Abstract
Co-design is essential for grounding embodied artificial intelligence (AI) systems in real-world contexts, especially high-stakes domains such as healthcare. While prior work has explored multidisciplinary collaboration, iterative prototyping, and support for non-technical participants, few have interwoven these into a sustained co-design process. Such efforts often target one context and low-fidelity stages, limiting the generalizability of findings and obscuring how participants' ideas evolve. To address these limitations, we conducted a 14-week workshop with a multidisciplinary team of 22 participants, centered around how embodied AI can reduce non-value-added task burdens in three healthcare settings: emergency departments, rehabilitation facilities, and sleep disorder clinics. We found that the iterative progression from abstract brainstorming to high-fidelity prototypes, supported by educational scaffolds, enabled participants to understand real-world trade-offs and generate more deployable solutions. We propose eight guidelines for co-designing more considerate embodied AI: attuned to context, responsive to social dynamics, mindful of expectations, and grounded in deployment.
Video Presentation
BibTeX
@inproceedings{bai2026towards,
title={Towards considerate embodied ai: Co-designing situated multi-site healthcare robots from abstract concepts to high-fidelity prototypes},
author={Bai, Yuanchen and Han, Ruixiang and Parikh, Niti and Ju, Wendy and Taylor, Angelique},
booktitle={Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems},
pages={1--24},
year={2026}
}