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arXiv 2602.03054cs.HCcs.AIcs.RO
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迈向体贴的具身AI:从抽象概念到高保真原型的多站点医疗机器人协同设计

Towards Considerate Embodied AI: Co-Designing Situated Multi-Site Healthcare Robots from Abstract Concepts to High-Fidelity Prototypes

Cornell Tech / Cornell University(康奈尔科技/康奈尔大学)

Yuanchen Bai, Ruixiang Han, Niti Parikh, Wendy Ju, Angelique Taylor

AI总结:

本文提出通过协同设计方法,从抽象概念到高保真原型,开发多站点医疗机器人,以减少医疗场景中的非增值任务负担。

摘要:

协同设计对于将具身人工智能(AI)系统扎根于现实世界情境至关重要,尤其是在高风险领域如医疗保健中。尽管先前工作探讨了跨学科合作、迭代原型设计以及对非技术人员的支持,但很少有人将这些要素整合到一个持续的协同设计过程中。此类努力通常针对单一情境和低保真阶段,限制了发现的通用性和参与者想法演变的清晰度。为了解决这些限制,我们与22名跨学科参与者进行了为期14周的工作坊,围绕具身AI如何在三个医疗场景中减少非增值任务负担:急诊部门、长期康复设施和睡眠障碍诊所。我们发现,从抽象头脑风暴到高保真原型的迭代进展,通过教育支架的支持,使参与者能够理解现实世界中的权衡并生成更具部署性的解决方案。我们提出了八条协同设计更体贴的具身AI的指导原则:关注情境、响应社会动态、关注期望并扎根于部署。项目页面:https://byc-sophie.github.io/Towards-Considerate-Embodied-AI/

英文摘要:

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, long-term 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. Project Page: https://byc-sophie.github.io/Towards-Considerate-Embodied-AI/

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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