Papers for

workplace ai designers

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

Workers share expertise differently when AI reuses their knowledge

When My Skill Becomes Agent Skill: How Knowledge Workers Share Their Expertise with AI Systems

Abstract: Organizations have long sought to make workers' expertise reusable by others. Agentic AI changes the nature of such reuse by enabling AI systems to act on workers' knowledge with limited human involvement. This raises the question of how this shift shapes workers' willingness to share their expertise. We conducted an experiment with knowledge workers who created materials incorporating domain knowledge and decided whether to authorize human or AI reuse. We find that AI and human reuse differ primarily in whether workers choose to share their knowledge, rather than in what they choose to share. Participants' reasoning shifts from prosocial considerations when sharing with humans toward concerns about loss of control, replacement, and downstream governance when sharing with AI. These findings suggest that AI reuse may intensify tensions between organizational knowledge reuse and contributors' interests. We discuss implications for workplace AI and knowledge management policies that preserve workers' rights and agency.

Wed 7 OctHuman-Computer Interaction
The gist
Sharing knowledge at work is different when AI systems use that knowledge instead of humans. The authors studied how people feel about letting AI or humans reuse their expertise. They found that workers worry more about losing control or being replaced when AI reuses their knowledge, while sharing with humans feels more about helping others. This could make sharing knowledge with AI more complicated in workplaces.
Open → 2610.09608v1