FIVE STEPS TO SERENITY
STEP I: DATA Become diligent about data collection and begin training AI tools against currently available data.
As summarized in the book “Predic- tion Machines,” by Ajay Agrawal, Joshua Gans and Avi Goldfarb, AI is “prediction technology” where prediction is the process of filling in missing information—prediction takes information you have, often called “data,” and uses it to gener- ate information you do not have.
Te first step to integrating AI in the Army is to apply AI toward current data sets. Data is the key—the best algorithm will fail if the data is inconsistent or sparse. RAND found that the advances in AI “are predicated on the availability of large, labeled data sets and significant comput- ing power to train the algorithms.” Te Army sustainment enterprise is ahead in DOD’s and the Army’s integration of AI because of data available in GCSS-Army, which, according to Northrop Grumman,
is the largest enterprise resource planning system ever successfully attempted within DOD. As a result, the Army has large, labeled data sets in GCSS-Army for main- tenance, materiel management and supply.
Te Army needs to develop algorithms to train against this data and apply AI to provide predictions on future maintenance and supply status from the tactical to the strategic level. Te Army needs to begin training the algorithms to provide predic- tive analysis to commanders now. Te benefit of this is to enable commanders to assess the usefulness of these predic- tions and forecasts in making decisions, further improving the application of AI. Tis offers a source of data for training, verification and testing to hone algo- rithms and to produce models of predicted future outcomes. Te Army could use the National Training Center at Fort Irwin, California, and the Joint Readiness Train- ing Center at Fort Polk, Louisiana, as initial hubs for training and validating algorithms on the existing data. Personnel would see the real-time status of logis- tics assets and commanders could make
decisions informed by predictive analysis from that data. As data is collected and decisions made from that data, the algo- rithms would become more accurate and the predictions more precise. Te number of Army units that rotate through these centers, the controlled environment and sophisticated data collection tools already in existence make these prime environ- ments for testing early AI integration on existing data.
STEP 2: COLLECTION Improve and expand data collection efforts to integrate the tracking of ammunition, fuel and transportation.
While the data in GCSS-Army establishes a great base for applying AI tools, the Army requires improvements and expansion to data fed into that database. Te Army is leaning forward in this endeavor through expanding GCSS-Army. In a 2017 article in Army Sustainment magazine, “GCSS- Army: Providing big data for readiness,” the commander of the Combined Arms Support Command, Maj. Gen. Rodney D. Fogg, discussed a future addition to
DATA PAVES THE WAY
Data is the key to integrating AI into the Army—the best algorithm will fail if the data is incomplete in any way. (Image by Getty Images/SolStock)
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Army AL&T Magazine Winter 2021
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