arXiv:2606.09833v1 Announce Type: cross Abstract: AI agents are reshaping the workspace, leading to drastic change of how humans work. Despite the considerable potential of human-agent collaboration both in preserving human agency and generating economic value, this paradigm remains largely absent from occupational task evaluation, hindered by the difficulty of gathering real human data and accounting for inter-human variability. We introduce CollabSkill, a framework for evaluating human-agent collaboration on real-world occupational tasks. CollabSkill pairs real human workers with AI agents o
The rapid advancement and integration of AI agents into workflows necessitates robust evaluation frameworks to understand their efficacy and impact on human-agent collaboration.
A strategic reader needs to understand how AI agents will reshape human work, what methodologies are being developed to assess their effectiveness, and the implications for productivity and economic value.
This framework provides a structured approach to evaluate human-agent collaboration in real-world professional tasks, moving beyond theoretical discussions to empirical measurement of performance.
- · AI Agent developers
- · Organizations adopting AI agents
- · Human-computer interaction researchers
- · Traditional task automation software
- · Companies unable to integrate AI meaningfully
Improved design and deployment of AI agents based on empirical collaboration data.
Increased efficiency and output in white-collar sectors due to optimized human-agent teams.
New regulatory and societal frameworks may emerge to manage human-agent collaborative work dynamics and job displacement.
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Read at arXiv cs.AI