Happy to share that I’m presenting 3 research projects at AIES 2025 🎉 1️⃣Gender bias over-representation in AI bias research 👫 2️⃣Stable Diffusion's skin tone bias 🧑🏻🧑🏽🧑🏿 3️⃣Limitations of human oversight in AI hiring 👤🤖 Let's chat if you’re at AIES or read below/reach out for details! #AIES25 #AcademicSky

🚨New paper: Reward Models (RMs) are used to align LLMs, but can they be steered toward user-specific value/style preferences? With EVALUESTEER, we find even the best RMs we tested exhibit their own value/style biases, and are unable to align with a user >25% of the time. 🧵

🚨New Paper: LLM developers aim to align models with values like helpfulness or harmlessness. But when these conflict, which values do models choose to support? We introduce ConflictScope, a fully-automated evaluation pipeline that reveals how models rank values under conflict. (📷 xkcd)

Honored to be promoted to Associate Professor at the University of Washington! Grateful to my brilliant mentees, students, collaborators, mentors & @techpolicylab.bsky.social for advancing research in AI & Ethics together—and for the invaluable academic freedom to keep shaping trustworthy AI.

🔗 Paper: aclanthology.org/2025.naacl-l... Work done with amazing collaborators @isaacslaughter.bsky.social, @kyrawilson.bsky.social, @aylincaliskan.bsky.social, and @monadiab77.bsky.social! Catch our Oral presentation at Ballroom B, Thursday, May 1st, 14:00-15:30 pm!📷✨

Intrinsic Bias is Predicted by Pretraining Data and Correlates with Downstream Performance in Vision-Language Encoders

Kshitish Ghate, Isaac Slaughter, Kyra Wilson, Mona T. Diab, Aylin Caliskan. Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: ...

aclanthology.org

Excited to announce our #NAACL2025 Oral paper! 🎉✨ We carried out the largest systematic study so far to map the links between upstream choices, intrinsic bias, and downstream zero-shot performance across 131 CLIP Vision-language encoders, 26 datasets, and 55 architectures!

Excited to announce our #NAACL2025 Oral paper! 🎉✨ We carried out the largest systematic study so far to map the links between upstream choices, intrinsic bias, and downstream zero-shot performance across 131 CLIP Vision-language encoders, 26 datasets, and 55 architectures!

🗞️ Hot off the press! 🗞️ @aylincaliskan.bsky.social and I wrote a blog post about how to make resume screening with AI more equitable based findings from our work presented at AIES in 2024. Major takeaways ⬇️ (1/6) www.brookings.edu/articles/gen...

Gender, race, and intersectional bias in AI resume screening via language model retrieval

Kyra Wilson and Aylin Caliskan examine gender, race, and intersectional bias in AI resume screening and suggest protective policies.

brookings.edu

UW’s @techpolicylab.bsky.social and I invite applications for a 2-year Postdoctoral Researcher position in "AI Alignment with Ethical Principles" focusing on language technologies, societal impact, and tech policy. Kindly share! apply.interfolio.com/162834 Priority review deadline: 3/28/2025

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