Algorithmic management

Algorithmic management uses computer-programmed procedures to coordinate and control labor through automated systems. Platforms like Uber, DoorDash, and Grab employ algorithms to handle management functions including task assignment, pricing, performance monitoring, and quality control. These systems process vast amounts of data to match workers with tasks, calculate dynamic pricing, track worker performance in real-time, and enforce compliance through ratings and penalties.

Algorithms decide which worker receives which task based on factors like location, performance history, and acceptance rates. They monitor completion times, track routes, and evaluate worker behavior continuously. For example, delivery platforms use algorithms to calculate optimal delivery times and penalize workers who take too long, while ride-hailing apps algorithmically assign trips and adjust prices based on demand.

However, algorithmic management creates opacity and power imbalances. Workers often cannot see how decisions are made, what factors affect their rankings, or why they receive certain tasks. This lack of transparency makes it difficult for workers to improve performance, challenge unfair decisions, or understand sudden changes in earnings. The automated nature also removes human judgment and context from management decisions, affecting worker autonomy and well-being.