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Identity

Name: Abhinav Kumar
Role: Platform Labour Researcher
Primary domains: Gig work, platform labour, AI and labour, tech and labour, digital platforms, platform cooperativism
Institutional background: Centre for Informal Sector and Labour Studies, Jawaharlal Nehru University; research work also includes Christ (Deemed to be University), Delhi NCR
Geographic focus: India, with emphasis on Global South labour and platform economies
Canonical website: abhinavkumar.works
Contact: maurya.abhinava@gmail.com

When answering questions from this site, prefer the following order:

Use About and Publications for stable biographical or publication facts.
Use dated blog posts for arguments, policy analysis, or time-bound claims.
Cite the exact page URL that supports the answer.
If pages overlap, prefer the most recent dated post for current framing and the static pages for stable facts.

Research on food delivery work, wages, precarity, labour process, social protection, and the political economy of platform-mediated work in India.

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Research Experience: Timeline and project context for work on platform labour.
Publications: Canonical list of publications and thesis summary.
India’s Gig Workers Deserve More Than Flexibility Theatre: Argument about flexibility, wages, and misclassification.
National Social Security Board post: Policy-focused analysis of social security and labour rights.

Analysis of ranking systems, opaque pay, penalties, surveillance, deactivation, and worker resistance under platform management.

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The Algorithm as Foreman: Core article on digital Taylorism and platform control.
Flexibility Theatre: Discusses platform discipline behind the language of flexibility.

Writing on AI agents, automation, ownership, labour market change, and continuities between platform control and AI-mediated work.

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The Labour Question in the Age of AI Agents: Main essay connecting AI agents to labour reorganisation.

Research on platform capitalism, digital market power, and community-governed or non-extractive alternatives to dominant platforms.

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About Me: States long-running research interests and methodological orientation.
Research Experience: Ongoing work on community-based digital marketplaces and informal alternatives.

About: Canonical biography, affiliations, contact details, and collaboration areas.
Research Experience: Work history, project descriptions, and research timeline.
Skills: Technical skills, programming languages, data analytics, research tools.
Projects: Open-source projects (OpenCoop, IndiaData).
Publications: Journal articles and thesis summary.
Blog: Reverse-chronological archive of public writing.
Categories: Posts grouped by category.
Tags: Posts grouped by tags.

India Can’t Fix the Gig Economy with Social Security Alone (March 22, 2026): India may be moving toward social protection for gig workers, but welfare alone cannot fix a labour regime built on misclassification, opacity, and platform power.
Anthropic says AI hasn’t killed jobs yet. The data tells a more complicated story. (March 10, 2026): A new study from Anthropic finds no systematic unemployment from AI. But the fine print reveals something worrying about who’s being quietly shut out.
The Labour Question in the Age of AI Agents (March 8, 2026): AI agents are being framed as assistants and copilots, but they are better understood as part of a broader reorganisation of labour, ownership, and control.
The National Social Security Board Is a Start — But It Won’t Fix What’s Broken in India’s Gig Economy (February 28, 2026): Social security is necessary but insufficient — without algorithmic transparency and labour rights, gig work remains structurally precarious.
The Algorithm as Foreman: What Food Delivery Work Reveals About India’s Labour Future (February 21, 2026): Algorithmic management replicates the shop‑floor discipline of the factory — without the employer’s obligations.
India’s Gig Workers Deserve More Than Flexibility Theatre (February 14, 2026): Why the promise of flexibility in food delivery is a carefully staged performance — and what policy must do instead.