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Applying Wargames To Real-World Policies

SCIENCE(2019)

Cited 12|Views4
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Abstract
In their Policy Forum “Next-generation wargames” (21 December 2018, p. [1362][1]), A. W. Reddie et al. explain that because the historical record does not include a large number of nuclear wars, scholars who wish to apply quantitative research methods to these events struggle with a dearth of data. To address this challenge, Reddie et al. constructed simplified games that can be repeated thousands of times. However, they seem to misunderstand the principal value of wargames in the policy field. Although observations of players who do not resemble actual decision-makers can produce statistically significant results, they are likely to be irrelevant to real-world policy decisions about escalation and nuclear use.![Figure][2] Wargame experiments explore the effects of potential wartime decisions.PHOTO: KAI KEISUKE/SHUTTERSTOCK.COMSimplification is central to good wargame design. In addition to making games playable, it abstracts extraneous detail in order to focus on understanding why the players made their choices. This is where the value of wargaming as a research method truly resides. Counting precisely how often one side wins or escalates is less important; if the answer is not “always” or “never,” it will not help decision-makers facing questions such as “Could this action lead to a nuclear war?”Reddie et al. rightly emphasize the playersu0027 role in illuminating important human factors but fail to recognize the value of human adjudication in gaming. Games driven by rigid rule sets or computer code cannot readily handle ingenuity or unexpected strategies and invariably limit playersu0027 potential decision sets. Reducing possible interactions or decisions to fit traditional statistical methods neuters a key strength of wargaming as a method: fostering and examining human creativity. As we seek to generate more and better data from wargames, it is essential that capturing this observational richness does not take second place to collecting data that are easily countable but ultimately insubstantial. [1]: http://www.sciencemag.org/content/362/6421/1362 [2]: pending:yes
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