THE CALCULUS OF CAUTION


Tis process is cumbersome but required to maintain control. Te key to maximizing value though, is to use the fewest mitigations to get to a reasonable level of risk. Tat’s where an AI-specific risk framework comes into play.


AI LAYERED DEFENSE FRAMEWORK As part of the AI Implementation Plan for Assistant Secretary of the Army Acquisition, Logistics and Technology (ASA(ALT)), announced in March 2024, Deputy Assistant Secretary of the Army (Data, Engineering and Software) is building the AI Layered Defense Framework. Te intent of the framework is to give program managers a toolkit to self-assess for AI-specific risks and be informed on relevant mitigations available to them. All AI capabilities would undergo the most basic mitigations (Layer 1) while more critical systems would get additional layers.


Tere are three layers of risk in which all AI capabilities fall:


Layer 1—AI tools that have broad value, and if compro- mised have limited potential for harm or hindrance of Army’s objectives. Te maximum benefit is achieved with the fewest controls. Using a navigation system to find lunch would fall in this category. We don’t need to invest a large amount in mitigations here.


Layer 2—AI software that offers strategic value to a more limited number of users. Tis layer will have more significant mitigation strategies to balance value and security. Key risks will be mitigated.


Layer 3—AI models that provide high value and cannot be compromised. Layer 3 will employ state-of-the-art defenses for the most valuable or critical capabilities.


Te AI Layered Defense Framework aims to incrementally increase security measures from an open, accessible strategy to a highly secure approach with stringent controls, tailored to the unique sensitivity and importance of Army data and systems. Te AI Layered Defense framework will serve as a thorough theoretical and practical framework for mitigating adversarial risks to our systems and warfighters. Here, risk is being broadly defined as the possibility that the occurrence of an event, related to AI systems, will adversely affect the achievement of the Army’s objectives. It’s a general statement which reflects the multitude of challenges the Army faces every day and the idea that many mission objectives must be achieved even if there are dangers. Te risk is not the potential of harm or injury, those have to be tolerated at some level; the risk is failing to achieve an objective.


12 Army AL&T Magazine Fall 2024


To maintain dominance in the battlefield of tomorrow, the U.S. needs to continue to lead in developing systems on the bleeding edge of technology. This means development and inclusion of AI capabilities.


While AI systems face the traditional cybersecurity risks asso- ciated with all computer systems, the AI Layered Defense Framework is concerned with building a comprehensive library of risks and mitigations unique to or inherent in AI systems: risk associated with the data used to train the system, the system itself,


MAKE CHANGE


Scaling and maturing artificial intelligence/machine learning is one of seven focus areas prioritized by ASA(ALT) in an effort to Disrupt the Status Quo through digital transformation. (Image courtesy of DASA(DES))


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