Conflict simulation, peacebuilding, and development

Daily Archives: 25/05/2011

Federal Virtual Worlds Challenge 2011 winners

Well, we’re a month late in reporting it, but better late than never: the winners of the 2011 Federal Virtual Worlds Challenge have been announced. Of particular interest to PAXsims readers will be NonKin Village, the winner in the “patterns of life” category:

Non-Kinetic (NonKin) Village provides training developers with a small autonomous society (like The Sims or SimCity) that is reconfigurable for a number of cross-cultural training goals. Nothing is scripted, it is all based on social science models of the society of interest. Once the models are setup, trainees can use it like the mock villages at US military forts to gain experience in foreign cultures and to learn to be sensitive to local norms, values, relationship building, and stakeholder issues prior to arriving in the country or region where they must interact with and possibly influence and assist natives in that culture. This is useful for many types of training such as, but not limited to, multinational corporations tutoring their workers, international aid organizations training their field representatives, and diplomatic advisors and military forces needing to learn how to handle counter-insurgency, stabilization and development issues.

Many specific types of training can be written with the Agents in NonKin Village. The current NonKin release holds two demo games aimed at military player(s) and at helping them to learn how to profile and befriend the population, and to begin to help stabilize their society. NonKin presents the player(s) with an artificial society that has a declining economy (formal and black market), a corrupt governance and leadership structure (clan as well as various would-be governmental groups and institutions), potential insurgents amidst families carrying out daily lives, and residents whose trust you can earn. The two demos, respectively, challenge trainees to (1) identify trends affecting the main economic activities, organizations, and networks of the village; and (2) build up relations and become familiar to the villagers in order to learn their social, kinship and political networks well enough to find and detain an insurgent. These are not completed training games, but are meant to be illustrative of what can be created with NonKin Village.

The FVWC site isn’t terribly informative, and there’s no announcement that I can find on RDECOM’s Army Technology Live website. Ironic, that.

However there is a great deal of information available on NonKin Village via the Ackoff Collaboratory for Advancement of the Systems Approach at the University of Pennsylvania, which developed the project. For those of you with Virtual Battlespace 2, you can even download the VBS2 plug-ins and mission files and give it a try yourself.

After the recent NDU Roundtable on Strategic Gaming a few of us had an interesting side discussion over whether avatar-centered videogames work well for cultural awareness training, or whether they might have some potential negative effects too. Certainly they allow users to potentially immerse themselves in a virtual world and learn from their simulated mistakes in a way that has no adverse real-world consequences. On the other hand, might there be a sort of reverse uncanny valley effect at work too, such that real foreigners seem so like the machine ones that trainees start to treat them as if they were programmed AI agents rather than complex human beings whose motivations both overlap with and differ from our own? Does interaction with a machine actually heighten empathy, or alter it?

This isn’t really an issue for the developers on NonKin to address—they’re much more in the business of pushing the technological envelope. However, I do think the answer is far from clear, and deserves some systematic study (if it hasn’t already been done). It is probably also an issue to be addressed in debriefs from virtual cultural awareness training, much as with any other simulation method: what are the good lessons to learn, and what might be the wrong ones (arising from limitations in the model or simulation process)?

%d bloggers like this: