以人为本的人工智能(Dagstuhl Seminar 22262)

Wendy E. Mackay, John Shawe-Taylor, F. V. Harmelen
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引用次数: 0

摘要

本报告记录了Dagstuhl perspective Workshop 22262“以人为本的人工智能”的项目和成果。本次Dagstuhl观点研讨会的目标是为设计和部署以人为中心的混合人工智能系统提供科学和技术基础,这些系统与人类合作,增强人类的能力,而不是取代人类的智能。从根本上说,人工智能和人机交互(HCI)的核心研究问题需要新的解决方案,特别是帮助人们理解人工智能系统建议或执行的操作,并促进人与人工智能系统之间有意义的交互。具体的挑战包括:学习复杂的世界模型;构建有效且可解释的机器学习系统;发展人控智能系统;使人工智能系统适应动态的、开放式的现实世界环境(特别是机器人和自主系统);实现对人类和复杂社会环境的深入理解;并在人工智能系统中实现自我反思。研讨会2022年6月26日至7月1日- http://www.dagstuhl.de/22262 2012 ACM主题分类以人为中心计算→人机交互(HCI);以人为本→交互设计;计算数学→概率统计;计算理论→概率计算;计算理论→自动推理;计算理论→约束与逻辑规划计算理论→机器学习理论;计算理论→算法博弈论与机制设计计算方法→人工智能;计算方法→机器学习
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Human-Centered Artificial Intelligence (Dagstuhl Seminar 22262)
This report documents the program and the outcomes of Dagstuhl Perspectives Workshop 22262 “Human-Centered Artificial Intelligence”. The goal of this Dagstuhl Perspectives Workshops is to provide the scientific and technological foundations for designing and deploying hybrid human-centered AI systems that work in partnership with human beings and that enhance human capabilities rather than replace human intelligence. Fundamentally new solutions are needed for core research problems in AI and human-computer interaction (HCI), especially to help people understand actions recommended or performed by AI systems and to facilitate meaningful interaction between humans and AI systems. Specific challenges include: learning complex world models; building effective and explainable machine learning systems; developing human-controllable intelligent systems; adapting AI systems to dynamic, open-ended real-world environments (in particular robots and autonomous systems); achieving in-depth understanding of humans and complex social contexts; and enabling self-reflection within AI systems. Seminar June 26–July 1, 2022 – http://www.dagstuhl.de/22262 2012 ACM Subject Classification Human-centered computing → Human computer interaction (HCI); Human-centered computing → Interaction design; Mathematics of computing → Probability and statistics; Theory of computation → Probabilistic computation; Theory of computation → Automated reasoning; Theory of computation → Constraint and logic programming; Theory of computation → Machine learning theory; Theory of computation → Algorithmic game theory and mechanism design; Computing methodologies → Artificial intelligence; Computing methodologies → Machine learning
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