AI-Driven Dermatology Could Leave Dark-Skinned Patients Behind

human skin cells

AI technologies have the potential to save thousands of people from skin cancer yearly, by aiding early diagnosis. However, this shift is also potentially dangerous for darker-skinned patients, as the demographic imbalances in dermatology can leave machine learning diagnoses less effective for darker-skinned patients.

How medicine discriminates against non-white people and women

a black hand and a white hand both using an oximeter side by side

This article explores how the pulse oximeter, a device used to test oxygen levels in blood for coronavirus patients, exhibits racial bias. Medical journals give evidence that pulse oximeters overestimated blood-oxygen saturation more frequently in black people than white.

How a Popular Medical Device Encodes Racial Bias

A patient using a pulse oximeter

COVID-19 care has brought the pulse oximeter to the home, it’s a medical device that helps to understand your oxygen saturation levels. This article examines research that shows oximetry’s racial bias. Oximeters have been calibrated, tested and developed using light-skinned individuals. For a non-white person, inaccurate readings could be fatal.

Skin Deep: Racial Bias in Wearable Tech

Black woman in sportswear looking at her smartphone with fitness data superimposed across the image

Health monitoring devices influence the way that we eat, sleep, exercise, and perform our daily routines. But what do we do when we discover that the technology we rely on is built on faulty methodology and legacy effects of racial bias?

Fitbits and other wearables may not accurately track heart rates in people of colour

hands with varying skin colours all wearing smartwatches

An estimated 40 million people in the US alone have smartwatches or fitness trackers that can monitor heartbeats. However, some people of colour may be at risk of getting inaccurate readings. Heart rate trackers rely on technology that is designed for and tested on lighter-skinned individuals, meaning that the technology could be less reliable for […]

How an Algorithm Blocked Kidney Transplants to Black Patients

X-ray with kidneys highlighted

An algorithm used in the US supposed to estimate kidney function, the severity of the disease and allocation of kidney transplants, is found to be racially skewed, under-allocating necessary resources to black patients. A study demonstrates that the algorithm took an individual’s race into account, meaning that they were not offered a kidney transplant when […]

Assessing and Mitigating Bias in Medical Artificial Intelligence

Report title page

Deep learning algorithms using data from homogeneous populations may be difficult to generalise, and potentially exacerbate racial disparities in health and health care. This research paper explores (1) whether the accuracy of a deep learning algorithm varies depending on race / ethnicity, and (2) whether this performance is down to racial variation or external health […]

Racial Bias Found in Health Care Company Algorithm

black patient being checked out by a white doctor

New York news video reporting on the investigation into UnitedHealth Group over allegations that they are utilising a racially biased algorithm. A new study reports that the new AI software leads to lower levels of care for black patients compared to white patients.

Can AI Tackle Racial Inequalities in Healthcare?

A medic helping a black woman with a leg injury

News article, drawing on a study by Nature Medicine, which explains how algorithms might be able to help tackle racial biases within doctors’ own judgements. Doctors’ judgement of how much pain a patient is feeling has been linked to discrimination and racism, with black patients likely to have their pain level underestimated, which can adversely […]

Health Care AI Systems are Biased

a brain depicted as computer circuits

This article explains how bias in AI systems is contributing to the exacerbation of racial health disparities. There is a huge issue with the misrepresentation of our data sets, which could result in health systems that do not correctly identify nor treat illnesses in non-white patients. For example, skin-cancer detection algorithms trained on light-skinned individuals, […]