Mandevillian intelligence

Mandevillian intelligence is a specific form of collective intelligence in which individual cognitive vices (i.e., shortcomings, limitations, constraints and biases) are seen to play a positive functional role in yielding collective forms of cognitive success. The present paper introduces the concept of mandevillian intelligence and reviews a number of strands of empirical research that help to shed light on the phenomenon. The paper also attempts to highlight the value of the concept of mandevillian intelligence from a philosophical, scientific and engineering perspective. Inasmuch as we accept the notion of mandevillian intelligence, then it seems that the cognitive and epistemic value of a specific social or technological intervention will vary according to whether our attention is focused at the individual or collective level of analysis. This has a number of important implications for how we think about the design and evaluation of collective cognitive systems. For example, the notion of mandevillian intelligence forces us to take seriously the idea that the exploitation (or even the accentuation) of individual cognitive shortcomings could, in some situations, provide a productive route to collective forms of cognitive and epistemic success.

[1]  Georg Theiner.  Varieties of Group Cognition , 2014 .

[2]  L. Zonneveld,et al.  Reshaping the human condition: exploring human enhancement , 2008 .

[3]  A. Dussutour,et al.  Noise improves collective decision-making by ants in dynamic environments , 2009, Proceedings of the Royal Society B: Biological Sciences.

[4]  G. Edelman.  Neural Darwinism: The Theory Of Neuronal Group Selection , 1989 .

[5]  E. Sosa.  A Virtue Epistemology , 2007 .

[6]  J. Baehr.  Character, Reliability, and Virtue Epistemology , 2006 .

[7]  Jan Lorenz,et al.  The wisdom of crowds in one mind: How individuals can simulate the knowledge of diverse societies to reach better decisions , 2011 .

[8]  Yaakov Kareev.  Advantages of Cognitive Limitations , 2012 .

[9]  Daniel A. Levinthal,et al.  Exploration and Exploitation in Organizational Learning , 2007 .

[10]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[11]  Eli Pariser,et al.  The Filter Bubble: What the Internet Is Hiding from You , 2011 .

[12]  J. Dessalles,et al.  Arguing, reasoning, and the interpersonal (cultural) functions of human consciousness , 2011, Behavioral and Brain Sciences.

[13]  L. Zagzebski.  Virtues of the Mind: An Inquiry into the Nature of Virtue and the Ethical Foundations of Knowledge , 1996 .

[14]  J. Baehr.  Four Varieties of Character-Based Virtue Epistemology , 2008 .

[15]  Michael S. Brady,et al.  The Epistemic Life of Groups: Essays in the Epistemology of Collectives , 2016 .

[16]  James A. Hendler,et al.  From the Semantic Web to social machines: A research challenge for AI on the World Wide Web , 2010, Artif. Intell..

[17]  Jeffrey R. Stevens,et al.  Evolution and the mechanisms of decision making , 2012 .

[18]  Thomas W. Simpson,et al.  Evaluating Google as an Epistemic Tool , 2012 .

[19]  Karl J. Friston.  Functional and Effective Connectivity: A Review , 2011, Brain Connect..

[20]  Verlin B. Hinsz,et al.  The emerging conceptualization of groups as information processors. , 1997, Psychological bulletin.

[21]  L. Macchi,et al.  Thinking : psychological perspectives on reasoning, judgment and decision making , 2005 .

[22]  William Hirst,et al.  The Adaptive Function of Distributed Remembering: Contributions to the Formation of Collective Memory , 2013 .

[23]  M. Moulins,et al.  Dynamic construction of a neural network from multiple pattern generators in the lobster stomatogastric nervous system , 1994, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[24]  M. Kearns,et al.  An Experimental Study of the Coloring Problem on Human Subject Networks , 2006, Science.

[25]  R. Nickerson.  Confirmation Bias: A Ubiquitous Phenomenon in Many Guises , 1998 .

[26]  Dennis Whitcomb,et al.  Social Epistemology: Essential Readings , 2011 .

[27]  Thomas D. Seeley,et al.  Imprecision in waggle dances of the honeybee (Apis mellifera) for nearby food sources: error or adaptation? , 1999, Behavioral Ecology and Sociobiology.

[28]  Robert L. Goldstone,et al.  Author ' s personal copy Recognizing group cognition Action editor : , 2010 .

[29]  Aniket Kittur,et al.  Augmented Social Cognition , 2008, AAAI Spring Symposium: Social Information Processing.

[30]  Monika Richter,et al.  Cognition In The Wild , 2016 .

[31]  Pietro Michelucci,et al.  The power of crowds , 2016, Science.

[32]  A. Selverston.  Modulation of circuits underlying rhythmic behaviors , 1995, Journal of Comparative Physiology A.

[33]  Michael C. Mozer,et al.  Skeletonization: A Technique for Trimming the Fat from a Network via Relevance Assessment , 1988, NIPS.

[34]  Alex Pentland,et al.  The data-driven society. , 2013, Scientific American.

[35]  Nick Bostrom,et al.  Cognitive Enhancement : Methods , Ethics , Regulatory Challenges ( 2006 ) , 2006 .

[36]  Lu Hong,et al.  Groups of diverse problem solvers can outperform groups of high-ability problem solvers. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[37]  Edwin Hutchins,et al.  The social organization of distributed cognition , 1991, Perspectives on socially shared cognition.

[38]  John R Anderson,et al.  An integrated theory of the mind. , 2004, Psychological review.

[39]  C. Sunstein,et al.  Deliberating Groups versus Prediction Markets (or Hayek's Challenge to Habermas) , 2006, Episteme.

[40]  James Surowiecki.  The wisdom of crowds: Why the many are smarter than the few and how collective wisdom shapes business, economies, societies, and nations Doubleday Books. , 2004 .

[41]  Yevgeniy Vorobeychik,et al.  Behavioral dynamics and influence in networked coloring and consensus , 2010, Proceedings of the National Academy of Sciences.

[42]  P. Todd,et al.  More Is Not Always Better: The Benefits of Cognitive Limits , 2003 .

[43]  Johnny Nhan,et al.  Digilantism: An Analysis of Crowdsourcing and the Boston Marathon Bombings , 2015 .

[44]  N. Kerr,et al.  Group performance and decision making. , 2004, Annual review of psychology.

[45]  A. Tversky,et al.  Judgment under Uncertainty: Heuristics and Biases , 1974, Science.

[46]  Gregorio Convertino,et al.  The CACHE Study: Group Effects in Computer-supported Collaborative Analysis , 2008, Computer Supported Cooperative Work (CSCW).

[47]  Chris Arney.  Social Physics: How Good Ideas Spread - the Lessons from a New Science , 2014 .

[48]  R. Scott Tindale,et al.  Accentuation of information processes and biases in group judgments integrating base-rate and case-specific information , 2008 .

[49]  Francis Heylighen,et al.  From Human Computation to the Global Brain: The Self-Organization of Distributed Intelligence , 2013, Handbook of Human Computation.

[50]  David Reitter,et al.  Social Cognition: Memory Decay and Adaptive Information Filtering for Robust Information Maintenance , 2012, AAAI.

[51]  Robert L. Goldstone,et al.  Propagation of innovations in networked groups. , 2008, Journal of experimental psychology. General.

[52]  Jennifer Lackey,et al.  Essays in Collective Epistemology , 2014 .

[53]  Winter A. Mason,et al.  Collaborative learning in networks , 2011, Proceedings of the National Academy of Sciences.

[54]  R. Hastie,et al.  The common knowledge effect: Information sharing and group judgment. , 1993 .

[55]  Eliot R. Smith,et al.  Situating Social Influence Processes: Dynamic, Multidirectional Flows of Influence Within Social Networks , 2007, Personality and social psychology review : an official journal of the Society for Personality and Social Psychology, Inc.

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

[57]  I. Couzin.  Collective cognition in animal groups , 2009, Trends in Cognitive Sciences.

[58]  D. Bjorklund.  The role of immaturity in human development. , 1997, Psychological bulletin.

[59]  J. Baehr.  The Inquiring Mind: On Intellectual Virtues and Virtue Epistemology , 2011 .

[60]  Michael C. Mozer,et al.  Using Relevance to Reduce Network Size Automatically , 1989 .

[61]  E. Marder,et al.  Understanding circuit dynamics using the stomatogastric nervous system of lobsters and crabs. , 2007, Annual review of physiology.

[62]  Luc Berthouze,et al.  Adaptivity through physical immaturity , 2002 .

[63]  Friederike Mengel,et al.  Limited memory can be beneficial for the evolution of cooperation. , 2012, Journal of theoretical biology.

[64]  Nick Chater,et al.  Networks in Cognitive Science , 2013, Trends in Cognitive Sciences.

[65]  Miriam Solomon,et al.  Scientific Rationality and Human Reasoning , 1992, Philosophy of Science.

[66]  William Hirst,et al.  Memory's Malleability: Its Role in Shaping Collective Memory and Social Identity , 2012, Front. Psychology.

[67]  Bo Xu,et al.  Individual irrationality, network structure, and collective intelligence: An agent-based simulation approach , 2016, Complex..

[68]  Guy Theraulaz,et al.  The biological principles of swarm intelligence , 2007, Swarm Intelligence.

[69]  G. Stasser,et al.  Hidden Profiles: A Brief History , 2003 .

[70]  T. Ash,et al.  Dynamic node creation in backpropagation networks , 1989, International 1989 Joint Conference on Neural Networks.

[71]  Michael Kearns,et al.  Experiments in social computation , 2012, KDD.

[72]  Alice M. Mulvehill,et al.  Social Machines , 2016, Apress.

[73]  Pietro Michelucci,et al.  Handbook of Human Computation , 2013, Springer New York.

[74]  James A. R. Marshall,et al.  Swarm Cognition: an interdisciplinary approach to the study of self-organising biological collectives , 2011, Swarm Intelligence.

[75]  Michael S. Bernstein,et al.  Human-Computer Interaction and Collective Intelligence , 2014 .

[76]  Isaac Record,et al.  JUSTIFIED BELIEF IN A DIGITAL AGE: ON THE EPISTEMIC IMPLICATIONS OF SECRET INTERNET TECHNOLOGIES , 2013, Episteme.

[77]  John Greco,et al.  Virtue epistemology : contemporary readings , 2012 .

[78]  Ian D. Turner.  Rationality, Foolishness and Adaptive Intelligence , 2006 .

[79]  A. Benjamin,et al.  Smaller is better (when sampling from the crowd within): Low memory-span individuals benefit more from multiple opportunities for estimation. , 2010, Journal of experimental psychology. Learning, memory, and cognition.

[80]  Siddhartha Bhattacharyya,et al.  Social creativity as a function of agent cognition and network properties: A computer model , 2010, Soc. Networks.

[81]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[82]  Graham Kendall,et al.  Search Methodologies: Introductory Tutorials in Optimization and Decision Support Techniques , 2013 .

[83]  Thierry Olive,et al.  Working Memory in Writing: Empirical Evidence From the Dual-Task Technique , 2004 .

[84]  Paul R. Smart,et al.  Dynamic Networks and Distributed Problem-Solving , 2010 .

[85]  Michael S. Bernstein,et al.  Handbook of Collective Intelligence , 2015 .

[86]  S. Moscovici,et al.  Biased information search in group decision making. , 2000, Journal of Personality and Social Psychology.

[87]  D. Myers,et al.  The group polarization phenomenon. , 1976 .

[88]  Winter A. Mason,et al.  Collective Search as Human Computation , 2013, Handbook of Human Computation.

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

[90]  John R. Anderson.  How Can the Human Mind Occur in the Physical Universe , 2007 .