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Series

Equity and Trust Engineering

Six components detect, simulate, and correct for demographic disparity. Trust and cognitive bias are modeled as multi-dimensional vectors, not single scores. Population-level monitoring disaggregates outcomes by intersectional identity and publishes the results annually.

BMT-11.01
The Liberation AI Framework
Six components form a composition where removing any one breaks the circuit. I-ICE captures intersectional identity, ISHI measures outcome disparities, IIPM classifies root causes, …
Exec Summary + Appendix
BMT-11.02
Trust Vector Quantization
Trust in an external agent is a sixteen-plus dimensional vector covering competence, integrity, benevolence, and contextual variation. Quantized into discrete tiers to resist …
Exec Summary + Appendix
BMT-11.03
Irrationality Protection
Loss aversion, anchoring, status quo bias: cognitive patterns modeled as features to serve, not defects to correct. IVQ translates system communication to match how the person …
Exec Summary + Appendix
BMT-11.04
Population-Level Equity Monitoring
Population-level ISHI disaggregates outcomes by race, geography, income, deployment path, and device configuration. h-ABM simulates interventions before deployment. FSSVA detects …
Exec Summary + Appendix
Synthesis
BMT-11.SYN · Synthesis
The Equity You Can Measure
Three threats to equity, a six-system measurement apparatus, a bounded claim about what the platform can and cannot solve, and a transparency commitment that compounds with each annual cycle of detection and remediation.
Exec Summary by Syam