Milan, Italy — The growing reliance on algorithmic management has sparked concerns about its opaque decision‑making and the impact on workers. In less than a decade, digital platforms have moved from niche markets to dominate diverse industries worldwide, both in developed and developing nations. These online mechanisms—such as Amazon, eBay, Uber, Deliveroo and Airbnb—facilitate the exchange of goods, services, or information between actors. In India, the platform economy has expanded rapidly, covering location‑dependent jobs like ride‑hailing, food delivery and caregiving, as well as location‑independent crowd work. This growth is driven by strong market demand and a large labour reserve that includes both local and migrant workers. Because more than 88 % of India’s workforce is employed in the informal economy, many view the rise of platforms as a potential means to address existing economic and social disparities.
The term “platform economy” refers to the increasing prominence of digital platforms whose models can reduce structural and labour costs, lower transaction costs and eliminate traditional barriers. These platforms promise greater autonomy for workers, allowing them to choose their workload, work portfolio, and the time and place of work. Consequently, many workers see platforms as viable opportunities to earn a living, whether at home or abroad. However, despite these advantages, platforms have raised concerns about deteriorating working conditions.
Algorithmic management underpins labour relations on these platforms. In practice, algorithms assign orders to specific workers, optimise delivery routes, calculate income and incentives, and monitor performance. Initially, workers welcomed algorithmic management, perceiving it as less stressful than dealing with human managers and believing the system to be more reliable in task allocation and income calculation. The ability of algorithms to process massive real‑time data enables faster, more accurate decisions, boosting productivity and reducing transaction costs.
Nevertheless, algorithmic management also carries indirect negative effects on workers’ physical and mental health. To meet platform targets, many workers now log 14 to 17 hours per day, disrupting work‑life balance. The opaque logic of algorithms leaves little room for human comprehension or contestation and can perpetuate existing biases and discrimination. Workers often struggle to understand how apps calculate remuneration or assess performance. As one Mumbai delivery worker explained, “If there is a problem on the road—like a bike accident—it is not considered. The company does not understand that if I cannot deliver, the app will deduct the amount or even double it from my payout.” Linking delivery times to ratings pushes workers to run red lights and ride at high speeds, increasing safety risks. Task assignment based on factors beyond workers’ control heightens stress and undermines collective resistance, prompting many to adopt individualistic strategies such as waiting at specific locations or cultivating good relations with team leaders to secure more orders.
Regulating platforms presents a significant challenge. In the EU, growing cases of algorithmic manipulation and discrimination, coupled with data inaccessibility, have spurred efforts to protect platform workers through new governance mechanisms. Italian courts in Palermo and Bologna have ruled that algorithmic assignment of deliveries disregards workers’ preferences and violates anti‑discrimination laws. In India, the debate centres on incorporating platform workers into the proposed Code on Social Security to ensure uniform coverage. Critics argue that the Code fails to address core issues such as worker classification, minimum wages, and clear implementation timelines, and it leaves responsibilities between central and state governments ambiguous. The Motor Vehicles Act of 2020 attempts to impose transparency obligations on platforms regarding app algorithms, yet it omits a “right to explanation,” leaving workers without insight into income calculation, task allocation, or performance evaluation. As complaints mount over personal data threats, lack of transparency, unaccountable programming, and algorithmic manipulation, there is a pressing need for a robust governance structure that grants platform workers greater access to data and the mechanisms shaping their work practices.
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