CDT’s Kristin Woelfel Submits Written Testimony to Pennsylvania Advisory Committee to the U.S. Commission on Civil Rights
On May 1, CDT submitted written testimony to the Pennsylvania Advisory Committee to the U.S. Commission on Civil Rights on the intersection of civil rights and AI in education. Our testimony provides a summary of CDT’s legal analysis of student civil rights laws as applied to the disproportionate impacts of AI-powered educational technologies on protected classes of students, along with a copy of the full legal research report and slide deck with visual depictions of CDT’s polling data. Specifically, our testimony:
Lays out key legal authorities for civil rights enforcement in schools;
Lists key discrimination principles under which claims for algorithmic discrimination in schools might arise;
Describes specific types of AI-powered education technologies that are known or likely to have a discriminatory impact on protected classes; and
Briefly summarizes CDT’s recommendations to local education leaders to address potential AI-driven inequities in school.
Coalition Urges Senate Not to Let Companies Waive Financial Regulations for AI
CDT joined AI Now Institute, American Civil Liberties Union, and several organizations dedicated to tech policy, consumer protection, and civil rights in a letter to Senate leadership and the Senate Banking, Housing, and Urban Affairs Committee opposing the “AI Innovation Labs” language in Sec. 10509 of the CLARITY Act.
As concern about risks and harms related to AI systems continue to grow, a growing chorus of policymakers, industry leaders, and advocates have called for independent AI assessments. This explainer provides an overview of recent proposals for third-party assessment in the United States, including state and federal legislation, executive actions, and industry proposals.
Having third parties assess AI systems might seem like common sense, but crafting effective policies toward this goal can be devilishly tricky. A poorly-constructed ecosystem for third-party assessment could easily fail to consider the most consequential mechanisms of risk, neglect the AI harms that most impact people, or do more to protect AI companies than people.
Not All Guardrails Are Created Equal: Comparing Content Safety and Copyright Filtering
As courts and policymakers work through questions about chatbot liability, they should be wary of analogies that flatten meaningful technical differences. Copyright filtering and safety intervention share real challenges around ambiguity and evasion, but they diverge in what each control must assess, how each manifests over the course of a conversation, and how much can be verified from the outside.
