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SOLVING TOMORROW'S DESIGN CHALLENGES REQUIRES NEW TOOLS FOR LARGE WORLD DECISION-MAKING

Published online by Cambridge University Press:  19 June 2023

Scott Ferguson ,
Kye Drobac  and
Kenneth M. Bryden
Scott Ferguson*
Affiliation:
North Carolina State University;
Kye Drobac
Affiliation:
North Carolina State University;
Kenneth M. Bryden
Affiliation:
Iowa State University
*
Ferguson, Scott, North Carolina State University, United States of America, [email protected]

Abstract

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Engineering design research has largely focused on normative models of decision analysis based on small world causal frames where uncertainty can be resolved as probabilities or probability distributions. However, today we need to design solutions for our built environment that are sustainable, just, and able to adapt. Because of the scale and complexity of our world, designs that address sustainability, justice, and adaptability are dominated by unresolvable uncertainty. This requires large world frames and new engineering design frameworks and tools that provide a much broader and nuanced understanding of the impact of our engineering decisions. In this paper we propose that these tools will need to link quantitative and qualitative data and engineering judgment using narrative decision-making processes. To support this, we provide two examples where engineering decision-making is based in part on narrative processes. We then identify five research areas that require additional research to support large-world frames including (1) how can we create microcosms that enable transition between large- and small-world frames and (2) how engineers develop conviction to act using the narratives they create.

Keywords

SustainabilityDecision makingUncertaintyNarrativeLarge world frames
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 3195 - 3204
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2023. Published by Cambridge University Press

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