Algorithmic Fragility: How Organizations Stabilize Unstable Machines

Summary

This paper introduces algorithmic fragility, the persistent instability of AI systems in organizational settings, framed as a structural condition rather than a temporary defect. It proposes stabilization work, the distributed labor organizations use to absorb and manage algorithmic breakdowns, and identifies three micro-level practices: buffering, reframing, and patching.