Don’t Neglect the Easy Wins for Military AI

By Christian Heller

The defense community is captivated with artificial intelligence (AI) and its possible impacts on warfare. There has been much debate on AI’s impact on offensive and defensive operations, nuclear command and control, and information warfare. AI experts worry about the dangers of ultrafast AI decision-making, the U.S.-China AI arms race, the level of autonomy granted to robots, and the overall threat to humans with increased AI independence.

The Department of the Navy (DoN) has responded with building organizations to help integrate AI into the military services. Most prolific of these groups are the Algorithmic Warfare Cross-Functional Team (also known as Project Maven) and the Joint Artificial Intelligence Center (JAIC). Project Maven’s efforts focus on using AI to support the processing, exploitation, and dissemination (PED) of video and imagery intelligence. These efforts also include using AI to exploit captured enemy material (CEM), acoustic intelligence (ACINT), and publicly available information (PAI, also known as Open-Source Intelligence, or OSINT). The JAIC’s first two initiatives were predictive maintenance and humanitarian assistance/disaster relief. Later last year, they expanded to include cyberspace and robotic process automation.

While these lines of effort are important, they pursue difficult, hard-to-achieve tactical goals while ignoring the easy, low-hanging-fruits of AI implementation within the bureaucracy. Self-targeting drones, deep fakes, and global integrated predictive analytics platforms are worthwhile, but the Navy can achieve better and faster returns on its investments by pursuing unglamorous AI efforts in the fields of manpower and administration. With a renewed willingness to rebuild the services to face the threats of the future, now is the ideal team to embrace AI.

Manpower

Existing uses of AI in the private sector can be implemented by the DoN to support recruiting, training, retention, promotions, and billet assignments. Numerous companies are using AI to help their hiring managers identify and recruit employees. Recruiting commands could adopt these services to reduce their personnel burden and increase their effectiveness. Montage combines AI, process automation, and analytics to personalize the recruitment process toward specific candidates. Textio helps recruiters choose the right words and language to attract the right people. Firms like Koru use predictive AI to better match candidates to available positions and could change the way the services assign personnel to specialties and units.

Many companies have already implemented cost-saving AI measures such as these. Google worked with American Eagle to customize their marketing to individual consumers, similar to how the services could customize efforts for individual recruits and better manpower management. Amazon, Starbucks, and Nike all use AI to personalize customer engagement and marketing. LinkedIn uses AI for its LinkedIn Recruiter platform to identify the best candidates for hiring managers, and Home Depot and Dyson use AI programs to identify candidates based on their internal databases, social media, and public job boards.

The lack of continuity of knowledge is endemic to the DoN where service members continuously change billets and commands. Turnover is high and leads to a severe lack of institutional knowledge. This turnover means the time-cost of retraining a replacement detracts from time spent advancing a project forward. AI training systems can help. IBM has partnered with firms to help departing employees document their knowledge for future workers. AI then indexes and sorts the information to make it more easily available, and successful efforts have already reduced the search times for previous knowledge by 75 percent.

The Navy and DARPA already proved the relevance of AI to training service members. A combined project in which a digital AI tutor led new sailors though their training saw AI-trained students “frequently outperform Navy experts with 7-10 years of experience.” AI startups like Bakpax aid teachers with their grading to identify specific personal needs for students and speed up the corrective process. A study by Johns Hopkins University found that students using Knewton, one of the original AI education startups which personalizes learning plans and materials for students, performed better compared to peers. Improvements in training may not seem like a critical requirement for the services, but training and development is viewed as the primary job benefit by millennials in choosing their employer.

AI also can help reform promotion processes with are plagued with inefficiency. Analytics firms like Palatine are helping leaders make better personnel decisions to identify strengths, weaknesses, and future potential. Well-meaning efforts within the Navy and Army are attempting to combat this issues, but AI can help eliminate recurrent human problems like bias from hiring and advancement.

Companies like Adecco are already able to prescreen candidates based on skillsets, geographic preferences, experiences, and availability to open locations. Its scale is massive: AI manages their timesheets, payroll, and work prioritization for its 700,000 workers and recruiters. A similar process could be applied to initial training and follow-on unit assignments to better meet the needs of commands and services while still satisfying the lifestyle demands of individuals and families.

Retention is a problem in both the government and the private sector, but AI solutions exist which can help. This increased level of human resources personalization towards recruiting, training, and billet assignments could drastically improve morale within the services and help retain talent for the DoN. Dissatisfaction with supervisors and a lack of appreciation are two of the main reasons employees quit, and AI and sentiment analysis can help manage those effects. AI management tools also help manage workloads and burnout, which, in a military environment, could prevent catastrophes.

Administration

The routine tasks of administration with the DoN and services can be significantly augmented by existing AI services. Document preparation, completion, and handling; payment and voucher processing; policy and guidance administration; and archival storage and retrieval are all carried out by AI at varying levels within the private sector. A Harvard Business Review study found that the majority of AI projects implemented by businesses involve automating back-office tasks. These tasks include updating personnel files from e-mails and call centers, as well as extracting and updating records between multiple systems. These examples found that process-automation is the cheapest and easiest of AI technologies to implement. Administrative programs can significantly reduce the time required for manually processing high numbers of different paperwork with inaccuracies or inconsistencies, and other government agencies like NASA have already adopted these practices in some departments.

Paperwork and process automation is well-established. For instance, the consulting and accounting firm Deloitte has automated thousands of forms and saved thousands more hours of labor for its clients in the financial sector. The accounting firm KPMG partnered with IBM and Watson to learn from 10,000 documents and help its tax advisors better serve their clients. Google’s Vision OCR detects text, character, and images in documents of various file types to extract, organize, and process the relevant information. Amazon’s Textract claims to go further by creating “smart search indexes” and automated workflows for processing documents through various departments.

Today’s tech leaders – Google, Amazon, Apple, and Microsoft – each have their own AI-powered assistants which businesses can implement to streamline management and coordination. Routine work like task management, calendar management, and emails and communication can be augmented by these tools.  Businesses can also use these tools to manage facilities and systems. These same tools can be used to engage leaders and commands with their service members using 24/7 assistance. Major companies like General Electric have adopted these tools, and IBM’s Watson Assistant has led to 40 percent reductions in time spent on administrative tasks.

Transitioning these types of workloads to, or augmenting them with, AI services can reduce the time burden currently placed upon staff officers and administrative specialists. In addition to large companies like Google and Amazon, start-ups like x.ai, Voicea, and Sigrid all perform a variety of tasks like coordinating calendars and meeting schedules, setting up conference calls, managing receipts and travel processes, scheduling transportation, and scanning and saving relevant files. Communications platforms like Zoom already auto-transcribe meetings and then publish the results as text-files for easy searches.

One key way AI is changing administrative work is aiding companies in their legal and regulatory compliance. With overlapping, always changing, and sometimes contradictory sets of policies and guidance, the DoN and the services could benefit from AI tools to assist leaders at both the senior and junior levels with policy adherence. AI has allowed insurance firms, one of the most highly-regulated and complex industries in the world, to analyze documents and process claims 25 percent faster.

Savings and Possibilities

Despite the difficulties which government agencies often have when implementing new technologies, examples of effective AI adoption already exist in some areas: the review and validation of 50,000 PDF records for a federal healthcare agency, state governments achieving 100 percent compliance for land lease payments and management, and state health insurance marketplaces responding to over 1,500 customers per day. In the United Kingdom, both the Ministry of Justice and the Department for Transport have implemented AI tools to provide better services to their citizens.

Adopting AI services to aid in manpower and administrative functions will pay for themselves with an outsized return-on-investment, and free up manpower and time which the services can redirect to other specialized needs. Even a small reduction in cost can provide substantial returns. For example, a 1 percent savings in the recruiting and training budgets for the Army ($5.1 billion), Navy ($2.1 billion), and Air Force ($2.4 billion) would result in $96 million in savings. A 1 percent savings in the services’ combined administrative budgets would result in over $200 million saved. Manpower can also be reduced in these respective areas to free personnel numbers for different MOS’s or operations. For example, decreases in administrative, training, and departmental management manpower for the Army (195,500), Navy (103,800), Marine Corps (56,100), and Air Force (125,100) could allocate thousands of billets for other duties.

Conclusion

These savings and efficiency measures are even more important considering the DoN’s increased emphasis on re-allocating funding toward research and innovation. AI support for tactical military purposes certainly deserves its own attention and prioritization, but the services and their leadership must not be quick to reject the immediate benefits to be gained by AI-services in the routine and familiar worlds of manpower and administration. These implementations can provide the highest near-term benefit and make additional funds and resources available for tactical AI research or other battlefield capabilities.

Christian Heller is a graduate of the U.S. Naval Academy and the University of Oxford. He currently works as an officer in the U.S. Marine Corps, and can be followed on Twitter @hellerch.

Featured Image: Server room of BalticServers (Wikimedia Commons)

One thought on “Don’t Neglect the Easy Wins for Military AI”

  1. Are the benefits of AI for military training hyped? Despite the apparent success of digital tutor, navy has not been able to progress in that direction – because the experiment was very specific to AI in IT, and it took nearly a decade of intense interaction with the industry, academia and navy to make it happen. Is such funding and more important metrics to assess efficacy available for aspects of military training?

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