Autonomous driving paper index
From Passive Tools to Autonomous Teammates: How Agent Reshapes Team Performance through Social Hierarchy Restructuring
One-line summary
As Artificial Intelligence evolves into autonomous agents, understanding how agent autonomy impacts team performance by reshaping social hierarchies is critical.
Engineering notes
Key topics: autonomous driving. See the paper for implementation details and experimental results.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
As Artificial Intelligence evolves into autonomous agents, understanding how agent autonomy impacts team performance by reshaping social hierarchies is critical. This study conducted a code development field experiment spanning 160 team-weeks, combining mixed-effects modeling of varied autonomy modes with qualitative interaction log analysis. Results reveal a dual-pathway mechanism: heightened agent autonomy enhances performance by establishing expert power. Conversely, it elevates agent social status, inducing human blind compliance and reduced engagement, yielding a negative masking effect. Theoretically, this research disentangles expert power from social status, extending social hierarchy logic to human-AI hybrid teams. Practically, organizations must balance agents' professional empowerment with mitigating human cognitive inertia by embedding ultimate gatekeeping responsibilities into workflows.
Links and sources
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