Trump’s election was an exemplary instance of decompositionary class politics: it aimed precisely at dividing people along lines of race and gender – with special attention to rust-belt populations damaged by globalization – in order to get them to vote for a capitalist plutocrat. Trump is, and will be, far from the only political figure to deploy ML technologies; Obama was, after all, ‘the big data President’ (Scola 2013). His campaign, his supporters and similar ventures such as the UK Brexit campaign have demonstrated how deeply AI-powered interventions can corrupt network communication. They have also shown the affinity between right-wing populism, or, more properly, neo-fascism, and digital exacerbations of the divisions within working classes already fragmented by decades of neoliberal class warfare, and on the verge of fresh AI-driven fractures. At the very moment when recompositionary initiatives around the social factory seem most important for anti-capitalist politics, these have been rendered far more difficult by the attention-shattering impact of algorithmic advertising, the chilling effect of ML-informed mass surveillance, and inflammatory fake news, toxic chatbots, cyber-warfare and other forms of ‘weaponized AI propaganda’ (Anderson and Horvath 2017). AI thus contributes to the transformation of the internet from a potential arena for the ‘circulation of struggles’ (Dyer-Witheford 1999) to one dominated by the circulation of commodities, the surveillance of resistances and the destruction of class solidarities.
A HEPTAGON OF STRUGGLES
Nonetheless, popular apprehension about the scale and direction of capitalism’s AI ambitions is growing. Recent years have seen resistances and protests relating to AI springing up around the social factory. What we emphasize is that these are eruptions of popular sentiment, not for more AI (‘full automation now’), but for its refusal. None are outright anti-AI struggles, but each rejects or contests specific aspects of AI. In their combination and overlap, and despite frequent disconnections and contradictions, they challenge the current trajectory of AI-capital. We list seven of these antagonisms – a heptagon of struggles.
- Strikes and other workplace actions against AI-driven wage-depression, speed-up, monitoring, precarity and algorithmic management. The preeminent example is the wave of strikes and walkouts across Amazon fulfilment centres in Germany, Italy, Spain, Poland and the UK, demanding wage increases, job security and improvements in worker safety (Boewe and Schulten 2017; Cillo and Pradella 2017; Amazon Workers and Supporters 2018). The October 2018 pledge by Jeff Bezos to raise Amazon workers’ minimum wage (though undermined by claw-backs to a variety of other payments) was a partial victory for this movement, a concession intended to head off any transatlantic migration of struggles from Europe to the US (Reese and Struana 2018). Other strikes have disrupted the algorithmic management of precarious labour. The food courier Deliveroo operates with a ML-driven dispatch engine, which, the company claims, is called ‘Frank’ and is ‘constantly calculating and recalculating the best combination of riders to orders ... rider travel time, food preparation time etc.’ (Pudwell 2017). From 2016 onwards, strikes by Deliveroo drivers against the low pay and high insecurity enabled by ‘Frank’ spread virally from the UK across Europe, reaching as far as Hong Kong (Cant 2017; Zamponi 2018). A related stream of struggles is the rolling and complex series of lega challenges mounted from London to California by drivers for Uber against their algorithmically managed non-worker status (Rosenblat 2018). These have unfolded both in tandem and in contradiction with the legal objections, street blockades and protest suicides of ‘regular’ taxi drivers fighting the undercutting of their work. Intense as these tumults are, they pale in comparison with the scale of driver strikes, protests, algorithm sabotage and system-gaming raging across the vast operations of Didi, China’s Uber equivalent, insurgencies that may prefigure the chaotic future of labour activism under AI-capital (Chen 2018). To the file of worker actions should be added the unexpected North American unionization wave in new digital journalism enterprises such as Gawker, Salon, Huffington Post, Vice Canada and Al Jazeera involving young workers under ‘immense pressure to generate 24/7 online and social media content’ whose earnings and labour conditions are directly shaped by AI-driven advertising and directed news feeds (Cohen and de Peuter 2018: 115). More diffuse forms of worker organization are to be found in the microwork platforms that, as we have seen, are part of the AI production process. Turker Nation, the online forum of labourers on Amazon’s Mechanical Turk, has for years fostered microworker mutua support and knowledge sharing, challenged egregious exploitation by the platform’s corporate clients and protested the policies of Amazon itself (Harris 2014; Katz 2017). The more ML and other forms of AI suffuse capital, the more all worker resistance to corporate power will involve de facto resistance to the algorithmic forms in which that power is instantiated.
automating the social factory
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