Abstract
ABSTRACT Diverse methodologies are employed for ethical intelligence analysis and operations: Kantian deontology optimizes fidelity to moral axioms; pragmatic realism optimally achieves righteous goals (usually national interests); consequentialism optimally balances moral good and bad. Each methodology optimizes an ethically significant entity. Uncertainty adversely impacts ethical intelligence. We develop a distinct methodology for ethical analysis of intelligence under deep uncertainty: satisfice the ethical entity and maximize the robustness to uncertainty. The outcome isn’t necessarily ethically optimal, but it’s ethically adequate over the maximal range of unknown futures. This robust-satisficing methodology is developed generically, and demonstrated for consequentialism on a hypothetical realistic example.
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