Algorithmic Harms to Workers in the Platform Economy: The Case of Uber

By Zane Muller

Technological change has given rise to the much-discussed “gig” or “platform economy,” but labor law has yet to catch up. Platform firms, most prominently Uber, use machine learning algorithms processing torrents of data to power smartphone apps that promise efficiency, flexibility, and autonomy to users who both deliver and consume services. These tools give firms unprecedented information and power over their services, yet they are little-examined in legal scholarship, and case law has yet to meaningfully address them. The potential for exploitation of workers is immense, however the remedies available to workers who are harmed by algorithm design choices are as yet undeveloped.

This Note analyzes a set of economic harms to workers uniquely enabled by algorithmic work platforms and explores common law torts as a remedy, using Uber and its driver-partners as a case study. Part II places the emerging “platform economy” in the context of existing labor law. Part III analyzes the design and function of machine learning algorithms, highlighting the Uber application. This Part of the Note also examines divergent incentives between Uber and its users alongside available algorithm design choices, identifying potential economic harms to workers that would be extremely difficult for workers to detect. Part IV surveys existing proposals to protect platform workers and offers common law causes of action sounding in tort and contract as recourse for workers harmed by exploitative algorithm design.

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