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

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

    Research output: Contribution to journalArticlepeer-review

    10 Scopus citations

    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.

    Original languageEnglish (US)
    Pages (from-to)319-335
    Number of pages17
    JournalPlanning Theory and Practice
    Volume16
    Issue number3
    DOIs
    StatePublished - Jul 3 2015

    Bibliographical note

    Publisher Copyright:
    © 2015 Taylor & Francis.

    Keywords

    • agent-based modelling
    • aquifer planning
    • collaboration
    • plan making
    • social learning

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