The cover of an Economist (2018) report on ‘Artificial Intelligence in the Workplace’ depicts a Brobdingnagian office lamp illuminating Lilliputian workers, under the title ‘AI-spy’. Digital technologies have brought a ‘new Taylorism’ (Salame 2018) to workplaces, in which job deskilling is fused with algorithmic management and accompanied by workplace surveillance capacities far greater than those of any clipboard carrying superintendent. Phoebe Moore and her colleagues (2018) detail how sociometric badges, keyboard counters, email scanning, location tracking, motion sensors, and voice and facial recognition technologies detecting shifts in efficiency and mood minute to minute are now normal in workplaces. ML-driven ‘People Analytics’ is the new obsession of corporate HR departments that draw on AI tools for employee screening and selection based on social media traces, and delegate interviews to chatbots (Buranyi 2018). Fed with such data, AI becomes a way of assessing workers’ ‘productivity and fitness to execute particular tasks (De Stefano 2018: 7). This creation of a digitally ‘quantified worker’ is advanced under the guise of providing employees with beneficial information about their performance, health and state of mind for the purposes of voluntary self-improvement and ‘wellness’; the corporate providers of wearable workplace devices market them as ‘humanizing’ technologies. But this barely masks their obvious enhancement of managerial power by such technologies of ‘limitless worker surveillance’ (Ajunwa, Crawford and Schultz 2017).
Primarily concerned with the stress, indignity and intrusiveness such surveillance inflicts on employees, Moore et al. (2018) are sceptical about ‘deep automation’ and emphasize the economic, technological and social barriers to its abrupt arrival. But such monitoring is a moment within AI development. By the same logic that AlphaGo’s defeat of grandmasters at the ancient game of Go depended on digital digestion of thousands of hours of previous human play, so recording worker performance, even if initiated for disciplinary reasons, opens the way to new transformations of labour into machine form. Autonomous vehicles depend on digitally recording hundreds of thousands of hours of human driving. The recordings of call centre staff become the basis for voice analytic software that first supplements their work and then supplants it. The robotization of Amazon fulfilment centres emerged from electronic tagging of human ‘ambots’: in 2018 the company had two patents approved for a wristband tracker emitting ultrasonic sound pulses and radio transmissions to monitor a picker’s hands in relation to inventory, providing ‘haptic feedback’ to ‘nudge’ the worker towards the correct object (Yeginsu 2018). Reports of these patents sparked a public outcry about worker privacy and speed-up, but it is also clear that the wristband, or even more extensive monitoring devices, could pave the way for the robotic replacement of pickers. The organic link between workplace monitoring and worker replacement, and hence between AI development and surveillance, led The Economist (2018) to conclude that while AI workplaces may not be immediately depopulated, they will become ‘creepier’.
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inhuman power