Allen School researchers are at the forefront of exciting developments in AI spanning machine learning, computer vision, natural language processing, robotics and more.
We cultivate a deeper understanding of the science and potential impact of rapidly evolving technologies, such as large language models and generative AI, while developing practical tools for their ethical and responsible application in a variety of domains — from biomedical research and disaster response, to autonomous vehicles and urban planning.
Groups & Labs
Behavioral Data Science Group
The Behavioral Data Science Group leverages large-scale behavioral data to extract actionable insights about our lives, health and happiness by combining techniques from data science, social network analysis, and natural language processing.
Social RL Lab
The Social RL Lab aims to leverage social information in human-AI and multi-agent interactions to enable AI to learn complex behavior, rapidly adapt to new circumstances and cooperate to achieve joint goals—similarly to how humans and animals learn.
Faculty Members
Centers & Initiatives
IFDS organizes its research around four core themes: complexity, robustness, closed-loop data science, and ethics and algorithms. By making concerted progress on these fundamental fronts, IFDS aims to lower several of the barriers to better understanding of data science methodology and to its improved effectiveness and wider relevance to application areas.
The Tech Policy Lab is a unique, interdisciplinary collaboration at the University of Washington that aims to enhance technology policy through research, education, and thought leadership. Founded in 2013 by faculty from the Paul G. Allen School of Computer Science & Engineering, Information School, and School of Law, the Lab aims to bridge the gap between technologists and policymakers and to help generate wiser, more inclusive tech policy.
Highlights
Allen School News
Asai (Ph.D., ‘25), research scientist at Ai2 and incoming faculty at Carnegie Mellon University, was recognized for her pioneering research that has helped establish the foundations for retrieval-augmented generation (RAG) and showcase its effectiveness at reducing LLM hallucinations.
Allen School News
Allen School researchers earned multiple awards at the 63rd Annual Meeting of the Association for Computational Linguistics for laying the foundation for how AI systems understand and follow human instructions, exploring how LLMs pull responses from their training data, and more.
UW News
In her new book “Digital Culture Shock: Who Creates Technology and Why This Matters,” Reinecke examines how culture shapes the design and use of technology — and why we should resist a one-size-fits-all approach.