CDT’s AI Governance Lab develops and promotes adoption of robust, technically-informed solutions for the effective regulation and governance of AI systems.
The Lab provides public interest expertise in rapidly developing policy and technical conversations, to advance the interests of individuals whose lives and rights are impacted by AI. We place a particular emphasis on the rights and interests of historically marginalized people, who are often disproportionately harmed by poorly designed and implemented systems and face systemic barriers in countering those harms.
The AI Governance Lab is led by experts experienced in guiding the responsible development of AI products and services and in developing governance structures for AI-powered systems. They leverage CDT’s leadership in AI policy to engage directly with companies and multistakeholder initiatives, support public interest advocates, and guide policymakers on the effective governance of AI.
Statement of Core Activities
The Lab works in close collaboration with academic researchers, practitioners, and other stakeholders to define and promote implementable solutions.
• Advocating for the adoption of responsible governance solutions through multi-stakeholder initiatives and direct-to-company engagement. The Lab works with practitioners to define, shape, and implement standards and norms around priorities like AI auditing and safety evaluation.
• Supporting CDT’s policy teams in advising policymakers on how to achieve effective auditing, safety, and accountability solutions through legislation, regulation, funding, and government-endorsed best practices.
• Strengthening public interest advocates, particularly civil rights organizations, researchers focused on disinformation, and other groups representing impacted communities.
• Building bridges and access points for the research community. The Lab hosts fellowships and pursues collaborations with researchers working on topics including fairness, accountability, and transparency in AI, as well as information integrity and AI safety.
Latest Insights
Can Generative Intermediaries Deliver When It Comes to Information Quality?
How Policymakers Can Address AI Auditing and Assessment Requirements
CDT Submits Comments Opposing FTC’s Misguided “Policy Statement Addressing AI Accuracy”
Design Decisions and the Duty to Defend: What an Insurance Coverage Case Signals for AI Governance
Out of Tune: Fine-Tuning Foundation Models Leads to Unpredictable Safety Drift