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Grand Challenges

Grand Challenge 1

How do we design AI in a way that is transparent and equally beneficial to all?

AI has the potential to increase productivity, enhance creativity, and accelerate discovery. It also has the potential to generate unintended consequences for individuals and communities who don’t fit a default user profile.

AI is already transforming the way many organizations and people work in Washington state owing to the concentration of companies at the forefront of AI development, and the trend is expected to spread. Allen School researchers are advancing the state of the art in AI research with an emphasis on open source, open data, and open processes, to enable both deeper, broader scientific understanding and broader participation in designing AI for the needs and preferences of different populations — while mitigating potential harms.


Faculty Meeting the Challenge

Professor


Computational Biology; Explainable AI; Machine Learning

Associate Professor


Generative AI; Knowledge Representation & Reasoning; Machine Learning; Natural Language Processing

Assistant Professor


Generative AI; Human-Centered AI; Machine Learning; Natural Language Processing

Professor


Machine Learning; Natural Language Processing

Associate Professor


Computing Education Research; Fabrication; Human-Centered AI; Human-Computer Interaction

Professor


Natural Language Processing

Associate Professor


Ethics & Fairness; Human-Centered AI; Natural Language Processing

Professor


Augmented, Virtual & Mixed Reality; Human-Computer Interaction; Security & Privacy

Associate Professor


Human-Centered AI; Human Computer Interaction; Social Computing

Assistant Professor


Explainable AI; Generative AI; Machine Learning; Natural Language Processing

Professor


Ethics & Fairness; Human-Centered AI; Human-Computer Interaction

Professor


Accessibility; Ethics & Fairness; Fabrication; Human-Computer Interaction; Ubiquitous Computing, Sensing & Embedded Systems

Assistant Professor


Computer Vision; Human-Centered AI; Machine Learning; Natural Language Processing; Robotics


Collaborators & Partner Institutions


Selected Projects

Culturally-attuned AI: Implicit learning of altruistic cultural values through inverse reinforcement learning

Nigini Oliveira, Jasmine Li, Koosha Khalvat, Rodolfo Cortes Barragan, Katharina…

CREATE awarded $4.6M for research on AI risks, opportunities for people with disabilities

This grant investigates bias, privacy, and security risks when GAI is used …

Digital Culture Shock: Who Creates Technology and Why This Matters

Katharina Reinecke, Princeton University Press, 2025. …

OLMo: Accelerating the Science of Language Models

Dirk Groeneveld, Iz Beltagy, Pete Walsh, Akshita Bhagia, Rodney Kinney…

2 OLMo 2 Furious

OLMo Team, Evan Pete Walsh, Luca Soldaini, Dirk Groeneveld, Kyle Lo, Shane Arora…

Tulu 3: Pushing Frontiers in Open Language Model Post-Training

Nathan Lambert, Jacob Morrison, Valentina Pyatkin, Shengyi Huang, Hamish Ivison…