A pluralistic approach to distributed cognition: tasks, mechanisms, and practices
thesisposted on 28.03.2022, 19:32 by Alexander James Gillett
This thesis is a conceptual re-analysis of distributed cognition. I defend the position against numerous challenges and propose a novel pluralistic approach. Distributed cognition is a research framework used in many differing fields within the sciences and humanities. It proposes that the unit of analysis for exploring human cognition is flexible, and that cognition is distributed across both time and space in multiple ways (Hutchins 2001). But the stunning variety of putative cases in the literature raises a multitude of questions about whether this concept is being applied coherently. The heterogeneity of size and type of distributed cognitive systems also exacerbates the problem of cognitive bloat. I argue that standard simpler approaches to these problems are inadequate because they fail to account for the importance of cognition distributed in time. As such, I propose a pluralistic approach that combines a number of naturalistic criteria from the literature: task-specificity (Davies & Michaelian 2016), the mutual manipulability criterion (Kaplan 2012), and normative patterned practices (Menary 2007a, 2016). These principles work in conjunction with each other in a consilient fashion to tackle the myriad problems facing a proponent of distributed cognition – as well as mitigating a further problem I call ‘methodological bloat’. My pluralistic framework also provides a robust and useful framework that is suitable for both theoretical and practical purposes: i.e. it not only provides us with a principled means of designating what distributed cognition is, it also shows how exploring distributed cognition in specific case studies can lead to insights about human cognition “in the wild”. I demonstrate these points with reference to the specific details of case studies – particularly Hutchins’ (1995a) seminal navigation team. This allows me to show that my pluralistic approach is not only superior to simpler approaches to distributed cognition but also provides insights that are of note to methodological individualists.