COGNITIVE BIAS IN PROFESSIONAL JUDGMENT
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1 COGNITIVE BIAS IN PROFESSIONAL JUDGMENT Dr. Janet L Sutton, PhD Behavioral Economist, Senior Research Psychologist U.S. Department of Defense (retired): -Air Force Research Laboratory (AFRL, Wright-Patterson AFB) -Army Research Laboratory (ARL, Ft. Sill, OK) 1
2 AGENDA 1. Definition of Terms 2. General Causes of Cognitive Biases 3. Interventions 4. Specific Example: Fundamental Attribution Error 5. Demonstration of Potential Cognitive Biases 6. Summary of Key Points 7. References * *Handout available: Scientific basis for researched Cognitive biases specifically relevant to the professional field of engineering 2
3 DEFINITION OF TERMS DEFINITION SOURCE Ethics The rules of conduct recognized in respect to a particular class of human actions or a particular group or culture Social system - External Morals Principles or habits with respect to right or wrong conduct. Morality is ultimately a personal compass Individual - Internal Because society says it is the right COMPLIANCE thing to do FLEXIBILITY Ethics are dependent on others for definition. They tend to be consistent within a certain context, but can vary between contexts Because we believe in something being right or wrong Usually consistent, although can change if an individual s beliefs change ORIGIN Greek word "ethos" meaning character" Latin word "mos" meaning "custom" ACCEPT- ABILITY Ethics are governed by professional and legal guidelines within a particular time and place Morality transcends cultural norms 3
4 ENGINEERINGS SCIENCES Engineering sciences emerged against the Rational Choice model of traditional economics A rational person is assumed: To correctly weigh costs, benefits, outcomes To know personal preferences Have perfect self-control To have the ability to constrain impulses 4
5 BEHAVIORAL ECONOMICS Behavioral Economics and Social Psychology introduced scientific evidence of Cognitive Biases affecting professional judgment -limited cognitive abilities -trouble exercising self-control -profoundly influenced by context 5
6 ENGINEERING & PSYCHOLOGY Together, these fields of research help provide a framework to understand when and how people make errors Systematic errors or biases recur predictably in certain circumstances 6
7 GENERAL CAUSES OF BIAS 1. Heuristics 2. Illusions 3. Group processes including groupthink 4. Psychological phenomena 5. Human cognitive limitations 6. Motivational factors 7
8 DISCIPLINE-SPECIFIC BIAS Anchoring Bias Adjustment Bias Attentional Bias Availability Bias Bandwagon Effect Belief Perseverance Over-confidence Bias Confirmation Bias Contrast Effect Default Bias End-user Bias Endowment Effect Fixation Framing Effect Halo Effect Hindsight Bias Hyperbolic Discounting IKEA Effect Information Bias Infrastructure Bias Invincibility Bias Knowledge Engineer Mere Exposure Effect Miserly Info Processing Neglect of Probability Normalcy Effects Over-optimism Bias Parkinson s Law Effect Pessimism Bias Planning Fallacy Popularity Bias Primacy / Recency Effects Representativeness Selective Perception Semantic Fallacy Semmelweis Reflex Sequence Impact Situation Bias Status Quo Bias Subject Matter Expert Sunk Cost Fallacy Technical Bias Time-based Bias Valence Effect Validation Bias Validity Effect Wishful Thinking 8
9 DE-BIASING INTERVENTIONS Commonly Proposed A. Warn about the possibility of bias without specifying its nature B. Describe the direction (and perhaps extent) of the bias that is typically observed C. Provide a dose of feedback, personalizing the implications of the warning D. Offer an extended program of training with feedback, coaching, and whatever else it takes to afford the respondent cognitive mastery of the task More Effective E. Incorporate awareness of the potential for SPECIFIC cognitive biases to influence professional judgment into the decision-making process F. Collect a team of people who will PROACTIVELY offer opposing viewpoints and challenge the conventional wisdom of the group. G. Play Devil s Advocate IN WRITING! H. EXPECT THE INEVITABLE BIAS and address it head-on 9
10 FUNDAMENTAL ATTRIBUTION ERROR (FAE) Asks the question, to what factors do I attribute observed or expressed thoughts, feelings, or behavior of others? Illustrates the brain s genuine desire to understand a situation and the behavior that occurred in that situation in a logical way 10
11 AVOIDING OF THE FAE BIAS Become aware of and knowledgeable about this common Cognitive Bias Put yourself in the other person s shoes Commit to acknowledging your potential for falling back on this bias when making professional judgments The Fundamental Attribution Error (FAE) FREQUENTLY leads to other cognitive biases 11
12 DEMONSTRATION Attribution Bias To what degree do you think the following factors contributed to Dr. Greer s success? Ability as a doctor Motivation to be successful as a doctor The ease of the goal Good luck Story-line Review 12
13 AVERAGE SCORE ABQ SPE DEMO RESULTS ATTRIBUTION FOR SUCCESS 13
14 SUMMARY OF KEY POINTS Cognitive bias in professional judgment is the tendency to make decisions or take action in an unknowingly irrational way Considerable scientific evidence exists for identifying domain-specific Cognitive Bias in the engineering disciplines Acceptance of the potential for Cognitive Bias to impact professional judgment is the first step in ethical decision-making 14
15 Abbreviated Reference List* Bahill, A.T., Son, Y.J., Smith, E.D., and Piattelli-Palmarini, M. (2007). Ameliorating Mental Mistakes in Trade Off Studies, Systems Engineering Brocas, I., Carrillo JD (2013). Dual-process theories of decision-making: A selective survey. Journal of Economic Psychology, Fischoff, B. (1982). Debiasing, in Judgment under Uncertainty: Heuristics and Biases, D. Kahneman, P. Slovic, and A. Tversky, Eds. Cambridge, USA: Cambridge University Press Kahneman, Daniel (2011). Thinking, Fast and Slow, New York: Farrar, Straus and Giroux Kurzban, Robert (2011). Why Everyone (Else) Is a Hypocrite: Evolution and the Modular Mind. Princeton University Press Smith, E.D. (2006). "Tradeoff Studies and Cognitive Biases," Department of Systems and Industrial Engineering, University of Arizona Tversky, T., and Kahneman, D. (2004). Advances in prospect theory: Cumulative representation of uncertainty, MIT Press, Cambridge Massachusetts 15
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