Problem
Research questions and friction points this paper is trying to address.
Human-Agent Collaboration
Workplace Value of AI
Workflow Augmentation
When Does AI Augment Work? A Workflow-Level Framework for Human-Agent Collaboration
🤖 AI Summary
本文通过建立一个包含六个条件的框架，探讨了AI如何增强未来的工作流程，以解决当前研究忽视的人机协作对工作性质转变的影响。
📝 Abstract
We aim to characterise the value of artificial intelligence in the workplace. Current studies largely measure this value in terms of the current automation capabilities and public adoption of AI. However, such metrics ignore the greater impacts of human--agent collaboration in transforming the nature of work. To account for this, we must expand the scope of our analysis beyond atomised tasks of today, and instead focus on how AI can augment entire workflows of the future. To ground this analysis, we establish a precise definition of AI augmentation comprising six conditions, spanning durable net value, meaningful human control, accountability and recovery, and long-term human development through learning, career pathways, and job purpose. We elaborate on these conditions and apply the framework in a case study of AI-mediated social surveys. We conclude by outlining how organisations, researchers, and government leaders can use this framework to make sense of the future of work.
Innovation
Methods, ideas, or system contributions that make the work stand out.
human-agent collaboration
workflow-level framework
AI augmentation
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