Mitigating the Attraction Effect with Visualizations

Human decisions are prone to biases, and this is no less true for decisions made within data visualizations. Bias mitigation strategies often focus on the person, by educating people about their biases, typically with little success. We focus instead on the system, presenting the first evidence that altering the design of an interactive visualization tool can mitigate a strong bias – the attraction effect. Participants viewed 2D scatterplots where choices between superior alternatives were affected by the placement of other suboptimal points. We found that highlighting the superior alternatives weakened the bias, but did not eliminate it. We then tested an interactive approach where participants completely removed locally dominated points from the view, inspired by the elimination by aspects strategy in the decision-making literature. This approach strongly decreased the bias, leading to a counterintuitive suggestion: tools that allow removing inappropriately salient or distracting data from a view may help lead users to make more rational decisions.

[1]  M. F. Luce,et al.  Constructive Consumer Choice Processes , 1998 .

[2]  Tomek Strzalkowski,et al.  Testing the Power of Game Lessons: The Effects of Art and Narrative on Reducing Cognitive Biases , 2014, DiGRA.

[3]  Christopher P. Puto,et al.  Adding Asymmetrically Dominated Alternatives: Violations of Regularity & the Similarity Hypothesis. , 1981 .

[4]  S. Moscovici,et al.  The group as a polarizer of attitudes. , 1969 .

[5]  Daniel Afergan,et al.  Improving Bayesian Reasoning: The Effects of Phrasing, Visualization, and Spatial Ability , 2016, IEEE Transactions on Visualization and Computer Graphics.

[6]  I. Simonson,et al.  Choice Based on Reasons: The Case of Attraction and Compromise Effects , 1989 .

[7]  D. Krantz,et al.  The effects of statistical training on thinking about everyday problems , 1986, Cognitive Psychology.

[8]  Heike Hofmann,et al.  Graphical inference for infovis , 2010, IEEE Transactions on Visualization and Computer Graphics.

[9]  Pierre Dragicevic,et al.  Assessing the Effect of Visualizations on Bayesian Reasoning through Crowdsourcing , 2012, IEEE Transactions on Visualization and Computer Graphics.

[10]  Eric J. Johnson,et al.  The adaptive decision maker , 1993 .

[11]  Richard E. Nisbett,et al.  A longitudinal study of the effects of undergraduate training on reasoning. , 1990 .

[12]  Steven F. Roth,et al.  On the semantics of interactive visualizations , 1996, Proceedings IEEE Symposium on Information Visualization '96.

[13]  John T. Stasko,et al.  Toward a Deeper Understanding of the Role of Interaction in Information Visualization , 2007, IEEE Transactions on Visualization and Computer Graphics.

[14]  Mary Czerwinski,et al.  An exploratory study of co-located collaborative visual analytics around a tabletop display , 2010, 2010 IEEE Symposium on Visual Analytics Science and Technology.

[15]  Peter Wright Consumer Choice Strategies: Simplifying Vs. Optimizing , 1975 .

[16]  Andrew S. Hanks,et al.  Trigger Foods: The Influence of “Irrelevant” Alternatives in School Lunchrooms , 2012, Agricultural and Resource Economics Review.

[17]  Oded Nov,et al.  How Deceptive are Deceptive Visualizations?: An Empirical Analysis of Common Distortion Techniques , 2015, CHI.

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

[19]  B. Fischhoff,et al.  Knowing with Certainty: The Appropriateness of Extreme Confidence. , 1977 .

[20]  Paolo Crosetto,et al.  Testing the Strength and Robustness of the Attraction Effect in Consumer Decision Making , 2015 .

[21]  Gerd Gigerenzer,et al.  Homo Heuristicus: Why Biased Minds Make Better Inferences , 2009, Top. Cogn. Sci..

[22]  William M. Hedgcock,et al.  Trade-Off Aversion as an Explanation for the Attraction Effect: A Functional Magnetic Resonance Imaging Study , 2009 .

[23]  Emre Soyer,et al.  The Illusion of Predictability: How Regression Statistics Mislead Experts , 2011 .

[24]  Henry Been-Lirn Duh,et al.  To Risk or Not to Risk?: Improving Financial Risk Taking of Older Adults by Online Social Information , 2015, CSCW.

[25]  S. Mamede,et al.  Cognitive debiasing 1: origins of bias and theory of debiasing , 2013, BMJ quality & safety.

[26]  Richard P. Larrick,et al.  Strategies for revising judgment: how (and how well) people use others' opinions. , 2009, Journal of experimental psychology. Learning, memory, and cognition.

[27]  Georges G. Grinstein,et al.  Visualization for knowledge discovery , 1992, Int. J. Intell. Syst..

[28]  Pierre Dragicevic,et al.  The Attraction Effect in Information Visualization , 2017, IEEE Transactions on Visualization and Computer Graphics.

[29]  Alex Endert,et al.  Warning, Bias May Occur: A Proposed Approach to Detecting Cognitive Bias in Interactive Visual Analytics , 2017, 2017 IEEE Conference on Visual Analytics Science and Technology (VAST).

[30]  Tamara Munzner,et al.  Visualization Analysis and Design , 2014, A.K. Peters visualization series.

[31]  S. Plous The psychology of judgment and decision making , 1994 .

[32]  P. Resnick,et al.  Hypothetical Outcome Plots Outperform Error Bars and Violin Plots for Inferences about Reliability of Variable Ordering , 2015, PloS one.

[33]  J. Payne,et al.  Let's be Honest about the Attraction Effect , 2014 .

[34]  R. Dawes,et al.  Heuristics and Biases: Clinical versus Actuarial Judgment , 2002 .

[35]  Thomas Mussweiler,et al.  Overcoming the Inevitable Anchoring Effect: Considering the Opposite Compensates for Selective Accessibility , 2000 .

[36]  Carey K. Morewedge,et al.  Debiasing Decisions , 2015 .

[37]  Wedell,et al.  Examining Models of Nondominated Decoy Effects across Judgment and Choice. , 2000, Organizational behavior and human decision processes.

[38]  D. Kahneman A perspective on judgment and choice: mapping bounded rationality. , 2003, The American psychologist.

[39]  M. Sheelagh T. Carpendale,et al.  Visualization of Uncertainty and Reasoning , 2007, Smart Graphics.

[40]  Marc Streit,et al.  WeightLifter: Visual Weight Space Exploration for Multi-Criteria Decision Making , 2017, IEEE Transactions on Visualization and Computer Graphics.

[41]  A. Tversky,et al.  Subjective Probability: A Judgment of Representativeness , 1972 .

[42]  André Calero Valdez,et al.  Priming and Anchoring Effects in Visualization , 2018, IEEE Transactions on Visualization and Computer Graphics.

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

[44]  Robin M. Hogarth,et al.  A note on aggregating opinions , 1978 .

[45]  H. Simon,et al.  Rational choice and the structure of the environment. , 1956, Psychological review.

[46]  Giuseppe Carenini,et al.  An empirical evaluation of interactive visualizations for preferential choice , 2008, AVI '08.

[47]  A. Tversky Elimination by aspects: A theory of choice. , 1972 .

[48]  Colin Camerer,et al.  The Effects of Financial Incentives in Experiments: A Review and Capital-Labor-Production Framework , 1999 .

[49]  Nelson L. Max,et al.  A characterization of the scientific data analysis process , 1992, Proceedings Visualization '92.

[50]  N. Schwarz,et al.  When debiasing backfires: accessible content and accessibility experiences in debiasing hindsight. , 2002, Journal of experimental psychology. Learning, memory, and cognition.

[51]  Giuseppe Carenini,et al.  ValueCharts: analyzing linear models expressing preferences and evaluations , 2004, AVI.

[52]  A. Tversky,et al.  Choice in Context: Tradeoff Contrast and Extremeness Aversion , 1992 .

[53]  Isaac Cho,et al.  The Anchoring Effect in Decision-Making with Visual Analytics , 2017, 2017 IEEE Conference on Visual Analytics Science and Technology (VAST).

[54]  Joshua Klayman,et al.  Debias the environment instead of the judge: an alternative approach to reducing error in diagnostic (and other) judgment , 1993, Cognition.

[55]  D. Kahneman Thinking, Fast and Slow , 2011 .

[56]  Hanan H Balkhy,et al.  Physician 'defiance' towards hand hygiene compliance: Is there a theory-practice-ethics gap? , 2013, Journal of the Saudi Heart Association.

[57]  John T. Stasko,et al.  Low-level components of analytic activity in information visualization , 2005, IEEE Symposium on Information Visualization, 2005. INFOVIS 2005..

[58]  Michael Gleicher,et al.  Error Bars Considered Harmful: Exploring Alternate Encodings for Mean and Error , 2014, IEEE Transactions on Visualization and Computer Graphics.

[59]  R. Fisher Social Desirability Bias and the Validity of Indirect Questioning , 1993 .

[60]  Matthew L. Jensen,et al.  Mitigating Cognitive Bias through the Use of Serious Games: Effects of Feedback , 2014, PERSUASIVE.

[61]  R. Nisbett,et al.  Immediate and delayed transfer of training effects in statistical reasoning. , 1991, Journal of experimental psychology. General.

[62]  Robert L. Goldstone,et al.  Concreteness Fading in Mathematics and Science Instruction: a Systematic Review , 2014 .

[63]  H. Arkes Costs and benefits of judgment errors: Implications for debiasing. , 1991 .

[64]  R. Pohl Cognitive illusions : intriguing phenomena in thinking, judgement and memory , 2017 .

[65]  Scott Highhouse,et al.  Context-Dependent Selection: The Effects of Decoy and Phantom Job Candidates , 1996 .

[66]  Hanspeter Pfister,et al.  LineUp: Visual Analysis of Multi-Attribute Rankings , 2013, IEEE Transactions on Visualization and Computer Graphics.

[67]  Bahador Bahrami,et al.  Deliberation increases the wisdom of crowds , 2017, ArXiv.

[68]  Antonio Jiménez-Martín,et al.  A decision support system for multiattribute utility evaluation based on imprecise assignments , 2003, Decis. Support Syst..

[69]  Ivan Hernandez,et al.  Disfluency disrupts the confirmation bias. , 2013 .

[70]  K. Stanovich,et al.  Cognitive sophistication does not attenuate the bias blind spot. , 2012, Journal of personality and social psychology.

[71]  D. H. Wedell,et al.  Distinguishing Among Models of Contextually Induced Preference Reversals , 1991 .

[72]  Aaron M Scherer,et al.  Effect of Harm Anchors in Visual Displays of Test Results on Patient Perceptions of Urgency About Near-Normal Values: Experimental Study , 2018, Journal of medical Internet research.

[73]  G. Duncan,et al.  Do the Right Thing: Diverging Effects of Accountability in a Managerial Context , 1999 .

[74]  Valerie F Reyna,et al.  Developmental Reversals in Risky Decision Making , 2014, Psychological science.

[75]  Clayton Lewis,et al.  A problem-oriented classification of visualization techniques , 1990, Proceedings of the First IEEE Conference on Visualization: Visualization `90.

[76]  Pierre Dragicevic,et al.  Fair Statistical Communication in HCI , 2016 .

[77]  M. Cadinu,et al.  Self-anchoring and differentiation processes in the minimal group setting. , 1996, Journal of personality and social psychology.

[78]  H. Sebastian Seung,et al.  A solution to the single-question crowd wisdom problem , 2017, Nature.

[79]  A. Rao,et al.  Could Ralph Nader's Entrance and Exit Have Helped Al Gore? The Impact of Decoy Dynamics on Consumer Choice , 2009 .

[80]  S. Sloman,et al.  Base-rate respect: From ecological rationality to dual processes. , 2007, The Behavioral and brain sciences.

[81]  T. A. Hurly,et al.  Irrational choices in hummingbird foraging behaviour , 2002, Animal Behaviour.

[82]  Pierre Dragicevic,et al.  Conceptual and Methodological Issues in Evaluating Multidimensional Visualizations for Decision Support , 2018, IEEE Transactions on Visualization and Computer Graphics.

[83]  Yigang Pan Sue O’Curry,et al.  The Attraction Effect and Political Choice in Two Elections , 1995 .

[84]  Mary L. Cummings,et al.  Automation Bias in Intelligent Time Critical Decision Support Systems , 2004 .

[85]  Richard P. Larrick,et al.  Teaching the Use of Cost-Benefit Reasoning in Everyday Life , 1990 .

[86]  Oded Nov,et al.  Showing People Behind Data: Does Anthropomorphizing Visualizations Elicit More Empathy for Human Rights Data? , 2017, CHI.

[87]  Ken A Paller,et al.  The potato chip really does look like Elvis! Neural hallmarks of conceptual processing associated with finding novel shapes subjectively meaningful. , 2012, Cerebral cortex.

[88]  D Kahneman,et al.  On the reality of cognitive illusions. , 1996, Psychological review.

[89]  Nancy F. Lenfestey,et al.  Cognitive interventions to reduce diagnostic error: a narrative review , 2012, BMJ quality & safety.

[90]  I. Scott MacKenzie,et al.  Fitts' Law as a Research and Design Tool in Human-Computer Interaction , 1992, Hum. Comput. Interact..

[91]  M. Beekman,et al.  Irrational decision-making in an amoeboid organism: transitivity and context-dependent preferences , 2011, Proceedings of the Royal Society B: Biological Sciences.

[92]  G. Loewenstein,et al.  Explaining the Identifiable Victim Effect , 1997 .

[93]  Claus F. Behrens,et al.  The feasibility of using Pareto fronts for comparison of treatment planning systems and delivery techniques , 2009, Acta oncologica.

[94]  Steven F. Roth,et al.  Data characterization for intelligent graphics presentation , 1990, CHI '90.

[95]  Eduardo B. Andrade Excessive confidence in visually-based estimates , 2011 .