文章摘要
孙效华,张义文,秦觉晓,李璟璐,王舒超.人机智能协同研究综述[J].包装工程,2020,41(18):1-11.
人机智能协同研究综述
Review on Human-Intelligent System Collaboration
投稿时间:2020-04-15  修订日期:2020-09-20
DOI:10.19554/j.cnki.1001-3563.2020.18.001
中文关键词: 人工智能  智能系统  人机交互  人机智能协同  技术视角  体验视角
英文关键词: artificial intelligence  intelligent system  human-computer interaction  human-intelligent system collabo-ration  technology-centric perspective  experience-centric perspective
基金项目:
作者单位
孙效华 同济大学上海 200092 
张义文 同济大学上海 200092 
秦觉晓 同济大学上海 200092 
李璟璐 同济大学上海 200092 
王舒超 同济大学上海 200092 
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中文摘要:
      目的 智能系统在智能制造、智慧城市、医疗健康、生活服务等各种场景中越来越广泛地存在,为应对人与智能系统的交互中所面临的诸多挑战,从技术和体验的视角分析人机智能协同中的关键问题。方法 对从人机交互到人机智能协同的发展脉络与研究范围进行梳理,提出综合技术视角和体验视角的研究框架;从智能系统的特征出发,梳理出技术视角下人机智能协同所带来的新兴问题;从体验的视角探讨如何推动实现人机智能协同;在此基础上总结人机智能协同的发展趋势。结论 总结了人机交互演进的三个阶段;提出了技术视角下人机智能协同的关键问题,包括人机能动性分配、动态学习和修正、情境自适应及主动响应模式;探讨了体验视角下人机智能协同的可解释性、信任问题、情感化及公平负责等问题;指出了人机智能协同全方位、多类型及体系化的发展趋势。
英文摘要:
      Intelligent system will exist widely in the future life and work. This work aims to analyze key issues in human-intelligent system collaboration from both technology-centric and experience-centric perspectives, to deal with the challenges in interactions between human and intelligent system. This work combed the evolution and research scope from human-computer interaction to human-intelligent system collaboration, and put forward a comprehensive research framework from both technology-centric and experience-centric perspectives. From the features of intelligent system, emerging problems brought by human-intelligent system collaboration were proposed, and the ways for promoting hu-man-intelligent system collaboration were discussed from experience-centric perspective. Future trends of human-intelligent system collaboration were summarized on this basis. A three-stage framework of human- computer interaction evolution is proposed. Key issues in human-intelligent system collaboration from technology-centric perspective are concluded, including degree of agency, adaptive learning and correction, context-sensitive and proactive interaction. Experience-centric issues like explainability, trust, affective interaction, fairness and accountability are discussed. Trends of human-intelligent system collaboration are described as comprehensive, diverse, and systematic.
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