Macrocognition: A Theory of Distributed Minds and Collective Intentionality
Nov 2013 · Oxford University Press
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272
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About this ebook
We live in an age of scientific collaboration, popular uprisings, failing political parties, and increasing corporate power. Many of these kinds of collective action derive from the decisions of intelligent and powerful leaders, and many others emerge as a result of the aggregation of individual interests. But genuinely collective mentality remains a seductive possibility. This book develops a novel approach to distributed cognition and collective intentionality. It argues that genuine cognition requires the capacity to engage in flexible goal-directed behavior, and that this requires specialized representational systems that are integrated in a way that yields fluid and skillful coping with environmental contingencies. In line with this argument, the book claims that collective mentality should be posited where and only where specialized subroutines are integrated to yields goal-directed behavior that is sensitive to the concerns that are relevant to a group as such. Unlike traditional claims about collective intentionality, this approach reveals that there are many kinds of collective minds: some groups have cognitive capacities that are more like those that we find in honeybees or cats than they are like those that we find in people. Indeed, groups are unlikely to be "believers" in the fullest sense of the term, and understanding why this is the case sheds new light on questions about collective intentionality and collective responsibility.
About the author
Bryce Huebner is an associate professor at Georgetown University. He completed a PhD at the University of North Carolina, Chapel Hill and did postdoctoral research in psychology at Harvard University and in the Center for Cognitive Studies at Tufts University (working with Dan Dennett). He has published both theoretical and empirical research, in philosophy and the cognitive sciences. He is currently engaged in research on moral cognition, reinforcement learning, and the possibility of epistemic accountability in distributed cognitive systems.
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