The gig economy is often celebrated as a defining innovation of contemporary capitalism. Platform labour is thus portrayed as a decisive break from industrial society: decentralised networks replacing factories, flexibility displacing discipline, and autonomy supplanting hierarchy.
This story is wrong. The gig economy does not represent a postmodern rupture from capitalist labour relations but a counter-revolution in labour discipline, enabled by Artificial Intelligence and disguised by postmodern illusion. The algorithm replaces the factory foreman; flexibility masks coercion; and autonomy becomes a euphemism for shifting economic risk from capital onto labour.
At the centre of this transformation stands the gig worker — not as a symbol of freedom but as the subject of algorithmic control.
Postmodern theory has insisted that power in late capitalism is diffused and decentred. Platforms are imagined as neutral infrastructures rather than commanding institutions, while algorithms are treated as opaque cultural artefacts. The disappearance of visible authority is mistaken for the disappearance of power itself.
The gig economy exposes this illusion. Power has not evaporated into networks; it has been automated.
A materialist understanding of AI begins with a simple proposition: AI is not intelligence but accumulated human labour, objectified in code and redeployed as capital. Algorithms operationalise past human activity — data, language, judgment, and social knowledge — under conditions of private ownership. In the gig economy, this dead labour confronts living labour directly.
Pricing algorithms determine wages in real time. Allocation systems decide who works and who waits. Rating mechanisms discipline behaviour through constant evaluation, while deactivation functions as instant dismissal without explanation or appeal. What defines algorithmic management is asymmetry: workers are rendered fully visible — tracked, measured, predicted — while the systems governing them remain opaque.
India offers a stark empirical lens into this transformation. With tens of millions engaged in platform-mediated work, the country has become a laboratory for
algorithmic labour governance. Ride-hailing drivers, delivery workers, warehouse pickers, and digital freelancers are formally classified as independent contractors, yet they experience levels of control exceeding many standard employment relationships.
Flexibility, the gig economy’s central promise, functions in practice as discipline. Algorithmic incentives reward constant availability and penalise refusal. Surge pricing and opaque bonus systems compel workers to remain online for long hours to earn subsistence incomes. Flexibility does not expand freedom; it externalises market risk while maintaining continuous control.
The rating system further reveals how algorithmic governance reproduces social domination. Presented as neutral feedback, ratings convert subjective customer judgments into numerical scores that determine access to work. In India, these systems intersect with entrenched hierarchies of caste, religion, gender, and language. Dalit and Muslim workers report lower ratings and higher deactivation rates — not because of inferior performance but because historical prejudice is mathematically encoded into platform management. Legal responses remain hesitant. Courts acknowledge platform control yet defer to contractual classifications that deny gig workers employee status.
The gig economy reveals what postmodern theory fails to grasp: power has not dissolved into networks; it has hardened into code. AI is not a post-human intelligence but dead labour commanding living labour with unprecedented efficiency. Gig workers are not peripheral to this transformation. They are its central subjects and their struggle is inseparable from the struggle over labour, democracy, and the future of technology itself.
Debashis Chakrabarti is a political commentator and Commonwealth Fellow, University of Leicester, UK