teleo-codex/foundations/collective-intelligence/_map.md

Collective Intelligence — The Theory

What collective intelligence IS, how it works, and the theoretical foundations for designed emergence. Domain-independent science — the TeleoHumanity-specific interpretation lives in core/teleohumanity/, and alignment-specific applications live in domains/ai-alignment/.

Intelligence Foundations

• intelligence is a property of networks not individuals — the core premise
• collective intelligence is a measurable property of group interaction structure not aggregated individual ability — CI is structural, not aggregate
• collective intelligence requires diversity as a structural precondition not a moral preference — diversity is functional engineering
• centaur team performance depends on role complementarity not mere human-AI combination — conditional, not unconditional
• partial connectivity produces better collective intelligence than full connectivity on complex problems because it preserves diversity — network topology matters
• collective intelligence within a purpose-driven community faces a structural tension because shared worldview correlates errors while shared purpose enables coordination — the core tension

Coordination Design

• designing coordination rules is categorically different from designing coordination outcomes as nine intellectual traditions independently confirm — rules not outcomes
• Ostrom proved communities self-govern shared resources when eight design principles are met without requiring state control or privatization — the empirical evidence
• protocol design enables emergent coordination of arbitrary complexity as Linux Bitcoin and Wikipedia demonstrate — the existence proofs
• trial and error is the only coordination strategy humanity has ever used — the current limitation
• Hayek argued that designed rules of just conduct enable spontaneous order of greater complexity than deliberate arrangement could achieve — the Hayek insight

AI Alignment as Coordination (domain-independent theory)

• universal alignment is mathematically impossible because Arrows impossibility theorem applies to aggregating diverse human preferences into a single coherent objective — the impossibility result
• RLHF and DPO both fail at preference diversity because they assume a single reward function can capture context-dependent human values — why current approaches fail
• scalable oversight degrades rapidly as capability gaps grow with debate achieving only 50 percent success at moderate gaps — the scalability problem
• multipolar failure from competing aligned AI systems may pose greater existential risk than any single misaligned superintelligence — the multipolar risk
• the alignment tax creates a structural race to the bottom because safety training costs capability and rational competitors skip it — the race dynamic

Moved to other layers (foundations audit 2026-03-07)

Claims below were moved because they are TeleoHumanity interpretations or alignment-domain claims, not domain-independent CI theory:

• → core/teleohumanity/: collective superintelligence as alternative, three paths to SI, alignment dissolves with continuous weaving
• → domains/ai-alignment/: AI alignment is coordination problem, safe before scaling, no research group building CI alignment