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And also excited to share our tutorial — on ACLU’s approach to evaluating generative AI’s implications for our work — with @techforimpact.bsky.social @bmad.bsky.social Ranya Ahmed and Evani Radiya-Dixit, also on Wednesday, at 5 PM Athens time programs.sigchi.org/facct/2025/p...

This work was the product of an amazing collaboration across civil society and academia — with a stellar team including @rone.bsky.social and @metaxa.net (Penn HCI), Cole Tanigawa-Lau (Stanford), Lena Armstrong (Harvard) and Ana Gutiérrez (my colleague at ACLU!)

The role is paid, open to graduate and undergraduate students, and available for remote or hybrid work from our NYC or DC office. The priority application deadline is February 25 — please share widely!

This is a unique opportunity to conduct applied research (our team regularly publishes at conferences like ACM FAccT, for instance) that will shape our approach to leveraging emerging technologies in line with our values.

Projects will be tailored to the intern’s skillset and interests, and could range from adapting cutting edge research on bias testing of large language models (LLMs) to develop a model-agnostic testing and evaluation toolkit, to conducting a landscape analysis of open weight model offerings.

For this position, we welcome applicants with backgrounds in technical fields (e.g., engineering, ML, AI, NLP, statistics) and applicants with backgrounds in sociotechnical fields (e.g., history of science, history of technology, HCI, information science, science and technology studies, sociology).

We believe this body of work will help us begin to incorporate this technology into our work so that it creates, rather than risks or diminishes value. For more info, read about our approach and follow @techforimpact.bsky.social @bmad.bsky.social!

technicallyoptimistic.substack.com/p/procedures...

To stay up to date with emerging research in this area, we formed a reading group open to anyone at the ACLU—including staff at our 54 affiliates across the country—that shares and discusses emerging research about gen AI (including research papers, model cards, articles, and other explainers).

To operationalize the principles, we created a product focused on procurement of Gen AI tools: a seven-page questionnaire that covers risks related to security, privacy, bias, copyright and accuracy. We ask vendors to explain what they’re doing with gen AI and hold them accountable to their answers.