Incorporating Values Sensitive Design into Crowdsourcing Methodologies for Knowledge Collaboration

Annie T. Chen, Samantha J. Kaplan, Pamella Lach, Lu Xiao

Research output: Contribution to journalArticlepeer-review


In recent years, we have seen a dramatic increase in crowdsourcing approaches to solve problems and engage in other types of knowledge work in many domains, including genetics, health, cultural heritage, digital preservation and design. Crowdsourcing initiatives offer many potential benefits, including engaging individuals of diverse backgrounds in collaborative meaning-making and production. And yet, the potential challenges and dangers, such as issues related to quality and false confidence, can hardly escape our attention. This panel will explore how human-centered approaches to crowdsourcing can help minimize its challenges. In particular, this panel will ask how we implement crowdsourcing methods, what our outcomes should be, and how we should go about developing and defining our outcomes in relationship to the workers. The first half of the session will be devoted to an introduction to crowdsourcing initiatives and associated critical issues. Each presentation will drill progressively deeper into the mechanisms and implications of crowdsourcing. In the second half of the session, we invite session attendees to engage with us in a collaborative activity employing techniques from the value sensitive design approach to design crowdsourcing initiatives that are sensitive to the communities with whom we engage and thereby endeavor to realize humanistic goals. It is our hope that the panel session will result in new collaborations and spark the development of more thoughtful, reflexive and productive crowdsourcing activities.

Original languageEnglish (US)
Pages (from-to)545-548
Number of pages4
JournalProceedings of the Association for Information Science and Technology
Issue number1
StatePublished - Jan 2017


  • crowdsourcing
  • knowledge collaboration
  • value sensitive design

ASJC Scopus subject areas

  • General Computer Science
  • Library and Information Sciences


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