The Study of Future War and the Future Study of War, March 16-18, 2001

Workshop Themes

1. Old Wars, New Wars.
   More and more frequently, conflict analysts (e.g., K. J. Holsti, Mary Kaldor, Anatol Lieven) and others opine that the nature of international war has fundamentally changed in the post-Cold War world and that much of the knowledge we have gained from studying past wars is irrelevant. It is alleged that the goals and issues of war have shifted from power politics concerns to ethno-cultural matters and that the ways in which wars are fought have changed dramatically. Instead of traditional confrontations between “official” military forces, international conflict increasingly involves terrorists, paramilitary forces, self-defense units, private armies, and other such non-state groups. Hence, say the critics, interstate wars are a thing of the past; future wars will be essentially internal wars (albeit with serious international implications due to spillover possibilities) that are fundamentally different from traditional interstate conflicts. In view of these and other assertions about the changed nature of war it seems wise to take this occasion to consider how much and it what ways we need to adjust our conceptualization of war.
   
2. Old Methods, New Methods.
   It has also been argued that the methods (i.e., measures, models, and techniques) that we conventionally use are out of date. Our measures of conflict and war may be too state-centric and not be as valid as they once were, given the alleged nature of the post-Cold War period. Similarly, our usual measures of those factors that we believe are related to conflict and war (e.g., power) may be substantially less valid in the 21st century. The models that we have tested can certainly be criticized as being too heavily influenced by the “Realist” perspective, in which power, alignment, and geographical factors play a prominent role. The findings concerning the “democratic peace” suggest strongly that we need to expand our models to encompass other international (e.g., economic and cultural) and domestic factors. And finally, some believe that a revolution in statistical methods is underway, of which we are insufficiently aware. This revolution promises to allow us to move beyond the simple, static, linear models that we conventionally use to more complex, dynamic, non-linear models that better represent reality.

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