A Visual Analytics Approach to Combat Confirmation Bias for a Local Food Bank
- 823 Downloads
In the fight against hunger, Food Banks must routinely make strategic distribution decisions under uncertain supply (donations) and demand. One of the challenges facing the decision makers is that they tend to rely heavily on their prior experiences to make decisions, a phenomenon called cognitive bias. This preliminary study seeks to address cognitive bias through a visual analytics approach in the decision-making process. Using certain food bank data, interactive dashboards were prepared as an alternative to the customary spreadsheet format. A preliminary study was conducted to evaluate the effectiveness of the dashboard and results indicated dashboards reduced the amount of confirmation bias.
KeywordsHuman factors Human-Systems integration Cognitive bias Visual analytics
The study is supported in part by a National Science Foundation grant - PFI: Flexible Equitable Efficient Effective Distribution (FEEED) (Award number: 1718672).
- 2.Haselton, M.G., Nettle, D., Murray, D.R.: The Evolution of Cognitive Bias. In: The Handbook of Evolutionary Psychology (2005)Google Scholar
- 4.Bazerman, M.H., Moore, D.: Judgment in Managerial Decision Making. Wiley, New York (2008)Google Scholar
- 5.Caledonia: Wiley (2009)Google Scholar
- 6.Lewicki, R.J., Saunders, D., Barry, B.: Negotiation. McGraw Hill, New York (2005)Google Scholar
- 8.Pirolli, P., Card, S.: The sensemaking process and leverage points for analyst technology as identified through cognitive task analysis. In: Proceedings of International Conference on Intelligence Analysis, vol. 5, pp. 2–4, May 2005Google Scholar
- 11.Keim, D.A., Mansmann, F., Schneidewind, J., Thomas, J., Ziegler, H.: Visual analytics: scope and challenges. In: Visual Data Mining, pp. 76–90. Springer, Heidelberg (2008)Google Scholar
- 12.Cook, K.A., Thomas, J.J.: Illuminating the path: the research and development agenda for visual analytics (2005)Google Scholar
- 13.Denmark, D., Harker, D., McCollough, A.: Interliminal design: mitigating cognitive bias and design distortion (2013)Google Scholar
- 14.Nussbaumer, A., Verbert, K., Hillemann, E.C., Bedek, M.A., Albert, D.: A framework for cognitive bias detection and feedback in a visual analytics environment. In: European Intelligence and Security Informatics Conference (EISIC), pp. 148–151. IEEE, August 2016Google Scholar
- 15.Pohl, M., Winter, L.C., Pallaris, C., Attfield, S., Wong, B.W.: Sensemaking and cognitive bias mitigation in visual analytics. In: 2014 IEEE Joint Intelligence and Security Informatics Conference (JISIC), pp. 323–323. IEEE, September 2014Google Scholar
- 16.Wall, E., Blaha, L.M., Franklin, L., Endert, A.: Warning, bias may occur: a proposed approach to detecting cognitive bias in interactive visual analytics. In: IEEE Conference on Visual Analytics Science and Technology (2017)Google Scholar