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.
The norms of conversational advertising are being written right now by companies. Policy should be written alongside them, and it should start with recognizing that surreptitious manipulation at scale built on intimate information is itself a privacy harm, and a privacy law can, in part, solve some of those issue
Talking Tech with Roy Austin & Alex Givens on The Future of AI Governance
In this episode of CDT’s Tech Talks, Roy L. Austin, Jr., inaugural director of Howard University School of Law’s AI Initiative, joins Alexandra Givens, President and CEO of the Center for Democracy & Technology, to discuss the challenges and opportunities shaping the future of AI.
CDT-led Coalition Calls for Transparency for White House AI Framework
CDT and Americans for Responsible Innovation led a broad, bipartisan coalition of over two dozen civil society groups in calling on the White House to release its Framework for review of frontier AI models.
Changing Course to Get It Right: The Advisory Committee Reviews Its AI Evidence Rule
CDT is keeping a close eye on Proposed Federal Rule of Evidence 707, which would govern when AI-generated information can be admitted as evidence in federal court — and many state courts where the federal rules are routinely adopted — without a human expert to explain it.
Absent meaningful guardrails, ALPRs — which can effortlessly reconstruct where a person lives, works, shops, socializes, seeks medical care, and more — can be weaponized for pervasive surveillance and misconduct
Fortunately, states are beginning to place sensible and much-needed safeguards on facial recognition. CDT recommends considering several policy priorities to address the risks of misidentification, dragnet surveillance, and other abuse of facial recognition.
