CDT Testimony before New York City Council Joint Hearing on AI, Student Data, and Privacy in NYC Public Schools
Today Maddy Dwyer, State Policy Analyst for CDT, testified at a joint hearing before the New York City Council Committee on Education and Committee on Technology, on the issues of artificial intelligence (AI), student data, and privacy in NYC Public Schools.
Her testimony focused primarily on how AI use in classrooms, including in New York City schools, has rapidly accelerated even amid growing recognition of the risks it poses to students. As part of her testimony, she explained how CDT’s nationally representative polling research reveals the prevalence of four key risks of AI that all increase the more a school uses AI — data breaches and ransomware attacks; proliferation of deepfakes and non-consensual intimate imagery; AI systems failing to work as intended; and troubling interactions between students and chatbots.
Dwyer highlighted specific recommendations for the Council to address these risks so New York City schools can realize the benefits of AI. In particular, she discussed that the Council can take action to address risk management of AI systems, AI governance, and transparency, including encouraging NYC Public Schools to conduct more research on how this technology impacts students; establishing transparency requirements for edtech AI vendors; and mandating the creation of model procurement resources to guide AI purchasing decisions.
Dwyer urged the Council to provide formal avenues to engage parents, students, and community members in decisions about whether and how to use AI in the classroom, and to use this feedback to drive their policymaking.
The Privacy Paradox: How Government Data Has Become Less Private and Less Useful
Providing ready access to information collected and maintained by the government promotes accountability, innovation, and research, making transparency a core responsibility of serving as a steward of the public’s data. Public agencies must also safeguard sensitive information when making data publicly available.
Defending State Data: Lessons from California v. USDA
As the federal government increasingly seeks access to state administrative data, policymakers should consider not only legal authority and privacy implications, but also the practical effects on public confidence, program effectiveness, and states’ ability to fulfill their obligations to residents.
CDT, EFF, EPIC, and Upturn Submit Comments on GSA’s Updated Draft AI Terms and Conditions for Federal Contracts
Today, the Center for Democracy & Technology and allies submitted comments to the General Services Administration (GSA) in response to the request for comment regarding their updated draft AI Terms and Conditions for federal solicitations and contracts.
Bias at Scale: Understanding AI’s Impact on Student Achievement and Opportunity Gaps
Schools have an opportunity and responsibility to ensure that new technologies support, rather than undermine, their longstanding goal of expanding opportunity.
