Organization Matters: A Qualitative Study of Organizational Dynamics in Red Teaming Practices For Generative AI
Bixuan Ren, Eunjeong Cheon, Jianghui Li
Abstract
The rapid integration of generative artificial intelligence (GenAI) across diverse fields underscores the critical need for red teaming efforts to proactively identify and mitigate associated risks. While previous research primarily addresses technical aspects, this paper highlights organizational factors that hinder the effectiveness of red teaming in real-world settings. Through qualitative analysis of 17 semi-structured interviews with red teamers from various organizations, we uncover challenges such as the marginalization of vulnerable red teamers, the invisibility of nuanced AI risks to vulnerable users until post-deployment, and the lack of user-centered red teaming approaches. These issues often arise from underlying organizational dynamics, including organizational resistance, organizational inertia, and organizational mediocracy. To mitigate these dynamics, we discuss the implications of user research for red teaming and the importance of embedding red teaming throughout the entire development cycle of GenAI systems.
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