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Seeing is not believing: cognitive bias and modelling in collaborative planning

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  • Charles Hoch
  • Moira Zellner
  • Dan Milz
  • Josh Radinsky
  • Leilah Lyons

Abstract

Planners making groundwater plans often use scientific hydrological forecasts to estimate long term the risk of water depletion. We study a group of Chicago planners and stakeholders who learned to use and helped develop agent-based models (ABM) of coupled land-use change and groundwater flow, to explore the effects of resource use and policy on future groundwater availability. Using discourse analysis, we found planners learned to play with the ABM to judge complex interaction effects. The simulation results challenged prior policy commitments, and instead of reconsidering those commitments to achieve sustainability, participants set aside the ABM and the lessons learned with them. Visualizing patterns of objections and agreements in the dialogue enabled us to chart how clusters of participants gradually learned to grasp and interpret the simulated effects of individual and policy decisions even as they struggled to incorporate them into their deliberations.

Suggested Citation

  • Charles Hoch & Moira Zellner & Dan Milz & Josh Radinsky & Leilah Lyons, 2015. "Seeing is not believing: cognitive bias and modelling in collaborative planning," Planning Theory & Practice, Taylor & Francis Journals, vol. 16(3), pages 319-335, September.
    • Handle: RePEc:taf:rptpxx:v:16:y:2015:i:3:p:319-335
    DOI: 10.1080/14649357.2015.1045015
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    Cited by:

    1. Ahmad Farhan Roslan & Terrence Fernando & Sara Biscaya & Noralfishah Sulaiman, 2021. "Transformation towards Risk-Sensitive Urban Development: A Systematic Review of the Issues and Challenges," Sustainability, MDPI, vol. 13(19), pages 1-24, September.
    2. Boeing, Geoff, 2017. "Methods and Measures for Analyzing Complex Street Networks and Urban Form," SocArXiv 93h82, Center for Open Science.

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