The conditions of peak empiricism in big data and interaction design

Michael Marcinkowski, Fred Fonseca

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


An influx of mechanisms for the collection of large sets of data has prompted widespread consideration of the impact that data analytic methods can have on a number of disciplines. Having an established record of the use of a unique mixture of empirical methods, the work of understanding and designing for user behavior is well situated to take advantage of the advances claimed by "big data" methods. Beyond any straightforward benefit of the use of large sets of data, such an increase in the scale of empirical evidence has far-reaching implications for the work of empirically guided design. We develop the concept of "peak empiricism" to explain the new role that large-scale data comes to play in design, one in which data become more than a simple empirical tool. In providing such an expansive empirical setting for design, big data weakens the subjective conditions necessary for empirical insight, pointing to a more performative approach to the relationship between a designer and his or her work. In this, the work of design is characterized as "thinking with" the data in a partnership that weakens not only any sense of empiricism but also the agentive foundations of a classical view of design work.

Original languageEnglish (US)
Pages (from-to)1279-1288
Number of pages10
JournalJournal of the Association for Information Science and Technology
Issue number6
StatePublished - Jun 1 2016

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Networks and Communications
  • Information Systems and Management
  • Library and Information Sciences


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