A Human-Centered Approach to Artificial Intelligence Applications in Naval Aviation

Open Access
Article
Conference Proceedings
Authors: Mitchell TindallBeth AtkinsonJordan SandersSarah BeadleJames Pharmer

Abstract: The doubling of artificial intelligence (AI) performance every six months (Sevilla et al., 2022) during the last decade necessitates that the application of these capabilities in high stakes settings not be done arbitrarily. Defining a structured, human-centered process increases the likelihood that the application of AI is done safely, effectively, and efficiently. Such a process, which considers both AI and automation, should start by identifying clear definitions to guide categorization of capabilities. A recent literature review identified 28 definitions for AI (Collins et al., 2021), to include AI being “…the ability of a machine to perform cognitive functions…problem solving, [and] decision-making.” Due to their complexity, investments in developing models can reach the millions (Maslej et al., 2023). Alternatively, automation can be defined as “…something which runs itself with little to no human interaction…” and guided by specific rules (GeeksforGeeks, 2022). Unique to AI is the ability to learn and evolve (GeeksforGeeks, 2022). With these definitions, the next step should focus on a comprehensive review of targeted domain tasks. This would include understanding the associated knowledge, skills, and abilities (KSAs), as well as the tasks’ criticality, frequency, and difficulty. Such information is generally a product of (cognitive) task analysis and/or front end analysis and is valuable when building criteria for the appropriateness of AI/automation. A recommended next step should include reengagement with experienced end-users, which is imperative for ensuring a comprehensive understanding of tasks and for yielding valuable insight into AI applications. This poster will provide an overview of the steps undertaken for initial consideration of AI and automation within a Navy domain, to include exclusion criteria and lessons learned with regard to applying this process. Finally, results will include estimated applicability of AI/automation technologies as related to current tasking in relevant aviation platforms.

Keywords: Artificial Intelligence – Naval Aviation – Human-Centered

DOI: 10.54941/ahfe1004216

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