计算机支持的协同工作
工作流程
愿景
计算机科学
任务(项目管理)
知识管理
工作(物理)
透视图(图形)
平面图(考古学)
数据科学
万维网
人工智能
工程类
社会学
历史
机械工程
考古
数据库
人类学
系统工程
作者
Dakuo Wang,Elizabeth F. Churchill,Pattie Maes,Xiangmin Fan,Ben Shneiderman,Yuanchun Shi,Li Wang
出处
期刊:Human Factors in Computing Systems
日期:2020-04-25
被引量:115
标识
DOI:10.1145/3334480.3381069
摘要
Artificial Intelligent (AI) and Machine Learning (ML) algorithms are coming out of research labs into the real-world applications, and recent research has focused a lot on Human-AI Interaction (HAI) and Explainable AI (XAI). However, Interaction is not the same as Collaboration. Collaboration involves mutual goal understanding, preemptive task co-management and shared progress tracking. Most of human activities today are done collaboratively, thus, to integrate AI into the already-complicated human workflow, it is critical to bring the Computer-Supported Cooperative Work (CSCW) perspective into the root of the algorithmic research and plan for a Human-AI Collaboration future of work. In this panel we ask: Can this future for trusted human-AI collaboration be realized? If so, what will it take? This panel will bring together HCI experts who work on human collaboration and AI applications in various application contexts, from industry and academia and from both the U.S. and China. Panelists will engage the audience through discussion of their shared and diverging visions, and through suggestions for opportunities and challenges for the future of human-AI collaboration.
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