The labour ministry’s draft code defines a gig worker as a person who performs work or participates in a work arrangement, and earns from such activities outside of a traditional employer-employee relationship. Going by this broad definition the number of Indian gig economy workers is 426 million (informal + temporary workers) i.e. 92% of India’s active labour force. This is happening at an odd juncture where our demographic dividend is set to be at its highest. Digital platforms such as Ola, Uber, Amazon, Urbanclap, Swiggy, and Zomato have shown us how gig economy platforms can be built and scaled to capitalise on the youth. However, the downside to such platforms is that the platforms own the data which may lead to short-term job creation but prevents mobility of gig workers’ skills in the future.

In this context, the authors interviewed 4,070 gig workers on their perception of platform fairness, wages, socioeconomic backgrounds and the savings they held. The study suggests that instead of creating siloed, monopolistic access to data sets on which algorithms can be trained, shared data can create a level playing field for companies of all sizes. Through this study, the authors propose a thin, middleware layer that enables data transfers between organisations with the gig worker holding sovereign rights.