Friends with benefits! Distributed cognition hooks up cognitive and social conceptions of science

Abstract

One approach to science treats science as a cognitive accomplishment of individuals and defines a scientific community as an aggregate of individual inquirers. Another treats science as a fundamentally collective endeavor and defines a scientist as a member of a scientific community. Distributed cognition has been offered as a framework that could be used to reconcile these two approaches. Adam Toon has recently asked if the cognitive and the social can be friends at last. He answers that they probably cannot, posing objections to the would-be rapprochement. We clarify both the animosity and the tonic proposed to resolve it, ultimately arguing that worries raised by Toon and others are uncompelling.

Keywords::

• Distributed Cognition
• Division of Cognitive Labor
• D-Cog
• Science Studies
• Scientific Knowledge
• SSK

Acknowledgements

We would like to thank Adam Toon and several anonymous referees for their helpful comments on earlier drafts.

Notes

^[1] We have both articulated this elsewhere. The criterion given by Magnus (2007) is posed in terms of a distinction that had earlier been articulated by McClamrock (1991, 1995).

^[2] Note that this takes both Marr's algorithm and Marr's implementation to be aspects of the process.

^[3] Hutchins (2014) uses ‘distributed cognition’ to mean a methodological approach which analyzes cognition in terms of the interaction between separate functional elements, even if all of the functional components are contained inside a single organism. Our characterization of d-cog explicitly requires distribution beyond the boundary of an organism, because we are especially interested in understanding science. For our purposes, what is crucial is precisely the involvement of instruments and communities of people.

^[4] One might wonder about the relation between d-cog and embedded cognition—the view that, as Rupert puts it, “cognitive processes depend heavily, and in hitherto unexpected ways, on organismically external properties and devices, and on the structure of the external environment in which the cognition takes place” (2004, p. 393). The central claim of both is that mechanisms, objects, and structures instantiated outside the body often provide critical support for the task accomplished in cognition. If one reads embedded cognition as something that happens inside the organism but requires the external structure as props, then it is a somewhat more conservative view. Alternately, one might read embedded cognition as d-cog.

^[5] We have the same worry about Cheon's (2014) positive definition, which includes many unexplicated jargon terms: “cognitive outputs” which result from “coordinated information processing” and the propagation of “semantic information.” Although the phrases use familiar English words, we do not have a precise enough understanding of them to apply the definition to cases.

^[6] Ultimately, the three-level analysis must be adjusted to account for different perspectives on various levels of organization of complex systems; see McClamrock (1991). As Danks put it, Marr's three levels conflate “a multidimensional space of theoretical commitments” (2013, p. 2129).

^[7] Bloor himself expresses the opposition in these term (e.g., 1991, p. 165).

^[8] In addition to SSK, Toon mentions the work of Helen Longino. He writes, “Similar claims are also found in the work of authors outside SSK. For example, Longino writes that science is ‘necessarily social’” (Toon, 2014, p. 120). In the passage he cites, Longino argues that “the development of knowledge is a necessarily social rather than individual activity” (1990, p. 12). Here the terminological difference seems especially acute. Longino offers several definitions of ‘knowledge’, all of which include the community as an explicit term (2002, pp. 135–140).

^[9] Note that the issue can be made substantive by combining an individualist definition of knowledge with the requirement that cognitive activity yield knowledge. For example, Giere (2013) insists that science must yield human knowledge for an individual. Vaesen (2011) argues that this risks allowing any d-cog analysis to be refigured in individual terms. Although our sympathies lie with Vaesen, d-cog as we understand it is compatible with either Giere or Vaesen being right.

^[10] Other examples given by Magnus (2007) include the machinery in a carpentry shop and double-blind clinical trials.

Additional information

Notes on contributors

P. D. Magnus

P. D. Magnus is Associate Professor at the University at Albany, State University of New York.

Ron McClamrock

Ron McClamrock is Associate Professor at the University at Albany, State University of New York.