Eliminating Bias in Algorithmic Systems Act of 2026
HB7110, the Eliminating Bias in Algorithmic Systems Act of 2026, would require federal agencies that use, fund, procure, oversee, regulate, or advise on certain algorithms to maintain an office of civil rights focused on algorithmic bias, discrimination, and related harms. The bill defines covered algorithms broadly to include computational processes using machine learning, natural language processing, artificial intelligence, or similar techniques that can materially affect access to, eligibility for, cost of, or conditions of government programs, regulated economic opportunities, or rights protected by an agency.
The bill also requires each covered agency’s civil rights office to employ experts and technologists and to produce biennial reports to relevant congressional committees. Those reports must describe the state of covered algorithm technology, risks of bias and discrimination, steps taken to mitigate harms, stakeholder engagement, and any legislative or administrative recommendations. In addition, the Attorney General’s Civil Rights Division must establish an interagency working group on covered algorithms and civil rights within one year of enactment.
If enacted, the bill would create or formalize civil-rights-focused oversight structures within federal agencies that interact with algorithmic systems, and it would add recurring reporting obligations to Congress. It would not directly regulate private-sector AI across the board, but it would affect agencies’ procurement, funding, oversight, and internal review of algorithmic tools, potentially influencing how federal programs, benefits, enforcement, and regulatory decisions are designed and monitored. The bill authorizes appropriations as necessary to carry out these requirements.
The available record shows the bill was introduced and referred to the House Committee on Oversight and Government Reform, with no recorded votes or committee transcript excerpts provided. Based on the bill’s sponsors and text, the measure appears to be framed as a civil rights and accountability initiative aimed at addressing discriminatory impacts of AI and automated decision systems. Because there is no recorded debate or vote history in the provided materials, there is no documented opposition or support beyond the bill’s introduction.
The main potential points of contention are the breadth of the definition of a covered algorithm and the scope of the protected characteristics covered, which includes race, sex, disability, immigration status, age, income level, biometric information, and other federally protected classes. Supporters are likely to emphasize the need for civil rights expertise, transparency, and mitigation of discriminatory harms in automated systems, while critics may question administrative burden, costs, overlap with existing agency functions, or whether the bill could sweep in too many technologies and agency activities. No specific objections or amendments are documented in the provided materials.