The Proletarianization of Data Science

**Forthcoming (2022) in Digital Work in the Planetary Market. Edited by Mark Graham and Fabian Ferrari. MIT Press** This chapter shows that the data science labour force, while globally distributed, is predominantly tied to powerful firms concentrated in specific locales. In particular, I argue that the planetary data science labour force is increasingly created by and for powerful technology capital in the USA. The increasing efforts of large firms in producing their own bespoke labour force has implications for digital labour in general. From the perspective of capital, data science labour-power is a scarce commodity to be competed for. Around the world, efforts are thus being made to proletarianize data science labour-power; to increase its supply and decrease its value, while capturing a competitive share of it. Wider distribution of the skills to perform currently rewarding and well-remunerated digital labour is often positioned as a means to close the economic gap between the Global North and South, but the distribution of such skills is accompanied by their simplification and consequent devaluation. While the proletarianization of data science labour-power may make more data science jobs available outside the Global North, it will do so only insofar as it reduces the labour costs for big technology firms. Rather than the elevation of less-privileged labourers to the digital era, the proletarianization of data science labour-power suggests the coming degradation of a privileged type of labour to the status of precarious and poorly remunerated ghost work.