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Distributed Cognition in Scientific Contexts

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Abstract

Even though it has been argued that scientific cognition is distributed, there is no consensus on the exact nature of distributed cognition. This paper aims to characterize distributed cognition as appropriate for philosophical studies of science. I first classify competing characterizations into three types: the property approach, the task approach, and the system approach. It turns out that the property approach and the task approach are subject to criticism. I then argue that the most preferable way to understand distributed cognition in science is provided by the system approach that takes a distributed-cognitive system as the unit of analysis. I clarify this position by considering possible objections and replies.

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Notes

  1. It might be better to give psychological evidence for the limit of human calculation ability rather than to simply speculate although it does not undermine the point that I made. To my knowledge, however, there is no concrete empirical research on this. Rather, I think it is useful to mention two things among the world record of Mental Calculation World Cup. In the task of adding ten 10-digit numbers, Naofumi Ogasaware in 2012 produced 10 correct results in 3:11 min. In the task of multiplying two 8-digit numbers, Marc Jornet Sanz in 2010 produced 10 correct results in 4:56 min. It is excusable to say that at first approximation, those records might be close to the limit of human ability.

  2. You can notice that it is a sufficient condition for being a part of a distributed-cognitive system, allowing that some non-contributive parts might consist in the system. While I cannot reject the possibility decisively, I believe that the possibility is not among typical scientific cases of distributed cognition.

  3. Giere (2002, 294) suggests that a proper part of a system should “differentially influence” to the outputs “in scientifically relevant way”. This is meant to exclude the features that “merely make it possible for the system to generate any output at all.” I believe that by adopting the notion of semantic information processing, (DCS2-S) provides a clearer way to distinguish a proper part of a system from environments.

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Acknowledgments

I would like to thank Edouard Machery and two anonymous reviewers for their helpful comments on earlier drafts of this paper. I also thank Dongwook Jung, Wonki Her, and the members of Philosophy of Science Working Group, Seoul National University for useful discussion.

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  1. Program in History and Philosophy of Science, Seoul National University, Gwanak-gu, Seoul, South Korea

    Hyundeuk Cheon

  2. Department of Philosophy, Hanyang University, Seongdong-gu, Seoul, South Korea

    Hyundeuk Cheon

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Cheon, H. Distributed Cognition in Scientific Contexts. J Gen Philos Sci 45, 23–33 (2014). https://doi.org/10.1007/s10838-013-9226-4

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