Human GenAI collaboration shows unique memory and trust patterns
The GenAI Who Knew Too Little: Revisiting Transactive Memory Systems in Human GenAI Collaboration
Human-Computer InteractionComputers and Society
Summary
Working together with generative AI changes how people share knowledge and trust each other. The study found that humans understand what AI is good at, but AI only briefly remembers human skills. People partly trust AI but always double-check its outputs. Also, humans lead the interaction while AI mostly follows orders. The researchers say existing ideas about shared memory systems need adjusting to fit human-AI teamwork.
What this means in practice
- •For knowledge worker teams: Design collaboration practices that account for AI's limited memory and trust patterns in mixed human-AI teams.
- •For ai interface designers: Create AI systems with clearer indicators of confidence and capability to improve human trust and interaction flow.
Authors
Christian Meske, Tobias Hermanns, Florian Brachten
Abstract
Generative artificial intelligence (GenAI) is rapidly transforming knowledge work, creating new collaborative dynamics that challenge tradi-tional human-human interaction patterns. This study investigates how Transactive Memory Systems (TMS) manifest in human-GenAI collabora-tion. Through qualitative interpretive interviews with 14 knowledge work-ers and thematic analysis, we identified distinct TMS manifestations across its three main dimensions: (1) regarding specialization, expertise recogni-tion exhibited asymmetry. Humans developed awareness of GenAI capabili-ties while GenAI demonstrated only temporary recognition of human exper-tise; (2) in terms of credibility, humans formed ambivalent trust relation-ships with GenAI, simultaneously attributing expertise to the latter while implementing additional verification processes; and (3) concerning coor-dination, where humans primarily directed more passive GenAI systems lacking initiative, resulting in hierarchical interaction patterns and unidi-rectional information flow. Our findings reveal that TMS manifests differ-ently in human-GenAI compared to human-human collaboration, necessitat-ing theoretical adaptations including trust markers, acknowledging GenAI's absent metamemory, and identifying its temporary memory.