CeRAI calls for human-centric AI in gig work; researchers discuss role of AI in India's gig economy

New Delhi [India], December 2 : In a thoughtful conversation at the AI4India podcast, Krishnan Narayanan and Omir Kumar from the Centre for Responsible AI (CeRAI), IIT Madras discussed the role of digital platforms and AI technologies reshaping work for millions of gig workers in India.

While unpacking their new research report titled, "The Algorithmic Manager: AI, Apps, and Workers in the Indian Gig Economy", they also discussed how the often-overlooked human realities play behind the algorithms driving the sector.

Omir Kumar, Policy Analyst at CeRAI, explained that gig work is one of India's fastest-growing sources of employment, with projections estimating over 2.35 crore blue-collar gig workers by 2029-30. Yet, despite the sector's scale, he noted, "Not enough attention has been paid to the technology that actually powers this ecosystem."

Drawing from his experience at Zomato and his policy research background, Kumar said the study was motivated by a desire to understand how AI, automation, and app-based systems manage workers, and how workers themselves perceive these systems.

Krishnan Narayanan, Researcher, CeRAI added that the research also fits into the broader work of CeRAI's Co-Intelligence Network, which studies the future of work. "We found that gig work, despite its size and impact, remains under-researched, especially through an interdisciplinary social-justice lens," he said.

"I don't think workers fully understand AI yet. They have an understanding, but for them it's the platform. They don't fully understand the nuance of AI. They might say they've never used AI, even though they experience the effects every day," he said.

A central insight from the report is what the authors call the "algorithmic-human manager", the combination of automated decision-making and human oversight that governs gig workers' everyday lives.

Despite working through apps, many workers believe that humans still make key decisions behind the scenes.

"Workers often assume an operations manager is ultimately deciding their allocation or incentives. Their understanding of AI is limited, even though they experience its effects every day," Narayanan noted.

During the conversation, they highlighted two major concerns for the gig workers. One is the lack of transparency around wages and incentive calculations, and second is the inability to contact a real human during disputes or deactivations.

Kumar highlighted that for the gig workers, grievance redressal is very crucial.

"Grievance redressal is everything for workers. They don't want to talk to a bot, they want a person on the other end," Kumar said.

Further, the study also examined dark stores in the booming quick-commerce sector, where handheld digital devices guide workers through picking and sorting tasks.

Kumar said the workers montioned they do not fear being replaced by robots. "One warehouse employee laughed off the idea saying, a robot won't dodge potholes, climb stairs, or handle sudden changes. And if it breaks down, operations stop. Humans adapt, machines can't."

"Humans and technology are working together. Workers have handheld devices that help them navigate the store. A worker told me, if a machine breaks down, operations stop. Humans can increase the pace of work when there's more load I can't tell that to a machine," he added.

The report proposed a Digital Public Infrastructure (DPI) concept called the Unified Worker Interface (UWI).

It proposes a portable, unified digital ID for all gig and informal workers, standardized reputation and work-history portability across platforms.

During the conversation, it was highlighted a protocol-based system enabling states and the Centre to deliver social security benefits directly, as well as a privacy-preserving, interoperable framework inspired by the success of UPI will play crucial role for gig economy.

"The ecosystem today is fragmented. A protocol-based UWI would simplify social security delivery, reduce duplication, and empower workers to carry their histories across platforms," Kumar said.

The study blends primary fieldwork with gig workers in Bengaluru and Delhi NCR, interviews with platform companies, experts, and social-science-based analytical frameworks.

The researchers also drew from frameworks like John Rawls' difference principle, Amartya Sen's capability theory, and Johan Galtung's structural violence to analyze fairness, power dynamics, and inequities in gig work.

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