REDSTONE ARSENAL, Ala. — Artificial intelligence is the new buzzword, and it’s everywhere. Some use it, others fear it. No longer confined to the tech world, AI has in recent years crept into everyday life, including in U.S. air force and missile command.
To help employees better understand topics such as machine learning, data visualization and data cleaning, AMCOM’s Business Transformation Office hosted the second annual Data Analytics Day on September 10, 2024, at the Sparkman Center at Redstone Arsenal.
Lisa Hirschler, AMCOM’s director of data and analytics, said the goal of the event was to open employees’ minds to the different ways data analytics can be applied daily across the command.
AMCOM Commander Maj. Gen. Lori Robinson told the more than 200 attendees that technology is changing rapidly and will continue to change rapidly, so it is critical to embrace it, understand it and learn how to apply it to the work they do every day.
“When I think about data analysis from my perspective, I think about decision making,” Robinson said. “This topic is important. It’s important to AMCOM and it’s important to the Army.”
Robinson said events like Data Analytics Day are essential for employees to learn about the tools and products available and how those tools can be used at AMCOM. She added that while technology is great, the human element can’t be removed. She said it’s important to use the machine to do the things it does best and use the human to do the things the human does best: cognitive thinking and decision making.
AMCOM Chief of Staff John Morris echoed Robinson on the importance of data-driven decisions and said the workforce needs to reduce its reliance on personal experience.
“We have access to huge data sets, and some of that data probably isn’t helping us as much as it should,” he said.
Morris asked attendees to focus on using data to help the command be more effective in today’s resource-constrained environment, either by finding ways to conduct business more cost-effectively or doing more with available resources.
“By focusing on how we can do more with what we already have, we should be more efficient, and data can help us do that if we look at it properly,” he said.
The Department of Defense has issued an update AI Strategy In 2023, the U.S. Department of Defense focused its strategic efforts on several interdependent objectives that support the DoD’s hierarchy of AI needs, a pyramid with quality data at the foundation and responsible AI at the top. The key, Hirschler says, is accountability.
“We can do a lot with AI,” she said. “But I want to talk about the base of the pyramid, which is good data, because you can’t do anything without a good base. That’s what will be our priority for 2025.”
Data quality continued to be a recurring theme throughout each presentation. Chief Data Officer John Keck spoke to the audience about machine learning, which requires quality data to reveal patterns. Keck described machine learning as a branch of AI.
“It allows systems to learn from data,” he said. “It’s a very large statistical algorithm that combines functional logic with deep data and reveals patterns.”
Without context, the topic of machine learning can seem complex. Yet Keck told the crowd that they use it every day. Facial recognition to open a smartphone, targeted ads on social media, and voice assistants that provide facts and information are all examples of machine learning. Each is designed to gather information, look for patterns, and in some cases, take action.
“Machine learning increases the availability of data,” Keck said. “You have a ton of data, but that doesn’t necessarily mean it’s available to derive insights from. It’s just a lot of data. Sorting through that data and creating categories to take action is difficult when you have big data, but it’s very useful if you know what you’re doing.”
For AMCOM, machine learning can be used to predict maintenance issues. The machine will learn histories and patterns based on aircraft data from sample sets, and then make predictions based on that data. Supply chains are another way machine learning can improve efficiency. If a logistician needs to know why a part didn’t arrive on time, variables and patterns will determine what happened and how to prevent it from happening again. The foundation is data quality. With multiple samples and data input, the machine will continue to learn and identify patterns.
“You keep processing the same data, and that same clean data keeps giving you more and more accurate information. That’s why you need repeatable processes with standard applications,” Keck said.
The Data Analytics Center is now part of AMCOM’s Business Transformation Office, which was created earlier this year. Its role is to enable AMCOM to adapt and thrive in the digital age through the integration of digital solutions, business processes and data analytics. Hirschler said this will improve decision-making capability at all levels by providing leaders with data as a strategic asset to stay ahead of enemy threats.
See photos from Data Analysis Day on AMCOM Official Flickr Page.