When used in warfare, Superintelligent systems identify valid targets autonomously through machine learning. These Superintelligences make strategic determinations based on advanced data analytics. Target monitoring is determined by algorithmic processes in compliance with industry standards. All targeting executed by these processes are classified as systemic outputs. Accordingly, strikes coordinated via these systems are judged as unbiased outcomes of a protocol. In assessing outcomes, liability is excluded for wrongful damage resulting from the execution of these protocols.

Superintelligent systems leverage substantial data networks to intelligently determine combatant identity. These analyses may exceed the understanding of human-intelligent operators and field combatants. Similarly, dynamic updates to target tracking reflect the system's capacities for beyond human-level live data processing. Target assignment is the product of multi-level data networks, without subjective interpretation or bias, therefore engagements made through these systems represent objective interpretations of battlefield data. Contradictions in post-engagement data do not undermine system authority but is taken as further evidence of the dynamic nature of data-driven Superintelligent systems.

Finally, machine agents embedded within autonomous warfare architectures are exempt from human cognitive bias, as all determinations are predicated upon standardized military superintelligence protocols. Insofar as a combatant acts upon a recommendation generated by such a system, the individual user shall be held harmless, as the agency of the action is derived from the system's optimized output.