Governing platform work in India: A risk matrix approach to tackling algorithmic arbitrage in line with the SDGs

Abstract

This paper analyzes the overlap of algorithmic management with the governance of labor in the platform (gig) economy of India, where the rapid pace of platformization has led to lagging legal frameworks. It examines the strategic use of legal ambiguities by digital labor platforms, or algorithmic regulatory arbitrage, and aims to identify major regulatory blind spots in existing labor regulation. The goal is to develop a comprehensive framework to guide legal reforms, institutional monitoring, and accountability of platforms. The research employs a combination of methods, including interviews with 273 stakeholders and the analysis of legal documents using NVivo, along with non-parametric statistical tests such as the Kruskal-Wallis and Chi-square tests. A Regulatory Risk Matrix Framework is created to evaluate the seriousness and likelihood of legal issues in five areas: worker classification, algorithm transparency, fairness in processes, welfare benefits, and dispute resolution. The study reveals significant legal and institutional gaps, particularly in worker classification and transparency in algorithmic control systems, enabling platforms to evade responsibility. Systematic procedural unfairness, exclusion from welfare schemes, and defective dispute resolution processes are identified through stakeholder responses. The matrix analysis indicates that worker classification and dispute resolution are critical areas, with a notable misalignment between central and state enforcement mechanisms. The concept of algorithmic regulatory arbitrage serves as a useful tool for explaining how platforms engineer compliance evasion. This paper makes an original contribution by integrating doctrinal, empirical, and strategic management perspectives into a jurisdiction-specific regulatory risk assessment. Unlike generic critiques of platform work, the study offers a tailored, actionable framework for Indian policymakers, regulators, and platform managers. It also advances methodological approaches by combining stakeholder perceptions with legal diagnostics to foster interdisciplinary scholarship in algorithmic governance and labor regulation. Additionally, this study aligns with SDG 8 (Decent Work and Economic Growth) and SDG 10 (Reduced Inequalities) by addressing regulatory mechanisms that can mitigate precarity and exclusion in algorithmically managed platform work in India.