Why Expertise Matters: A Response to the Challenges

Five different scientific communities are challenging the abilities of experts and even the very concept of expertise: the decision research community, the sociology community, the heuristics and biases community, the evidence-based practices community, and the computer science community (including the fields of artificial intelligence, automation, and big data). Although each of these communities has made important contributions, the challenges they pose are misguided. This essay describes the problems with each challenge and encourages researchers in the five communities to explore ways of moving forward to improve the capabilities of experts.

[1]  K. Holyoak,et al.  Pragmatic versus syntactic approaches to training deductive reasoning , 1986, Cognitive Psychology.

[2]  K. Knorr-Cetina.  The Manufacture of Knowledge , 1981 .

[3]  Michael Marien,et al.  Book Review: The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies , 2014 .

[4]  R. Hogarth,et al.  Judging probable cause. , 1986 .

[5]  Julia Evetts,et al.  Professionalism: Value and ideology , 2013 .

[6]  Lucy Suchman.  Plans and situated actions: the problem of human-machine communication , 1987 .

[7]  Maarten Sierhuis,et al.  Beyond Cooperative Robotics: The Central Role of Interdependence in Coactive Design , 2011, IEEE Intelligent Systems.

[8]  Kurt Salzinger,et al.  Clinical, Statistical, and Broken-Leg Predictions , 2005 .

[9]  Gary Klein,et al.  Can We Trust Best Practices? Six Cognitive Challenges of Evidence-Based Approaches , 2016 .

[10]  M. Lynch,et al.  Scientific Practice and Ordinary Action , 1993 .

[11]  J. Gregory Trafton,et al.  Minding the Weather: How Expert Forecasters Think , 2017 .

[12]  J. Kagan,et al.  Rational choice in an uncertain world , 1988 .

[13]  Jeffrey M. Bradshaw,et al.  Ten Challenges for Making Automation a "Team Player" in Joint Human-Agent Activity , 2004, IEEE Intell. Syst..

[14]  Robert L Wears,et al.  The Rush from Judgment. , 2017, Annals of emergency medicine.

[15]  Mary Susan Weldon,et al.  Remembering as a social process , 2000 .

[16]  Kenneth M. Ford,et al.  Expertise in context: personally constructed, socially selected and reality-relevant? , 1997 .

[17]  Etienne Wenger,et al.  Communities of Practice: Learning, Meaning, and Identity , 1998 .

[18]  Rob Johnston.  Analytic Culture in the U.S. Intelligence Community: An Ethnographic Study , 2012 .

[19]  Charles Anderson,et al.  The end of theory: The data deluge makes the scientific method obsolete , 2008 .

[20]  Robert R. Hoffman,et al.  The myths and costs of autonomous weapon systems , 2016 .

[21]  Erik Brynjolfsson,et al.  The second machine age: work, progress, and prosperity in a time of brilliant technologies, 1st Edition , 2014 .

[22]  Jeffrey M. Bradshaw,et al.  The Seven Deadly Myths of "Autonomous Systems" , 2013, IEEE Intelligent Systems.

[23]  Baruch Fischhoff,et al.  Eliciting knowledge for analytical representation , 1989, IEEE Trans. Syst. Man Cybern..

[24]  D. Lazer,et al.  The Parable of Google Flu: Traps in Big Data Analysis , 2014, Science.

[25]  Ira Solomon,et al.  Effects of alternative sample space representations on the accuracy of auditors' uncertainty judgments , 1987 .

[26]  Charles A. Doswell,et al.  On the Use of Mesoscale and Cloud-Scale Models in Operational Forecasting , 1992 .

[27]  Lewis R. Goldberg,et al.  Methodological critiques. Seer over sign: The first "good" example? , 1968 .

[28]  H. Mieg.  The Cambridge Handbook of Expertise and Expert Performance: Social and Sociological Factors in the Development of Expertise , 2006 .

[29]  Jean Lave,et al.  Situating learning in communities of practice , 1991, Perspectives on socially shared cognition.

[30]  A. Tversky,et al.  Prospect Theory : An Analysis of Decision under Risk Author ( s ) : , 2007 .

[31]  Gary Klein,et al.  Rapid Decision Making on the Fire Ground , 1986 .

[32]  Norman G. Lederman,et al.  The Death of Expertise , 2014 .

[33]  R. Dawes.  Judgment under uncertainty: The robust beauty of improper linear models in decision making , 1979 .

[34]  Jeffrey M. Bradshaw,et al.  Seven Cardinal Virtues of Human-Machine Teamwork: Examples from the DARPA Robotic Challenge , 2014, IEEE Intelligent Systems.

[35]  Gerd Gigerenzer,et al.  The "conjunction fallacy" revisited : How intelligent inferences look like reasoning errors , 1999 .