Balancing the Books and the Backseat: Algorithmic Managemen…

Abstract India's vision of Viksit Bharat @2047 rests significantly on harnessing Artificial Intelligence (AI) to power an inclusive digital economy, with the gig and platform sector projected to grow from 7.7 million workers in 2020-21 to 23.5 million by 2029-30 [1]. Within this expanding workforce lies an under-documented segment: college students who work as ride-hailing drivers and delivery partners for platforms such as Uber, Ola, Rapido, Swiggy, and Zomato alongside their academic commitments. While the Code on Social Security, 2020, operationalised through Rules notified in 2025-26, extends formal welfare recognition to gig and platform workers for the first time, it remains largely silent on the algorithmic mechanisms, dynamic pricing, rating-based deactivation, and automated task allocation, that govern their day-to-day work experience, a gap well documented in the international algorithmic-management literature [2], [3], [4]. This paper examines the intersection of AI-driven algorithmic management and worker welfare policy through a mixed-methods approach: a review of the current regulatory framework combined with primary survey data (n = 18) collected from college students in Coimbatore district engaged in gig work. The findings show that a majority of respondents report unpredictable pricing (70.6%) and roughly two in five report unfair ratings (41.2%) or deactivation/suspension (35.3%), while awareness of the e-Shram portal (52.9%) and of statutory welfare benefits (58.8%, with a further 23.5% only vaguely aware) remains partial. The paper concludes with a policy framework recommending algorithmic transparency mandates, accessible grievance redressal mechanisms, and targeted awareness measures for student and youth gig workers, contributing to the broader goal of inclusive, technology-driven, and socially secure economic growth envisioned under Viksit Bharat @2047.