Report: Algorithms Are Worsening Racism, Bias, Discrimination
WASHINGTON, D.C. – Algorithms systematically and disproportionately harm Black and Brown communities by restricting opportunity and access, raising prices, and increasing surveillance and law enforcement, according to a new report from Public Citizen.
“Government policy is falling further and further behind in developing appropriately scaled solutions to address problems of accountability for algorithmic racial bias and discrimination,” the report reads. “There will not be a single silver bullet to address the wide-ranging harms of algorithmic racism. Rather, it will take a long-standing, concerted, and collaborative effort among policymakers, enforcers, organizers, advocates, and technologists to implement many different solutions to fully address the need.”
“Algorithmic racism not only replicates, but also exacerbates economic, social, and racial injustice,” said Jane Chung, Big Tech accountability advocate for Public Citizen. “To make a better world, we need to consider not only how to ensure algorithms are not worsening inequity, but also how they might be used to improve equitable outcomes. We need to start creating anti-racist algorithms.”
Algorithms are processes or sets of rules used along with data and statistical analyses in calculations for decision making. Unless they are intentionally designed to account for the legacy of and ongoing systems of discrimination, inequality, and bias, algorithms – even “color blind” ones – will replicate and exacerbate racial inequality. Algorithmic processes are less transparent, less accessible, and more difficult to explain or understand – and thus, more difficult to audit and regulate, according to the report. This lack of transparency is the reason many call them ‘black box’ algorithms: “There is no way to look inside and see how the sausage is made.”
Some of the key findings about how algorithms are worsening racism, bias, and discrimination:
- Auto insurance is more expensive. Communities of color pay 30% more for auto insurance premiums than whiter communities with similar accident costs;
- Credit scores are lower. White homebuyers have credit scores 57 points higher than Black homebuyers, and 33 points higher than Latinx homebuyers;
- Mortgages are more expensive or altogether inaccessible. Higher, discriminatory mortgage prices cost Latinx and Black communities $750 million each year. At least 6% of Latinx and Black applications are rejected – but would be accepted if the borrower were not a part of these minority groups;
- Students get screened out of better schools and assigned worse grades. In New York City, Black and Latinx students are admitted to top schools at half the rate of white and Asian students. At some universities, Black students were up to four times as likely to be labeled “high risk” as white students;
- Patients are denied life-saving care. White patients with the same level of illness were assigned higher risk scores than Black patients. As a result, the number of Black patients eligible for extra care was cut by more than half;
- Criminal justice system is more punitive. Black defendants are as much as 77% more likely to be assigned higher risk scores than white defendants; and
- Communities are over policed. Black individuals were targeted by predictive policing for drug use at twice the rate of white individuals. Non-Black people of color were targeted at a rate 1.5 times that of white individuals. Notably, the actual pattern of drug use by each race is comparable across the board.
Public Citizen’s report addresses racial discrimination and bias and explores solutions to advance racial justice. But algorithms have been shown to perpetuate bias and discrimination based on gender, socioeconomic status, immigration status, ethnicity, nationality, sexuality, ability, and more.