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Mechanical Novel: Crowdsourcing Complex Work Through Reflection and Revision

In: Design Thinking Research

Author

Listed:
  • Joy Kim

    (Stanford University)

  • Sarah Sterman

    (Stanford University)

  • Allegra Argent Beal Cohen

    (Stanford University)

  • Michael S. Bernstein

    (Stanford University)

Abstract

Crowdsourcing systems accomplish large tasks with scale and speed by breaking work down into independent parts. However, many types of complex creative work, such as fiction writing, have remained out of reach for crowds because work is tightly interdependent: changing one part of a story may trigger changes to the overall plot and vice versa. Taking inspiration from how expert authors write, we propose a technique for achieving interdependent complex goals with crowds. With this technique, the crowd loops between reflection, to select a high-level goal, and revision, to decompose that goal into low-level, actionable tasks. We embody this approach in Mechanical Novel, a system that crowdsources short fiction stories on Amazon Mechanical Turk. In a field experiment, Mechanical Novel resulted in higher-quality stories than an iterative crowdsourcing workflow. Our findings suggest that orienting crowd work around high-level goals may enable workers to coordinate their effort to accomplish complex work.

Suggested Citation

  • Joy Kim & Sarah Sterman & Allegra Argent Beal Cohen & Michael S. Bernstein, 2018. "Mechanical Novel: Crowdsourcing Complex Work Through Reflection and Revision," Understanding Innovation, in: Hasso Plattner & Christoph Meinel & Larry Leifer (ed.), Design Thinking Research, pages 79-104, Springer.
  • Handle: RePEc:spr:undchp:978-3-319-60967-6_5
    DOI: 10.1007/978-3-319-60967-6_5
    as

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