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Designing AI for Human Agency
About the Talk
In this talk, shared her experience as a design researcher working on an interdisciplinary AI research team to develop innovative AI systems. She discussed how we can build AI that not only pushes the boundaries of technology but also places human agency, safety and fairness front and centre.
The presentation focuses on two project: the first is on a generative AI model designed to support game creators with ideation, enhancing their creative processes through generating consistent, diverse, and user-modifiable gameplay sequences. The second project is a teachable AI system that assists people who are blind or have low vision in locating personal objects, emphasizing the opportunity AI brings to accessibility.
About the Speaker
Linda Wen is a design researcher on the Game Intelligence team at Microsoft Research Redmond. She is passionate about creating safe and responsible AI technology that is accessible to everyone, regardless of their abilities, socioeconomic status, race/ethnicity, gender, or countries of origin.
Currently, Linda leads UX research on an interdisciplinary team focused on developing generative AI models for gaming. She is excited about AI’s potential to empower game creators worldwide, enabling them to tell their unique stories. Previously, she worked on the Teachable AI Experiences team, where she designed personalized accessibility solutions for blind and low-vision users leveraging the power of AI.
Linda holds a Master of Science degree in design engineering from Imperial College London and a Master of Art degree in global innovation design from the Royal College of Art. She studied international relations and linguistics for her undergraduate degree at Pomona College in Los Angeles.
Recommended resources
→Wen, L.Y., Morrison, C., Grayson, M., Marques, R.F., Massiceti, D., Longden, C. and Cutrell, E., 2024, May. Find My Things: Personalized Accessibility through Teachable AI for People who are Blind or Low Vision. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (pp. 1-6). https://dl.acm.org/doi/10.1145/3613905.3648641
→ Kanervisto, A., Bignell, D., Wen, L.Y. et al. World and Human Action Models towards gameplay ideation. Nature 638, 656–663 (2025).
https://www.nature.com/articles/s41586-025-08600-3
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