As of 2022, the median White household in the United States held approximately $285,000 in net wealth, compared to just $45,000 for the median Black household. A new report led by Yvette Pappoe, distinguished professor in the David A. Clark School of Law at the University of the District of Columbia, discusses how the integration of artificial intelligence into systems that govern housing, lending, employment, and other critical areas could affect this gap in the United States, which has consistently widened since the 1960s.
According to Pappoe and her co-authors from the University of Connecticut, AI technology is not inherently harmful; rather, their research confirms that when AI systems are trained on data that has been shaped by systemic racial disparities, the technology reproduces those patterns, further accelerating racial inequities in real-world processes. The authors highlight three domains that contribute to the racial wealth gap (housing, lending, and employment) and outline how companies and policymakers can establish transparency and accountability in algorithmic decision-making.
In housing, the authors call on landlords and tenant-screening companies to disclose that AI is used in their processes and what the technology’s criteria are before applicants apply. To ensure that racial bias does not impact mortgage or other loan borrowers, the authors suggest the use of third-party audits of AI underwriting and credit scoring systems.
Algorithmic hiring and performance evaluation systems also have the potential to exacerbate the racial wealth gap. According to the authors, employers should be required to inform workers about how algorithms assess their qualifications and performance. The authors also urge policymakers to strengthen worker protections and labor rights to address AI’s potential role in workplace exploitation.
“To be clear, this does not have to be a foregone conclusion. AI technologies can produce positive outcomes when developed, tested, and adopted with principled and civil-rights-protective guardrails,” the authors write. “But without safeguards, governance, and corrective measures, AI risks reinforcing existing disparities under the guise of neutrality and efficiency. Companies developing or deploying AI must do so responsibly.”
Professor Pappoe’s academic expertise includes fair housing, intersectional feminism, and employment discrimination law. Her work primarily focuses on the intersections of race and gender and how the legal system tackles those complexities in administering justice.
Professor Pappoe earned her bachelor’s degree in sociology from the University of Maryland, Baltimore County and her juris doctorate from the University of Maryland Francis King Carey School of Law.
