Special Issue of the Journal Futures
Steffen Roth, La Rochelle Business School, France, & University of Turku, Finland
Michael Grothe-Hammer, Norwegian University of Science and Technology, Norway
Jari Kaivo-oja, University of Turku & University of Helsinki, Finland
Kristof van Assche, University of Alberta, Canada
Harry F. Dahms, University of Tennessee, Knoxville, USA
Call for Papers
This special issue focuses on the often precarious relationship between evidence and simulation, a topic that has been in need of close examination at least since the early 1970s, when the pioneers of futures studies developed or replicated the first global system dynamics models and computer simulations such as the “World3” model of Meadows et al. (1972).
Ever since, simulations have been applied to a broad spectrum of areas and topics, ranging from business strategy development, to aerospace and aviation engineering, traffic management.
On the one hand, simulations clearly help explore alternatives scenarios (Booth et al., 2009), theorise long waves (Forrester, 1976), anticipate or avoid undesirable short-, medium- or even long-term developments, or replace tests and experiments that would otherwise be unfeasible or dangerous. For example, simulations of nuclear weapons have been deemed sufficiently strong, reliable, and predictive to replace the testing of those weapons.
On the other hand, the 2007-2008 financial crisis had already underscored the tremendous impact and risks of economic models and financial simulations, and simulations also have played a key-role in the 2020 coronavirus crisis, with the results of model or simulation applications often having been confused with, or deliberately presented as evidence. More concretely, in the current crisis, simulations have been or are being used to
- Detect, define, and assess the risk/extent of the COVID-19 pandemic,
- Guide and justify the selection and implementation of the risk mitigation strategies, and
- Assess the efficiency of the risk mitigation strategies.
In situations where problem definition, method choice, and success measurement are all based on simulations, however, we are confronted with the question of how we can at all distinguish between a simulated and an actual crisis. Overreliance on simulations may therefore be associated with the risk of (or suspicion regarding) academic or political dissimulation or immunization strategies that escape conventional forms of control or criticism (Andersen and Pors, 2019; Andersen and Stenner, 2020; Tosini, 2020). If simulations are confused with or replace classical methods, and entire research designs, theories, or fields of research turn into self-confirming networks of simulations, then science may indeed develop immunity against scrutiny and criticism and, thus, once again “become as oppressive as the ideologies it had once to fight” (Feyerabend, 2006, p. 360). Decision-making based on such simulated “truisms” and claims for the future might then result in the implementation of ill-informed or even deceitful policies.
These and similar issues are most critical both in the short-term assessment and management of the current coronavirus crisis and in the medium and long term. In fact, a recent simulation study published in Nature suggests that “prolonged or intermittent social distancing may be necessary into 2022” (Kissler et al., 2020). Given the tremendous extent of different types of collateral damage resulting from lockdowns and other non-pharmaceutical pandemic interventions, the impact simulations currently are having on life in general, and social life, in particular, could hardly be greater.
In the context of Futures Studies, Foresight and Anticipatory Systems, and against this backdrop, we welcome research papers and notes that are cognizant with the thin red lines between simulation and dissimulation, especially if they promise to illuminate general and/or specific aspects of the relationship between dis-/simulation and evidence, or address questions and challenges of the following non-exclusive type:
- Simulation and ontology: What is (a) simulation? Prediction, discussion framework, plausible future?
- Types of simulation: cognitive, prognostic, and crowdsourcing simulations (Zackery et al., 2016). What next?
- Simulation and evidence: Since evidence of future developments and conditions is unavailable, can simulations even reliable predictive tools, and if, how?
- Simulation, counter-factual reasoning, and the social construction of the future (Booth et al., 2009; Fuller and Loogma, 2009).
- Simulation and risk perception: Post-normal science, risk assessment, and risk acceptance in times of uncertain facts and disputed values (Fuller, 2017; Funtowicz & Ravetz, 1993).
- Simulation and normality: The role(s) of simulations in old normal, new normal, and/or post-normal science.
- Open, closed, dynamic, anticipatory, or autopoietic: The impact of systems paradigms on predictive model designs and simulation outcomes (Fuller, 2017).
- Simulations and extrapolation: How to overcome forecasting challenges via multidisciplinary approaches (Orrell and McSharry, 2009)?
- Simulation and social differentiation (Grothe-Hammer and Berthod, 2016; Roth, Schwede, et al., 2019; Ward, 2003)?
- Trust WHO: Dis-/simulation, dissemination, and mis-/trust (Luhmann, 2013, p.13).
- The Great Reset: The role of simulations in “resetting our future state” (WEF, 2020).
- Simulation, speculation, and abduction: Truth and inference in the age of big data and the digital transformation of theories (Deacon et al., 2018; Kitchin, 2014; Roth et al., 2019a; 2019b).
- Simulation and gamification: How is learning organised in real-life simulation studies? What are tipping points when simulations feel or turn real?
- Prospects and limitations of the use of simulations for understanding, visioning, and forecasting the complex post-coronavirus world.
Manuscript submission is open from 01 October 2020 to 30 June 2021. Manuscripts must constitute original research and comply with the Futures author guidelines. In the online system please ensure you submit your paper within Manuscript Type: ‘Virtual Special Issue: Simulation and Dissimulation’. Once accepted, articles submitted to our virtual special issue are published in a regular issue of Futures. Simultaneously, each accepted manuscript is added to the virtual special issue, which is gradually built up as individual manuscripts are published online in Futures. The advantage of this procedure is that it speeds up the publication of individual articles.
The full CfP and further information are available on the Journal homepage: https://www.journals.elsevier.com/futures/call-for-papers/call-for-papers-simulation-and-dissimulation
Do not hesitate to contact me (firstname.lastname@example.org) for further question and informal enquiries!