Digital technologies have enabled unprecedented expansion in the volume and kinds of data collected about workers. Today, employers amass data from technologies such as wearables, mobile apps, computer software, and other surveillance tools but also through simple, low-tech methods such as self-reporting information on a paper form. The ability to analyze large datasets enables employers to make broad and at times speculative inferences about workers’ productivity, their future behavior, their interactions with other people and machines, and more.

Fundamentally, data is a way to gain and organize knowledge about a workplace. But in a context where workplaces are sites of major power imbalances, it is essential to ask, how is that knowledge produced and for what purpose? Who has control over deciding what the data means, where it goes, and how it is used? While proponents of data-hungry workplace technologies promise that data can help accomplish everything from enhancing worker productivity to creating safer, happier workplaces, these tools often further entrench older dynamics of exploitation and control. And they are altering the landscape of many long-standing struggles for worker rights, autonomy, and well-being.

Is the right path to fight against all worker datafication? When can data-driven tools benefit workers? What would it take for workers to have meaningful control over their data? What do we actually want from worker data? This explainer provides an introduction to different recent approaches to worker data, and explores ongoing questions, critiques, and possibilities.