Tech Talk: Fairness in Algorithms and Privacy-Smart Wearable Companies
CDT’s Tech Talk is a podcast where we dish on tech and Internet policy, while also explaining what these policies mean to our daily lives. You can find Tech Talk on SoundCloud and on iTunes.
When exploring the intersection of technology and society, the terms fairness, ethics, and privacy are among the most commonly used. This episode of Tech Talk is no exception.
Ali Lange and Gautam Hans join me to talk about a paper they are working on with the UC Berkeley School for Information that that addresses algorithmic fairness, specifically what people think is fair in terms of the automated decisions made about them online.
I also get to talk to the always charming Michelle De Mooy about a report she collaborated with Fitbit on. The report explores how privacy and ethics can be embedded into the research and development process at innovative health wearable companies. With more and more people tracking their steps, privacy-smart wearable companies would definitely be an important step forward for protection of our personal data.
CDT Comment Welcomes NIST Effort to Develop Zero Draft
Drawing on CDT’s previous comments on this NIST effort and our prior research on documentation, our submission welcomes NIST’s effort to develop the zero draft, which provides a much-needed step toward more standardized, high-quality guidance on how developers of AI system components should document key properties and potential sources of AI risk. This guidance will be a valuable resource for organizations to improve interoperability, build more performant AI products, and more effectively identify and mitigate AI risks.
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.
