Human-Centered Human-AI Collaboration (HCHAC)

TL;DR

This paper explores the emerging paradigm of human-centered human-AI collaboration, emphasizing human leadership, reviewing current research, proposing a framework, and illustrating practical applications like autonomous vehicles.

Contribution

It introduces a comprehensive framework for human-centered HAC, integrating research insights and providing a case study in autonomous vehicles to guide future developments.

Findings

Framework for human-centered HAC proposed

Case study demonstrates practical application in autonomous vehicles

Highlights future research directions in ethics and reliability

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.