<p>This paper asks a simple question: when we use digital platforms, are we more like horses that leave manure behind or like workers whose efforts help create value? Building on the idea of “data as labor,” we suggest that everyday activities, such as scrolling, clicking, and solving reCAPTCHAs, can function as a thin form of labor for data-driven firms. We argue that the key issue is not who owns the data, but whether the terms on which platforms use it are fair. To make this case, we connect debates on household production, unconscionable contracts, and surveillance capitalism to current data practices. We then explore how tools such as portability and erasure rights, data unions, and data strikes might give users modest forms of bargaining power. Our aim is not to offer a final theory, but to invite a more careful discussion of recognition and fairness in the data economy.</p>

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Are We Horses? Rethinking Data as Labor

  • Tae Wan Kim,
  • Nicholas Vincent

摘要

This paper asks a simple question: when we use digital platforms, are we more like horses that leave manure behind or like workers whose efforts help create value? Building on the idea of “data as labor,” we suggest that everyday activities, such as scrolling, clicking, and solving reCAPTCHAs, can function as a thin form of labor for data-driven firms. We argue that the key issue is not who owns the data, but whether the terms on which platforms use it are fair. To make this case, we connect debates on household production, unconscionable contracts, and surveillance capitalism to current data practices. We then explore how tools such as portability and erasure rights, data unions, and data strikes might give users modest forms of bargaining power. Our aim is not to offer a final theory, but to invite a more careful discussion of recognition and fairness in the data economy.