In the 21st century, decision makers are faced with global challenges that involve high complexity and deep uncertainties. In response to these challenges, systems models used for decision making increasingly acknowledge uncertainty in addition to complexity. Instead of predicting a best-estimate future and optimal policy, model-based studies explore a wide variety of futures, and search for robust and adaptive policies. Thus, the ‘purpose’ of model use changes.
‘Fit for purpose’ is the main criterion for determining the validity of systems models regardless of the modeling methodology. Hence, a change in the purpose implies a change in the requirements for a valid and plausible model. For instance, models were traditionally expected to be robust, rather than showing behavioral sensitivity to their inputs. However, to accommodate deep uncertainties, e.g., the consequences of unknown unknowns, shocks or structural changes, they now need to generate a rich diversity of scenarios.
This research aims to investigate the desired characteristics of models used for dealing with uncertainty, and to outline a validation process with respect to the established validation techniques. The end result will be a framework for testing the validity of uncertainty-oriented systems models and recommendations for their validation. This framework can guide the development and use of systems models in futures studies that systematically address uncertainty, and strengthen their credibility for assisting 21st century decision making.
Funding: IIASA Postdoctoral Program
Program: Advanced Systems Analysis, Ecosystems Services Management, and Water Programs
Dates: July 2017 – present
Last edited: 03 October 2019
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