These DARPA simulators could predict a war before it starts
DARPA, BAE Systems, and the Air Force Research Lab are working to pioneer new computer simulations, algorithms, and advanced software to provide military decision makers with organized, near real-time information on causes of war and conflict in operational scenarios.
Drawing upon a range of otherwise disconnected sources of raw data, the new software program is designed to use reasoning algorithms and simulations to analyze intelligence reports, academic theories, environmental factors, and details from operational scenarios and other kinds of user input.
"It is about taking information from disparate sources which would be impossible for a person to consume in a short amount of time," Jonathan Goldstein, Senior Principal Scientist, Autonomy Controls and Estimation, BAE Systems, told Warrior Maven in an interview.
The Air Force Research Laboratory recently awarded a $4.2 million deal to BAE Systems to develop CONTEXT; DARPA is sponsoring BAE's efforts.
The emerging product, called Causal Exploration of Complex Operational Environments (CONTEXT) models different political, territorial, and economic tensions that often cause conflict. These nodes, or variables making up a complex, yet interwoven tapestry of causes, include things like economic tensions, terrorism, tribal or religious conflict and issues about resources or territorial disputes — among other things.
"The technology evaluates causal insertions in different forms and innovates them into a model of interwoven causal relationships present in otherwise disconnected sources. We are building a model that can rapidly be used by an expert, so that when a new conflict flares up, decision-makers can understand the underlying issues," Goldstein said.
While on the surface, organizing and performing some analytics of large pools of data might bring AI to mind, CONTEXT evaluates material input by users and does not necessarily access massive volumes of historical or stored data. Nonetheless, it does appear to perform some measure of automation and AI like functions, in so far as it organizes and integrates different sources for a human decision maker.
"This shortens the decision cycle. People are not good at maintaining a causal model with complexity in their head. The software creates a large graph of causes, evaluates approaches and examines the potential consequences of a given approach," Goldstein explained.
Automation and AI, which are of course progressing at near lighting speed these days, are often described in terms of easing the "cognitive burden," meaning they can quickly perform analytics and a range of procedural functions to present to a human operating in a command control capacity.
At the same time, causes of conflict are often a complex byproduct of a range of more subjectively determined variables – impacted by concepts, personalities, individual psychology, historical nuances, and larger sociological phenomena. This naturally raises the question as to how much even the most advanced computer programs could account for these and other somewhat less "tangible" factors.
Leading AI and cybersecurity experts often say that advanced computer algorithms can analyze data and quickly perform procedural functions far more quickly than human cognition – yet there are nonetheless still many things which are known to be unique to human cognition. Humans solve problems, interpret emotions and at times respond to certain variables in a way that the best computer technology cannot.
"War causation is always over determined. Even with advanced statistical regressions on extremely large data sets, it is unlikely that what causes conflict can be determined with accuracy," Ross Rustici, Senior Director, Intelligence Services, Cybereason – and former DoD Cyber Lead Intrusion Analyst and Technical Lead for DoD, East Asia, told Warrior Maven.
At the same time, despite natural limitations, using software and simulation to analyze data in this fashion is of course by no means useless, Rustici added.
Calling CONTEXT a "step in the right direction," Rustici said "any effort to update war prosecution and war cessation planning will go a long way towards updating a military that has learned hard lessons in counterterrorism and regime building. Gaining a finer understanding of how populations and defeated military groups will respond to tactics for winning the war and securing the peace is something that is long overdue."
Rustici further elaborated that human understanding of some elements of causality can without question have a beneficial impact in many respects. However, there are of course substantial limitations, and few would disagree that there are many concepts, feelings, variables and subjective factors informing causality — underscoring the widespread recognition that, despite the pace of technological computer advances, there are still many things which machines cannot do.
"This program is unlikely to have a significant impact beyond understanding how to conduct further modelling in the future," Rustici said.
This article originally appeared on Warrior Maven. Follow @warriormaven1 on Twitter.