While there have been some early adopters of Artificial Intelligence (AI) in the federal government, it is still an under-utilized technology when it comes to helping agencies deliver on the mission. Despite its futuristic-sounding name, we’re at the point where machines can process more information and detect more patterns than humans and the platforms and solutions that deliver this massive compute power are, in many cases, ready for primetime.
The idea of AI has been around since the mid-20th century; however, until recently, it’s all been more fiction than reality. Though many people might still think of Skynet and Terminator when they hear this phrase, there is plenty of good that can come from these Artificial Intelligence-based technologies.
“There is a huge chasm right now [between] the public dialogue and public reception about AI and what the opportunities are today for … agencies; what is achievable and what is already being done,” said Justin Herman, who heads up ETOC. Examples include everything from the Army’s use of AI to perform maintenance on its Stryker vehicles to the General Services Administration’s Emerging Citizen Technology Office (ETOC) that looks to integrate chatbots, personal assistants, and other tools to deliver citizen services and streamline internal processes.
So, what has changed in recent years to lead to not only the conversion from fiction into reality for AI, but more importantly its adoption by federal agencies, well known for their cautious adoption of cutting-edge technology?
Of course, it is data. It’s no secret that we’re creating more and more data each year. It’s estimated that in just two years, by 2020, we’ll produce 44 times the data we created in 2009. While much of that data is generated by personal devices and private sector organizations, federal agencies are not only able to tap into these data sources, but are also creators of an enormous amount of data themselves. The Department of Defense (DoD), for example, has a stockpile of data, much of which probably sits in storage environments and has never even been analyzed, let alone put to work for the benefit of national security.
But what good is this data if it cannot be retrieved from stored, managed, and applied in a cost-effective manner?
Without the advancements in compute capability and without the ability to store and manage the amount of data we are generating, AI would still be more potential than actuality. Instead, we’re at the zenith of AI’s hype cycle, according to Gartner’s Hype Cycle report, which will move it squarely into mainstream adoption in the next two years.
However, beyond the hype-cycle the other significant factor that determines technology adoption is timing. In the case of AI, which also encompasses Machine and Deep Learning – the timing issues pertain primarily to the amount of data and the ability to store, process, and then apply that data to critical problems that federal agencies address.
Based on this insight, federal agencies are well poised to enter push through the hype cycle and integrate AI’s tremendous power into mission-critical activities, if not now, then in the very near future. Agencies, like the DoD, should start investing now, leveraging their technology partners and the ETOC to ensure that they’re prepared for the AI revolution. The key challenge lies not in finding an application – though mission-focused problem solving will be most fertile – but in ensuring that they have a robust and future-proof data management infrastructure in place.
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