A view of the U.S. Capitol in Washington, D.C., on June 25, 2026. President Donald Trump jolted Republicans during a fiery appearance at the U.S. Capitol on Wednesday, scrapping a housing bill signing ceremony and clashing behind closed doors with a party rebel who challenged him over the Iran war. Trump had been expected to sign the bipartisan housing.
Only Trump doesn’t care about housing
It was August 15, 2024. Then candidate Donald Trump stepped out of his Bedminster, New Jersey, golf club’s columned clubhouse to a gaggle of reporters. He was flanked by tables of groceries and signs showing the rising cost of food. Also on one of the tables was a dollhouse, meant to represent the equally alarming rise in housing prices.
It was a speech about the economy, the single most important issue of the 2024 election cycle, full of promises that went right to the heart of Americans’ anxieties. While former President Joe Biden and then Vice President Kamala Harris were contorting themselves to posture a good economy that just needed more time to recover from the pandemic, Trump was preying on voters’ very real fears of unaffordable gas, groceries, and homes. It was obviously a winning message.
In that speech, Trump promised, “We’re going to open up tracts of federal land for housing construction. We desperately need housing for people who can’t afford what’s going on now.”
As of mid-2023, there had been a housing shortage of nearly four million homes, according to the National Association of Realtors. Americans all over the country were either priced out of buying new homes due to low inventory, trapped in their existing homes by sky-high mortgage rates, or facing exorbitant rent hikes thanks to corporate investors buying up rental properties. Americans needed help, and Trump promised it.
Cut to March of 2026, when Trump reportedly told House Speaker Mike Johnson, “No one gives a sh*t about housing.”
That kind of thinking may explain why Trump this week suddenly announced he was canceling a signing ceremony for the bipartisan “21st Century ROAD to Housing Act,” a housing bill co-sponsored by Sens. Elizabeth Warren and Tim Scott that passed the House 358-32 and was approved in the Senate on Monday.
Trump instead demanded Congress pass the SAVE America Act, his controversial election grievance bill that doesn’t have enough Republican support to get passed in the Senate.
It’s just the latest in a line of policy self-owns where Trump has seemingly intentionally made life more difficult for Republicans hoping to keep their majority. Despite midterm elections occurring in the midst of a blistering economy and an unpopular war, they were surely hoping the housing bill would give them something — anything — to brag about when they returned home to their districts.
And very much to the contrary, Americans do give a sh*t about housing. According to a recent survey by the Bipartisan Policy Center, a whopping 79% say the cost of housing is extremely or very important to them. Eighty-three percent say Congress should take action on the issue — like it just did. Eighty-nine percent say the House and Senate need to work together to pass affordable housing legislation — like they just did. And 63% say they would be more likely to vote for a lawmaker if they helped pass legislation to build more affordable homes and lower housing costs — like they just did.
There aren’t many issues that unite Americans like housing does, and very few bipartisan policy wins Congress can point to, and yet, Trump is holding that bill hostage in order to get his pet project — which doesn’t even have the support of his own party — pushed through.
If you’re trying to make sense of something so nonsensical, as I’m sure many Republican lawmakers are, it’s certainly sad but not actually all that complicated. Trump said what he needed to get reelected and then promptly abandoned his promises in order to pursue his own self-interests, even if those interests are bad for Republicans and bad for voters.
That’s just the kind of guy he is.
S.E. Cupp is the host of "S.E. Cupp Unfiltered" on CNN.