Intelligence, Consciousness, and Wisdom: A Hierarchical Framework for AI Ethics and Alignment

Contemporary AI alignment research faces a persistent implementation gap: agreed ethical principles do not reliably translate into aligned behavior. This paper argues that the gap is structural, not a failure of principle specification. Using an extended hierarchy of informational organization — Data, Information, Knowledge, Intelligence, Consciousness, Wisdom — I distinguish intelligence, consciousness, and wisdom as functionally distinct capacities that can arise independently. Current AI systems operate at the level of intelligence: they predict, optimize, and adapt without the evaluative integration required for wisdom. Building on recent theory-derived assessments of AI consciousness [Butlin et al., 2023; Chalmers, 2023], I argue that the same architectural gaps associated with consciousness — including absent global-workspace organization, recurrent integration, and unified agency — also explain why behavioral alignment methods such as RLHF and Constitutional AI cannot close the evaluative gap. The paper specifies falsifiable conditions under which this claim would fail and frames wisdom as a structurally distinct mode of value-integrative cognition, not an enhanced form of intelligence.