Value of cognitive diversity in science

When should a scientific community be cognitively diverse? This article presents a model for studying how the heterogeneity of learning heuristics used by scientist agents affects the epistemic efficiency of a scientific community. By extending the epistemic landscapes modeling approach introduced by Weisberg and Muldoon, the article casts light on the micro-mechanisms mediating cognitive diversity, coordination, and problem-solving efficiency. The results suggest that social learning and cognitive diversity produce epistemic benefits only when the epistemic community is faced with problems of sufficient difficulty.

[1]  W. Heath.  The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies , 2008 .

[2]  Scott E. Page,et al.  Agent-Based Models , 2014, Encyclopedia of GIS.

[3]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[4]  Michael Weisberg.  New Approaches to the Division of Cognitive Labor , 2010 .

[5]  E. Anderson.  Knowledge, Human Interests, and Objectivity in Feminist Epistemology , 1995 .

[6]  J. Thoma,et al.  The Epistemic Division of Labor Revisited , 2015, Philosophy of Science.

[7]  M. Polanyi.  The Republic of science , 1962 .

[8]  Ryan Muldoon,et al.  Diversity and the Division of Cognitive Labor , 2013 .

[9]  H. Longino.  The Fate of Knowledge , 2001 .

[10]  Kevin J. S. Zollman,et al.  The Independence Thesis: When Individual and Social Epistemology Diverge* , 2011, Philosophy of Science.

[11]  Claus Beisbart,et al.  How can computer simulations produce new knowledge? , 2012 .

[12]  H. Longino.  Science as Social Knowledge: Values and Objectivity in Scientific Inquiry , 1990 .

[13]  S. Kauffman,et al.  Towards a general theory of adaptive walks on rugged landscapes. , 1987, Journal of theoretical biology.

[14]  David Lazer,et al.  The Network Structure of Exploration and Exploitation , 2007 .

[15]  P. Ylikoski,et al.  Understanding with theoretical models , 2014, Journal of Economic Methodology.

[16]  P. Kitcher,et al.  The advancement of science : science without legend, objectivity without illusions , 1995 .

[17]  Elhanan Borenstein,et al.  EVOLUTION OF LEARNING IN FLUCTUATING ENVIRONMENTS: WHEN SELECTION FAVORS BOTH SOCIAL AND EXPLORATORY INDIVIDUAL LEARNING , 2008, Evolution; international journal of organic evolution.

[18]  D. Lamb.  The Advancement of Science. Science Without Legend, Objectivity Without Illusions , 1994 .

[19]  S. Page.  Prologue to The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies , 2007 .

[20]  Miriam Solomon,et al.  Groupthink versus The Wisdom of Crowds: The Social Epistemology of Deliberation and Dissent , 2006 .

[21]  Philip Kitcher,et al.  The Division of Cognitive Labor , 1990 .

[22]  Rogier De Langhe,et al.  A Unified Model of the Division of Cognitive Labor , 2014 .

[23]  Scott E. Page,et al.  Agent-Based Models , 2014 .

[24]  P. D. Magnus,et al.  New Waves in Philosophy of Science , 2010 .

[25]  A. Banerjee,et al.  A Simple Model of Herd Behavior , 1992 .

[26]  Magnus Enquist,et al.  Social Learning : A Solution to Rogers ’ s Paradox of Nonadaptive Culture , 2007 .

[27]  Steven Johnson,et al.  Where good ideas come from : the seven patterns of innovation , 2010 .

[28]  F. D’Agostino.  From the organization to the division of cognitive labor , 2009 .

[29]  David L. Hull,et al.  Science as a Process: An Evolutionary Account of the Social and Conceptual Development of Science, David L. Hull. 1988. The University of Chicago Press, Chicago, IL. 608 pages. ISBN: 0-226-35060-4. $39.95 , 1989 .

[30]  Kevin J. S. Zollman.  The Epistemic Benefit of Transient Diversity , 2009 .

[31]  Alvin I. Goldman,et al.  A Guide to Social Epistemology , 2012 .

[32]  M. Fricker.  FORUM: Miranda FRICKER's Epistemic Injustice. Power and the Ethics of Knowing , 2008, THEORIA.

[33]  Michael Strevens,et al.  The role of the priority rule in science , 2003 .

[34]  Uta Berger,et al.  Robustness analysis: Deconstructing computational models for ecological theory and applications , 2016 .

[35]  Ryan Muldoon,et al.  Epistemic Landscapes and the Division of Cognitive Labor* , 2009, Philosophy of Science.

[36]  Johannes Himmelreich,et al.  Epistemic Landscapes, Optimal Search, and the Division of Cognitive Labor , 2015, Philosophy of Science.