Hannah Bloch-Wehbais an Assistant Professor of Law at Drexel University Kline School of Law. She is also one of CDT’s non-resident Fellows, engaging with our policy teams to provide valuable insights. In this Q & A we get to learn more about Hannah and her current work.
Why did you become a CDT fellow?
I became a fellow to engage with CDT on cutting-edge issues related to free expression, privacy, and surveillance, and to be a part of a community focused on the real-world applications of academic research in law and policy.
What is your current research focus?
I’m writing about the challenges that algorithmic decisionmaking poses to civil liberties, accountability, and transparency.
What is the most pressing internet policy question of today?
How should we ensure that automated decisionmaking is explainable, accountable, and fair?
What issues do you think more students should be studying?
More students who study technology should learn about criminal justice and immigration, because it is in these environments that new “innovations” in surveillance and law enforcement are often first introduced. The converse is equally true: students who study criminal justice and immigration should study the role of technology in altering and amplifying the power of law enforcement and surveillance.
What advice do you have for aspiring tech & internet academics?
This community is both generous and tightly knit. Don’t be shy, reach out! I benefited greatly from the advice of folks who came before me, and most of us are eager to pay it forward.
What’s a passion or hobby you have outside of tech & the internet?
I love elaborate cooking and baking projects, am an avid runner, and am learning to throw pots.
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.
