Private businesses already use AI to find efficiencies in their own business and improve the return-on-investment of products and projects.
At the risk of dating myself, one of my favorite movies growing up as a kid was “WarGames” starring Matthew Broderick. I didn’t realize it at the time, but in the climactic scene, the large supercomputer ‘WOPR’ operated by the Defense Department, showed artificial intelligence capabilities. By playing tic-tac-toe against itself, it learned a lesson that prevented global thermonuclear war.
In many ways, Hollywood has warped what many think of when they first hear the term artificial intelligence, or AI. My thoughts used to go to movies like “The Terminator” or “The Matrix” where sentient machines develop the ability to think for themselves and try to overthrow humankind. While this makes for an exciting movie plot, AI has much more tangible—and less threatening—benefits, particularly for government.
In 2018, U.S. Chief Information Officer Suzette Kent announced the creation of the first Federal Data Strategy that will serve as a foundation for how agencies use AI.
Her analogy in describing the need for the strategy was compelling.
“Technology modernization allows us the opportunity to rethink our foundation,” Kent saidat an event announcing the strategy. “We have to move aggressively. We don’t want to build the high-speed train without the track.”
AI can serve as part of that track. As the government collects more and more data, the need for solutions to drive true value from that data grows in importance. AI, in conjunction with big data and analytics, can deliver that baseline value and go beyond traditional solutions to find deeper insights.
Other governments have recognized this as well. For example, the United Arab Emirates was the first nation to appoint a senior cabinet official solely focused on AI empowerment and oversight within the government, appointing a Minister of State for Artificial Intelligencein October 2017. Canada was the first nation to release a national AI strategy. And China has released a 3-year plan to be a leader … if not the leader … in AI.
So, for those of us whose understanding of AI has heretofore been solely that of the Hollywood blockbuster, AI is the science of training systems to emulate specific human tasks through learning and automation. In short, it’s a technology that makes it possible for machines to learn from experience, adjust to new inputs and perform specific human tasks, such as pattern recognition, finding anomalies in data, image and video analytics, and more. Specific to analytics, AI can help analytics programs in government find connections and trends in the data that human analysts might miss due to scale, complexity, or other factors … and it can do it at a much faster speed. AI can find context in data, gaining insight from previous discoveries to create better outcomes in the future. From an analytics perspective, AI tends to focus in these areas:
- Machine learning: Machine learning and deep learning find insights hidden in data without explicitly being told where to look or what to conclude. This results in better, faster and more accurate decision-making capabilities.
- Natural Language Processing: NLP enables understanding, interaction and communication between humans and machines, automatically extracting insights and emerging trends from large amounts of structured and unstructured content.
- Computer vision: Computer vision analyzes and interprets what’s in an image or video through image processing, image recognition and object detection.
- Forecasting and optimization: Forecasting helps predict future outcomes, while optimization delivers the best results given resource constraints. This includes enabling large-scale automation for predicting outcomes and optimizing decisions.