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Exploring the Future of Human-AI Collaboration: Insights from "Human-AI Interaction and Collaboration"

Authors: Dan Wu; Shaobo Liang;

Exploring the Future of Human-AI Collaboration: Insights from "Human-AI Interaction and Collaboration"

Abstract

How should people and AI work together in ways that are useful, ethical, and trustworthy? Edited by Dan Wu and Shaobo Liang (Wuhan University), “Human–AI Interaction and Collaboration” maps the fast-moving terrain where users, systems, and information meet—treating human strengths and machine strengths as complements, not substitutes. The introduction frames collaboration as a user-centered endeavor that must balance capability with ethics, transparency, and trust.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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