Human-Centered Human-AI Collaboration (HCHAC)

• URL: http://arxiv.org/abs/2505.22477v1
• Date: Wed, 28 May 2025 15:27:52 GMT
• Title: Human-Centered Human-AI Collaboration (HCHAC)
• Authors: Qi Gao, Wei Xu, Hanxi Pan, Mowei Shen, Zaifeng Gao,
• Abstract summary: Human-AI Collaboration (HAC) represents a novel type of human-machine relationship facilitated by AI technologies.<n>Human-centered AI (HCAI) emphasizes that humans play critical leadership roles in the collaboration.<n>This chapter delves into the essence of HAC from the human-centered perspective, outlining its core concepts and distinguishing features.
• Score: 9.14056952246194
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In the intelligent era, the interaction between humans and intelligent systems fundamentally involves collaboration with autonomous intelligent agents. Human-AI Collaboration (HAC) represents a novel type of human-machine relationship facilitated by autonomous intelligent machines equipped with AI technologies. In this paradigm, AI agents serve not only as auxiliary tools but also as active teammates, partnering with humans to accomplish tasks collaboratively. Human-centered AI (HCAI) emphasizes that humans play critical leadership roles in the collaboration. This human-led collaboration imparts new dimensions to the human-machine relationship, necessitating innovative research perspectives, paradigms, and agenda to address the unique challenges posed by HAC. This chapter delves into the essence of HAC from the human-centered perspective, outlining its core concepts and distinguishing features. It reviews the current research methodologies and research agenda within the HAC field from the HCAI perspective, highlighting advancements and ongoing studies. Furthermore, a framework for human-centered HAC (HCHAC) is proposed by integrating these reviews and analyses. A case study of HAC in the context of autonomous vehicles is provided, illustrating practical applications and the synergistic interactions between humans and AI agents. Finally, it identifies potential future research directions aimed at enhancing the effectiveness, reliability, and ethical integration of human-centered HAC systems in diverse domains.

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