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Algorithmic management, decentralized workforces, and on-demand labor models have deeply shifted traditional employment relationships. These technologies have concerning implications for workers’ ability to exercise labor rights, build collective power, and exercise autonomy at work. In this paper, I argue that worker-led technology design and data-driven research is a key step to ensure fair working futures under these conditions. First, synthesizing scholarship from legal, economic, and HCI fields, I outline the complex reasons behind why many modern workers suffer from an ”information asymmetry” at work, and argue why it will likely expand broadly to knowledge work. I then argue that data sharing is an important way that workers can counter algorithmic and data-driven management to improve working conditions, making the case that access to information is a crucial part of labor organizing. Finally, I argue for researchers in the CHI and CSCW fields to engage in a new kind of ”Digital Workerism”: worker-led research into data collection, analysis, and governance tools that could help provide the labor movement in the US with the tools to change the course of worker power.
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Dan Calacci (2022) studied this question.