We stand at a peculiar hinge in military history. Machines now carry sensors deeper and longer into battlefields, algorithms sift intelligence at speeds our brains cannot match, and autonomy is moving from assistive scripts to consequential judgements. Preparation for war was once a matter of physical conditioning, doctrine, and a hardening of nerves. In the era of pervasive autonomy, psychological preparation must add new domains: calibrated trust in automation, training for moral complexity at a remove, and institutional practices that protect human agency and mental health when machines mediate violence. Evidence and experience from recent decades show these are not theoretical worries, they are operational necessities.
Remote operators and intelligence specialists provide early lessons. Studies and narrative reviews of unmanned aerial vehicle crews reveal elevated risks of emotional exhaustion, burnout, and forms of moral injury that differ from classical combat trauma. Operators describe prolonged witness to violence via high definition feeds, followed by an immediate return to ordinary life, a type of temporal and moral dislocation that creates unique psychological strain. Clinical and survey work across nations documents meaningful rates of distress and stress symptoms among remote aircrews, and highlights the need for tailored prevention and treatment strategies.
The phenomenon is not limited to North American programs. Comparative studies of UAV crews have found that seniority, exposure to battlefield imagery, and long duty hours correlate with higher stress measures, indicating that cumulative exposure matters even when physical danger to the operator is absent. Qualitative analyses of Reaper crews and similar teams point to poor preparatory training for moral exposure, intense scrutiny after incidents, and organizational gaps that amplify moral distress. These findings suggest that psychological preparation must begin in doctrine and flow through recruitment, training, operations, and post-mission care.
Three linked psychological tasks should guide a modern training syllabus. First, calibrate trust. Humans must learn when to rely on automated judgement, and when to withhold assent. Trust that is too low leaves capable systems unused, and trust that is too high makes operators blind to machine error. Building this calibration requires transparency in system behavior, deliberate exposure to system failure modes during training, and mission rehearsals that include autonomous agents as active participants rather than inert tools. Including autonomy early in mission planning and exercises allows human teams to ‘‘wrestle with how to trust’’ their machine partners, which is precisely the sort of learning that reduces brittle reliance in the field.
Second, inoculate for stress and cognitive load. Stress inoculation training, adaptive simulation, and progressive exposure to sensory and moral stressors reduce reactivity and build procedural resilience. Technology enabled learning, including high-fidelity simulation and extended reality, can present layered stressors: time pressure, degraded communications, ambiguous sensor returns, and cascading system faults. These environments permit safe rehearsal of decisions under duress, and they can be instrumented to measure decision latency, attentional collapse, and physiological markers of overload. Evidence compiled by national learning and defense bodies emphasizes that technology-enabled training is not an optional extra, it is an effective vector to build the specific cognitive skills required for human-machine teaming.
Third, prepare for moral injury and ethical complexity. Moral injury arises when individuals perpetrate, witness, or fail to prevent acts that transgress deeply held moral beliefs, or when an authority betrays moral expectations. The literature on moral injury, originally developed in veteran research, is directly applicable to machine-mediated killing, where operators may feel both distant and responsible for lethal outcomes. Training must therefore cultivate moral articulation: structured reflection, ethical rehearsal, and supervised debriefing so that personnel can name the moral stakes of actions taken with the assistance of machines. Clinical approaches developed for moral injury emphasize narrative repair and guided moral processing, interventions that should be adapted into military occupational health pathways.
Operational implementation needs practical policies. At the unit level, integrate AI literacy into basic and advanced courses so every operator understands the system’s limits, typical failure modes, and the indicators that should trigger human intervention. Make system transparency part of acceptance testing, and require mission rehearsals that include simulated autonomy failures. From a personnel management perspective, monitor cumulative exposure to high-intensity screen-mediated operations, enforce rotation and decompression windows, and normalize access to embedded mental health professionals who understand the interplay of technical error, cognitive load, and moral distress. These are not merely welfare measures, they are force preservation practices.
Training design must also address automation bias and signal detection. Teach operators pattern recognition that includes not only what machines detect, but when machines fail to detect. Exercises should deliberately include false positives and false negatives so human teams practice skepticism without slipping into paralysis. Decision aids that present the system’s confidence and rationale, combined with interface affordances for rapid cross-checking, improve the predictability of automation and support better human judgement. Empirical work suggests that improving transparency of rationale and creating opportunities for human interrogation of machine outputs improves the accuracy of automation use while also exposing its predictable error modes.
A final domain is culture. Unit cultures that stigmatize mental health care, or that valorize unreflective technologism, will defeat even the best curricular innovations. Doctrinal statements and leadership guidance must therefore affirm the primacy of meaningful human control, and commanders should be evaluated for how they protect both the moral agency and psychological welfare of their people when deploying autonomous systems. International coalitions will require harmonization of training, because disparate attitudes toward autonomy and differing levels of trust among partners can degrade coalition effectiveness.
Practical steps commanders and policy makers can enact immediately are straightforward. Require AI literacy modules in professional military education. Institute stress inoculation and XR rehearsal programs targeted to roles that will have high exposure to machine-mediated violence. Embed mental health practitioners in ISR and autonomy units, and build post-mission moral debriefs into standard operating procedures. Finally, mandate that new systems come with accessible documentation of failure modes and a plan for how training will teach calibration of trust. These measures are modest in cost compared to the human and strategic costs of miscalibrated trust, burned-out crews, and avoidable moral injury.
The philosophical point is simple, if easy to neglect. Machines reorder responsibilities, but they do not erase moral choice. To treat autonomy as merely a technological optimization is to ask humans to perform moral and cognitive labor without giving them the conceptual tools or institutional protections to do it well. Psychological preparation for machine-dominated wars must therefore be as much about cultivating judgment, conscience, and communal support as it is about ergonomics and sensor feeds. If we do this work now, we preserve both effectiveness in conflict and the moral integrity of the people we send to wage it.