How India’s gig platforms monetize invisible labor?

A groundbreaking study sheds light on the hidden burdens carried by India’s food delivery workforce, revealing how algorithmic control, platform inefficiencies, and relentless digital routines create a structure of “invisible labor” beneath the surface of app-based gig work. Titled “‘The Boring and The Tedious’: Invisible Labour in India’s Gig-Economy”, the study offers a rare qualitative deep dive into the everyday struggles of gig workers on platforms such as Swiggy, Zomato, Blinkit, and BigBasket.

Based on semi-structured interviews with 14 food delivery workers in Hyderabad, the research rejects both celebratory and dystopian narratives. Instead, it uncovers the nuanced reality of how India’s gig workers survive within a gamified system that trades autonomy for efficiency while systematically disregarding the physical and mental toll of repetitive, uncompensated tasks.

What constitutes ‘invisible labor’ in the gig economy?

The study identifies two dominant forms of invisible labor endured daily by app-based delivery workers: prolonged waiting and tedious digital repetition.

First, pervasive waiting time consumes between 25% to 30% of a typical shift. Workers often arrive at restaurants to find orders delayed, despite app updates indicating readiness. They also experience long intervals between deliveries, especially in so-called “high-demand zones” that fail to generate consistent orders. Post-delivery delays are common as workers struggle with gated apartment complexes, missing address information, and unresponsive customers - all without any compensation for the extra time spent.

Second, tedious repetition pervades the digital interface. Workers endure frequent app-switching - jumping between the delivery app and Google Maps due to unreliable navigation. They also must perform multiple mandatory status updates and take proof-of-delivery photos. Repetitive phone calls to customers and routine interactions with customer support over address or cancellation issues further add to the mental load. These actions, though minor in isolation, cumulatively contribute to digital fatigue, frustration, and operational inefficiency.

How does algorithmic management reinforce worker discomfort?

The research examines “two-fold gamification” - a concept describing the interactive push and pull between platform-designed incentives and workers’ tactical resistance. Platforms like Zomato and Swiggy use algorithmic features such as medal tiers or zonal incentives to direct worker behavior under the guise of performance optimization. Yet workers are not passive recipients of these rules. They devise workarounds like prematurely marking themselves “arrived” at a restaurant to avoid penalties caused by factors beyond their control, such as kitchen delays or map inaccuracies.

The report underscores the ethical tension in this gamified structure. Platforms track every move but ignore the nuances of the worker’s lived experience. Algorithms often misrepresent time estimates, fail to adjust for traffic or building access complexities, and prompt unnecessary notifications. This results in cognitive overload, as workers attempt to satisfy the system’s opaque performance metrics while navigating chaotic urban landscapes.

Crucially, the study argues that these systems are not neutral. Platform design prioritizes data collection and productivity metrics over worker comfort, subtly reinforcing exploitation under the guise of technological efficiency. Workers adapt and resist not to game the system, but to cope with its unrealistic expectations.

Can worker-centered automation offer relief without disempowerment?

Looking ahead, the study explores the potential for worker-centered automation as a response to digital fatigue. Systems like AutoDroid and conceptual tools such as GigSense are proposed as solutions to reduce low-value interactions, automating routine updates, app-switching, or basic customer communication. While some workers expressed openness to such technologies, others raised concerns about increasing surveillance, data misuse, and the inability of AI to address physical-world challenges like delayed kitchens or navigation through complex neighborhoods.

Instead of replacing workers, the researchers advocate for meaningful augmentation. This includes design directions such as ambient automation, which works quietly in the background, and customizable micro-automations, which allow workers to tailor shortcuts according to their unique routines.

The report closes with a strong call for Human-Computer Interaction (HCI) that centers on equity and inclusion, especially in the Global South. It urges developers, policymakers, and platform designers to move away from reductive metrics of efficiency and instead prioritize “digital comfort” - designing interfaces and algorithms that bridge the gap between abstract platform logic and the lived reality of gig work.