Democratizing AI for DOD: Seizing a Competitive Advantage
The future of war is changing at an accelerating pace. Battles of the future will have less to do with Cold War-era equipment (planes, tanks, ships) and everything to do with data, information processing, and the efficient deployment of artificial intelligence. Next-gen warfare will be made possible by artificial intelligence, network-centric and fast at the speed of light. The stakes are not only high, they are huge. The winner will hold the upper hand with the advantage of the first come.
There is no doubt about the Chinese Communist Party’s ambitions to lead the world when it comes to AI. Xi Jinping said China will be theworld leader in AI by 2030, and he islead national policies insupport for this goal. Testifying recently before the Senate Armed Services Committee, Eric Schmidt, chairman of the National Security Commission on Artificial Intelligence, said he was convinced that China’s leadership in key technological areas is a national crisis that must be addressed directly, now. He told lawmakers that China could surpass the United States in AI over the next decade, and during his questioning Schmidt said he believes the United States may have one or two years ahead of China in some AI applications.
With the margins at their thinnest, the United States and its allies must do more to build an AI-capable workforce and transform the culture of defense departments to adopt AI. adoption of AI, I recommend a three-tier approach.
First, the Pentagon should take an automation-driven approach to data science, which has been taken across industries, including high-tech finance. With this approach, data scientists can leverage automation throughout the AI lifecycle to quickly test the feasibility of problem framing, generate a robust first result, and then enrich their expertise. Modern automated tools reduce the timeline of AI results from months or years to days or weeks. Models leveraging open source tools that provide explainability and reliability offer young data scientists a sure path to automation. The alternative, and the status quo, is for DOD to hire many more PhD-level data scientists to create all of the AI solutions. However, with a shortage of American STEM talent and the lure of high-tech AI startups, these federal data science jobs will remain vacant and the country will continue to fall behind.
Second, the DOD should take advantage of enterprise AI platforms that allow a wider range of staff (eg, software developers, research analysts) with just a few days of training to create solutions. of AI. Modern enterprise AI platforms take advantage of automation and provide a simple graphical user interface that enables people without extensive experience in machine learning techniques and software programming to build a suite of predictive algorithms. .
For example, a business analyst created a reliable AI solution to identify the factors that most predict the success of candidates for special forces training, helping both candidates and the military. The beauty of automated machine learning is that it increases productivity while allowing understaffed DOD data scientists to spend their time solving more complex problems, like developing next-gen AI to fight against cyber threats.
Third, the Ministry must implement an AI capacity building and culture change program that pervades all levels of the organization, from frontline troops to DOD leaders. Not everyone needs to be a data scientist, but everyone needs to know how and where AI can be deployed and how to leverage artificial intelligence to meet mission requirements.
For example, fighters must be trained to understand, integrate, and implement the versatile power of AI – the applications of which abound. In addition to placing the right personnel in the right training programs more effectively, AI can identify fighters and veterans at risk of suicide, identify patterns to predict cybersecurity attacks, and anticipate which tanks, trucks, or helicopters need. maintenance before blocking soldiers in the field. AI can also be used to more accurately forecast demand for fuel, ammunition, or other supplies.
There is no doubt that the United States needs to devote more resources to developing superior AI technology and training more data scientists. Failure to do so exposes the country to great technological, economic, military and even personal risks. As we develop these capabilities, it is critical that staff at all levels of DOD develop a deeper understanding of how, when and where to use AI.
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