RESUMO
In an increasingly complex military operating environment, next generation wargaming platforms can reduce risk, decrease operating costs, and improve overall outcomes. Novel Artificial Intelligence (AI) enabled wargaming approaches, based on software platforms with multimodal interaction and visualization capacity, are essential to provide the decision-making flexibility and adaptability required to meet current and emerging realities of warfighting. We highlight three areas of development for future warfighter-machine interfaces: AI-directed decisional guidance, computationally informed decision-making, and realistic representations of decision spaces. Progress in these areas will enable development of effective human-AI collaborative decision-making, to meet the increasing scale and complexity of today's battlespace.
RESUMO
OBJECTIVE: Intelligence analysis is a necessary operation for organizations engaged in adversarial decision making in military, criminal justice, and civil spheres. In particular, we focus on studying the sentiment of actors in a military-relevant decision-making task and how information pertaining to these actors is presented. BACKGROUND: Two intelligence analysis systems were created to represent sentiment data. METHOD: These systems and another with the raw information (i.e., the control condition) were presented to experimental participants in separate trials with the pretext that they act as intelligence analysts and compare two social media actors in U.S.-occupied territory on given subject matters. RESULTS: Results demonstrated that cognitive processing of the information improved and was preferred for the prototype that presented information in scatterplot form rather than a line graph, though side-by-side comparisons also were preferred from the disfavored system. CONCLUSION: We conclude with suggestions for designing intelligence analysis software that conforms to best practice in human factors with a focus on cognitive processing. APPLICATION: We hope these recommendations will improve intelligence analysis of sentiment information via a new system.
