TACTIACL AI: NOT A CASTLE IN THE SKY


connectivity—including low-bandwidth transmission, the need for applications to operate with variable levels of processing power, and being able to hold data and prioritize transmission when connectiv- ity is available. We’re unlikely to find a single solution to meet our needs as well as operate under our constraints; if we do, it will likely be unaffordable. To solve this problem, PEO C3T has begun a brand- new pathfinder project to tackle identified gaps like infrastructure and data availabil- ity. Te aim is to build a foundation for enabling AI across our portfolio in blocks of capability.


UNMAGICAL REALITY There’s a running joke that artificial intelligence (AI) works like magic. You take all of your problems—inconsistent or nonexistent data, or even an over- whelming amount of data, unpredictable circumstances, the advancing speed of threats—you stuff them into a cauldron, sprinkle in some AI and the potion turns to gold—and it tastes great, too! We know it works because we’ve seen the demon- strations—sanitized data, locked in a castlelike data center, surrounded by a moat of clear distinction.


Te reality is that there is no monolithic data castle and we need more than magic. Tactically, a castle is great for defending your home turf, but not such a great util- ity for an expeditionary force. In our rush to adopt AI, we defaulted to the acquisi- tion model we all know—identify explicit requirements for AI, pass them off to a systems contractor, field the result and start fresh with the next set of require- ments. We haven’t thought much about what’s different with AI, because we can’t afford the luxury of time when we’re in competition with nations less concerned about the ethics and implications of deploying this advanced technology.


QUANTUM LEAPS


Researchers from the U.S. Army Combat Capabilities Development Command’s (DEVCOM) Army Research Laboratory (ARL) and Tulane University combined machine learning with quantum information science to reconstruct the quantum state of an unknown system. (Photo courtesy of ARL)


In the early days of 2020, before the year was defined by the COVID-19 pandemic, PEO C3T convened the first of several AI-focused workshops to survey stakehold- ers—including requirements developers, testers, science and technology—to iden- tify potential use cases for AI, as well as what the roadblocks would be to deploy- ing AI in the field. Te results of that workshop, further refined over the ensu- ing months, demonstrated that there was a lot missing from the bigger picture— like access to operational data and a lack of common infrastructure—to make AI effective and sustainable.


OVERCOMING ROADBLOCKS Te way to best approach these AI road- blocks, PEO C3T determined, was engagement through an AI pathfinder project. Te project will spin out a series of AI-enabled capabilities that were care- fully selected to force the PEO and its partners to work through the barriers discovered during the workshops. For example, we’re developing applications that will be able to identify key informa- tion from an operational order and feed it automatically into a range of systems, but we’ve only been able to gain access to four examples of operational orders, and most


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Army AL&T Magazine


Spring 2021


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