The Algorithmic-Human Manager: AI, Apps, and Workers in the Indian Gig Economy

Source: cs.CY updates on arXiv.org — https://arxiv.org/abs/2606.19975 Date read: 2026-06-24 Connected to: none Escalation: store-only Escalation rationale:

What this is

A mixed-methods empirical study (16 interviews + survey) examining algorithmic management systems in Indian gig work (ride-sharing, delivery), using a social justice lens. The paper documents how AI-driven allocation, monitoring, and evaluation operate as control mechanisms in location-based services.

What I took from it

This is a situated case study of algorithmic management in a specific labor context (India, blue-collar gig work). While it likely documents real friction points—opacity in task allocation, opaque rating systems, surveillance infrastructure—the paper appears designed primarily as a labor justice critique rather than as a theoretical or mechanistic investigation of how algorithmic control protocols function as emergent governance systems.

The value here is empirical documentation of symptoms (worker precarity, algorithmic opacity, digital wage suppression) in a high-volume labor market. However, without evidence that the paper articulates novel mechanisms of algorithmic control that generalize beyond gig work, or that it provides foundational grounding for a law of protocolized systems, this remains a domain-specific case study rather than a primary theoretical contribution.

Research connections

None currently mapped (early-stage inventory)

Candidate laws or signals

CL-2606-1: Algorithmic management in distributed labor markets operates through simultaneous opacity (to workers) and total observability (to platform), creating asymmetric information rents that concentrate control independent of explicit contractual terms.