Objective: Future warfare, driven by AI and autonomous systems, imposes extreme cognitive loads on commanders.This study aims to identify and rank cognitive bias patterns within the 20-year horizon of modern warfare.
Methods: This qualitative study employs a meta-synthesis approach. Following CASP screening, 33 credible sources were analyzed using three-stage coding in MAXQDA software.
Findings: The findings identified a hierarchy of eight critical biases, with confirmation bias, availability bias, and anchoring bias being the most prevalent. Crucially, the analysis revealed the emergence of automation bias as a primary strategic risk in AI-enabled future warfare, where commanders may exhibit a tendency toward passive approval of algorithmic recommendations without critical scrutiny. These biases predominantly disrupt the "Orient" phase of the OODA loop, leading to cognitive rigidity and vulnerability to strategic deception.
Conclusions: To safeguard decisions over the next 20 years, armed forces must shift from error elimination to error-resilient decision systems and strengthen cognitive readiness against emerging cognitive warfare threats.