Introduction 

During the first week of his second term in office, President Donald Trump issued an unprecedented thirty-six executive orders. Executive orders are legally binding directives that allow the president to instruct federal agencies on how to interpret and implement federal law without congressional approval. The Trump administration has also relied heavily on presidential actions, which are directives that call on the federal government to take specific steps but are not published in the Federal Registry. Because these actions are not formally recorded, they are more difficult for the public and Congress to track, limiting transparency and oversight.
 

These tools enable the administration to rapidly reshape federal policy, often producing far-reaching consequences for communities nationwide. Congress retains mechanisms to challenge or restrict these directives through legislation, oversight, and public pressure, while courts review them for legality and constitutionality. The Congressional Black Caucus Foundation (CBCF) monitors executive orders and presidential actions that put Black Americans at risk, specifically in economic opportunity, education, criminal justice, health equity, and civil rights protections. Their Executive Order Tracker shows the legal status of these directives and records over 150 responses from Congressional Black Caucus members who have voiced concerns about their impact on Black communities (Congressional Black Caucus Foundation, 2024).
 

As federal executive power rapidly expands, Congress faces mounting pressure to enact legislation to urgently strengthen oversight of algorithmic systems that are currently shaping access to opportunity and public services. Two recent bills, the Algorithm Accountability Act and the Eliminating Bias within Algorithmic Systems Act of 2026, mark crucial and immediate steps toward confronting the civil rights risks posed by artificial intelligence.
 

Federal Algorithmic Accountability: Two Emerging Approaches 

1. The Algorithm Accountability Act 

The Algorithm Accountability Act would amend Section 230 to limit liability protections for social media platforms if recommendation algorithms cause foreseeable harm. Platforms must exercise reasonable care in algorithm design, or risk losing immunity and facing civil lawsuits for damages.
 

This approach mirrors state-level trends in algorithmic accountability: companies must assess risks, disclose procedures, and prevent foreseeable harms. The bill bars forced arbitration for claims of algorithmic harm, allowing individuals to seek justice in federal court. It narrows Section 230 protections, marking a significant federal move to regulate algorithmic design and platform responsibility.
 

2. The Eliminating Bias within Algorithmic Systems Act of 2026 

The Eliminating Bias within Algorithmic Systems Act requires federal agencies that use or oversee algorithms to establish civil rights offices staffed by experts focused on bias and discrimination. Covered algorithms include any AI systems affecting access to public programs, opportunities, or rights.
 

Agencies submit biennial reports to Congress on machine learning bias risks, mitigation steps, stakeholder engagement, and policy recommendations. The bill creates a DOJ-led interagency working group to coordinate federal civil rights oversight, mirroring expanding state efforts to require algorithmic impact assessments and to coordinate across agencies.
 

Why These Bills Matter for Black and Brown Communities 

Recent federal and academic research shows that algorithmic systems can deepen racial inequities in ways that are often hidden from public view. The Stanford Artificial Intelligence Index Report documents how automated systems used in public benefits screening, fraud detection, and risk assessment can incorrectly flag Black and Brown individuals at higher rates, resulting in delays or denials of necessary services (Perrault and Gil, 2025). In healthcare, clinical decision support tools have been shown to underestimate the severity of illness among Black patients because they rely on historical cost data rather than medical need, resulting in unequal access to treatment. Educational technologies, including automated plagiarism detectors and learning analytics platforms, have also demonstrated higher error rates for students with non-standard dialects and multilingual backgrounds, which can lead to unwarranted disciplinary actions or academic punishments. These examples show how algorithmic systems can reproduce systemic disparities when deployed without rigorous oversight, transparency, or civil rights safeguards.
 

The CBCF urgently warns that unchecked executive actions and shifting federal policies can rapidly deepen these inequities, especially when oversight is weak or inconsistent (Congressional Black Caucus Foundation, 2024). The Eliminating Bias within Algorithmic Systems Act takes a critical step by mandating federal agencies to immediately monitor and report on algorithmic harms, while the Algorithm Accountability Act addresses the pressing dangers posed by commercial recommendation algorithms to online behavior and public safety.
 

Together, these bills urgently demonstrate the federal government's role in building the civil rights infrastructure that communities have long demanded. They also directly respond to the growing, critical public demands for transparency, accountability, and justice in the field of artificial intelligence.
 

Conclusion 

“A house built without inspection will collapse on those who trust it,” explains how this might affect our community. Systems that shape opportunity and public life must be examined, tested, and held accountable before harm occurs. As artificial intelligence becomes more deeply embedded in federal decision-making, Congress has a responsibility to ensure that these systems do not reproduce or intensify racial inequities. The Algorithm Accountability Act and the Eliminating Bias within Algorithmic Systems Act of 2026 offer two complementary approaches to strengthening oversight, reducing harm, and protecting Black and Brown communities from the unintended consequences of automated decision-making. Strong supervision is not optional. It is the foundation that keeps the entire house standing.
 

References 

Congressional Black Caucus Foundation, Inc. (2026, February 13). CBCF Executive Order Tracker: Impacts on Black America " congressional black caucus foundation " Advancing the global black community by developing leaders informing policy and educating the public. Congressional Black Caucus Foundation. 

https://www.cbcfinc.org/policy-research/cbcf-executive-order-tracker-impacts-on-bla ck-america/ 

Gil, Y., & Perrault, R. (2025, November 19). Artificial Intelligence Index Report 2025 | Stanford Hai. AI Index Report 2025. 

https://hai.stanford.edu/assets/files/hai_ai_index_report_2025.pdf 

Markey, E. (n.d.). Eliminating bias in algorithmic systems act of 2026 (s. 3680). GovTrack.us. https://www.govtrack.us/congress/bills/119/s3680