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Mutually beneficial decision making in Human-AI teams: Understanding soldier’s perception and expectations from AI teammates in human-AI teams

Military decision-making, a complex process entailing multiple domains (Bosch et al., 2018), may involve routine as well as unprecedented situations requiring quick responses. The current decision-making process in military operations involves the decision-maker and their team collecting information during various phases of a mission, analyzing, and synthesizing it to determine the most suitable courses of action, and then considering their consequences (Olinover & Geva, 2021). Thus, this complex decision-making process may demand higher than normal attentional resources. However, humans are limited in their information processing ability as their capability to make decisions involves a complex interplay of such factors as perceptions, past experiences, severity, emotions, thoughts, and intellectual capacity (Harari, 2016), all of which may negatively affect the situational awareness of military professionals making decisions, thus endangering their and their teammates’ lives. Human decision-making is prone to overconfidence bias, the overestimation of one’s knowledge of their surroundings, the illusion of uncertainty, the inability to estimate the dynamic nature of different situations and surroundings (Kahneman, 2011). Taking action based on incomplete or inaccurate knowledge in high-risk dynamic environments leads people to take risks that they would have not if they had a better understanding of the consequences of their actions (Kahneman, 2011; Bosch et al., 2018). Currently, artificial intelligence (AI) is increasingly being used to assist humans in making decisions in high-stakes situations (Zhang et al., 2020). The steady advancement in technology, increased computing power, and the availability of large data streams for algorithm training has accelerated the development of smarter AI technologies (Ezer et al., 2019). Combining human and AI strengths can reduce human workload, improve situational awareness, scale military forces, reduce casualties, improve system resilience, and facilitate effective decision-making in combat scenarios. Human-agent teams (HATs) can be defined as a collaboration of one or more intelligent autonomous agents and human counterparts, each working as a full-fledged member of a team towards a common goal (O’Neill et al., 2020; McNeese et al., 2018; McNeese et al., 2021). Military missions are primarily staged during regional conflicts, which, by definition, involve the “deep uncertainty” (Jong, Daalen, & Dekkers, 2014) associated with the strategies, capabilities, and intentions of the parties involved as well dynamic setups and unexpected threats (Paparone & Reed, 2011; Bosch et al., 2018). Numerous variables such as enemy strength and intentions, environment and terrain, sociocultural factors, the strength of one’s own forces, changing weather conditions, and communications, among others all need to be considered while accessing a tactical situation (Paparone & Reed, 2011). Route clearance is one such mission that has accounted for more than 50% of US army casualties overseas (Wilson, 2007). Improvised Explosive Devices (IEDs) are generally hidden from plain sight (e.g., buried under sand) and come in many sizes, shapes, and forms, making emplaced IEDs difficult to detect (Nixon et al., 2015). HATs could possibly be implemented in such high-risk high uncertainty task. The goal of the study is to use the route clearance task as a use case scenario to evaluate the interaction between humans and AI agents and determine the expectations placed on the AI agent. In this study we also aim to understand the preferred modes of communication in a human-AI team from a human perspective. We will focus on evaluating human-AI teams facilitating mutually beneficial decisionmaking through bidirectional communication in a high-risk environment. Using an interview-based study (N = 20), we will explore the following research objectives: Objective 1: Understand humans’ perspectives for having and accepting an AI teammate Objective 2: Identify expectations placed on an AI teammate in human-AI teams. Objective 3: Identify the best practices for completing a route clearance task through human-AI teaming. Objective 4: Identify the preferred modes of communicating between human and AI teammates.