Human-Centered Human-AI Collaboration (HCHAC)
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 17 of its 136 references that are in the map. First posted on arXiv 28 May 2025.
Builds on
17 of 136 references.
References · 17
- 2017Explanation in Artificial Intelligence: Insights from the Social Sciencescited by 1,206
- 2020Artificial Intelligence, Values and Alignmentcited by 448
- 2018Machine Theory of Mindcited by 226
- 2020Human-Centered Artificial Intelligence: Reliable, Safe & Trustworthycited by 183
- 2024When combinations of humans and AI are useful: A systematic review and meta-analysiscited by 106
- 2022"Help Me Help the AI": Understanding How Explainability Can Support Human-AI Interactioncited by 63
- 2017Cooperating with Machinescited by 39
- 2021The future of human-AI collaboration: a taxonomy of design knowledge for hybrid intelligence systemscited by 39
- 2023Human-AI collaboration is not very collaborative yet: A taxonomy of interaction patterns in AI-assisted decision making from a systematic reviewcited by 18
- 2024Explainable AI improves task performance in human-AI collaborationcited by 12
- 2025Value Compass Benchmarks: A Platform for Fundamental and Validated Evaluation of LLMs Valuescited by 7
- 2024Levels of AI Agents: from Rules to Large Language Modelscited by 6
5 more
- 2024Evaluating and Modeling Social Intelligence: A Comparative Study of Human and AI Capabilitiescited by 6
- 2021Human-AI interaction: An emerging interdisciplinary domain for enabling human-centered AIcited by 3
- 2023Agent Teaming Situation Awareness (ATSA): A Situation Awareness Framework for Human-AI Teamingcited by 3
- 2022New research paradigms and agenda of human factors science in the intelligence eracited by 2
- 2023Applying HCAI in developing effective human-AI teaming: A perspective from human-AI joint cognitive systemscited by 2
Built on by
Not cited yet.