Before the Department of Defense can even begin leveraging artificial intelligence at scale, it needs access to the data.
But obstacles ranging from political constraints, organizational silos, technical challenges, acquisition pathways, and lack of understanding and trust continue to hinder effective implementation of the emerging technology across the department.
The DoD Chief Digital and AI Office wants to “popularize” data models and establish common practices for organizing and structuring data.
“I hesitate to talk about standards because they seem a little draconian or a little imposed. But we want to use good models so people know what it means to share data,” Bill Streilein, CDAO’s chief technology officer, said Monday at the DON IT West conference.
To respond to the lack of confidence in artificial intelligence, the CDAO published its Responsible Artificial Intelligence (RAI) Toolkit to ensure that AI applications comply with ethical standards. The CDAO RAI team plans to add more features to the toolkit, including an acquisition toolkit with standardized contract language and RAI project management tools.
CDAO also invests in educational programs to improve understanding of AI at all levels of the department.
Streilein said the department just launched executive-level courses at Johns Hopkins University, the Naval Postgraduate School and the Massachusetts Institute of Technology. These three-to-four-day courses provide executive-level professionals with a better understanding of the implications of integrating data analytics and artificial intelligence into daily operations. The CDAO also plans to develop courses at other levels.
The DoD is also offering 11 new positions that “recognize the value and power” of people with expertise in data analytics and AI.
“People can maintain these skills throughout a career in ministry, perhaps moving in and out of industry to pass on lessons learned within ministry and industry to have an effect,” Streilein said.
The DoD recently released its data, analytics and AI adoption strategy. It builds on previous DoD data and AI strategies and addresses recent industry advancements in federated environments, decentralized data management, and generative AI.
Streilein said AI experimentation is at the heart of the strategy, promoting an approach of exploring and testing AI technologies rather than expecting them to be perfect and immediately deployable.
“One of the key words of our strategy is to experiment with AI. We shouldn’t expect this technology to be ready for use as a toaster. This is something we need to integrate, experience, try and learn,” Streilein said.
“The main idea is to constantly experiment and deploy, but this is done with user feedback. It’s not that we’re going to throw the capabilities over the wall, and users just need to understand how to use them. We want this feedback because it will help us understand what needs to change next time.
CDAO wants DoD to adopt a product-oriented approach. He wants the ministry to treat data as a product rather than a strategic asset.
“Product orientation changes our mindset from seeing things like data as strategic assets, which tend to be hoarded if we think about what an asset is, to a product, which is something that someone uses,” Streilein said.
“So if someone has a data product, the value is realized because there is a customer. Our goal is to empower every CTO and CIO in the department with the skills and tools to become a product manager so they can deliver what they promised to their customers.
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