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通过功能与示例勾勒人工智能概念:重症监护病房中的人工智能创新

Sketching AI Concepts with Capabilities and Examples: AI Innovation in the Intensive Care Unit.

作者信息

Yildirim Nur, Zlotnikov Susanna, Sayar Deniz, Kahn Jeremy M, Bukowski Leigh A, Amin Sher Shah, Riman Kathryn A, Davis Billie S, Minturn John S, King Andrew J, Ricketts Dan, Tang Lu, Sivaraman Venkatesh, Perer Adam, Preum Sarah M, McCann James, Zimmerman John

机构信息

Carnegie Mellon University, Pittsburgh, PA, USA.

Izmir University of Economics, Izmir, Turkey.

出版信息

Proc SIGCHI Conf Hum Factor Comput Syst. 2024 May;2024. doi: 10.1145/3613904.3641896. Epub 2024 May 11.

Abstract

Advances in artificial intelligence (AI) have enabled unprecedented capabilities, yet innovation teams struggle when envisioning AI concepts. Data science teams think of innovations users do not want, while domain experts think of innovations that cannot be built. A lack of effective ideation seems to be a breakdown point. How might multidisciplinary teams identify buildable and desirable use cases? This paper presents a first hand account of ideating AI concepts to improve critical care medicine. As a team of data scientists, clinicians, and HCI researchers, we conducted a series of design workshops to explore more effective approaches to AI concept ideation and problem formulation. We detail our process, the challenges we encountered, and practices and artifacts that proved effective. We discuss the research implications for improved collaboration and stakeholder engagement, and discuss the role HCI might play in reducing the high failure rate experienced in AI innovation.

摘要

人工智能(AI)的进步带来了前所未有的能力,但创新团队在构思人工智能概念时却面临困难。数据科学团队想到的创新并非用户所需,而领域专家想到的创新又无法实现。缺乏有效的构思似乎是一个瓶颈。多学科团队如何才能识别出可构建且受欢迎的用例呢?本文介绍了构思人工智能概念以改善重症医学的第一手经验。作为一个由数据科学家、临床医生和人机交互(HCI)研究人员组成的团队,我们开展了一系列设计研讨会,以探索更有效的人工智能概念构思和问题制定方法。我们详细介绍了我们的过程、遇到的挑战以及被证明有效的实践和工件。我们讨论了对改善协作和利益相关者参与的研究意义,并探讨了人机交互在降低人工智能创新中高失败率方面可能发挥的作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a7d1/12247186/b50b87333731/nihms-2091611-f0001.jpg

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