P03 / Project dossier
BETA-MIND
Designed a research program to measure how persistent AI use changes independent reasoning, socialization, creativity, and decision accountability.
Challenge
Most AI evaluations measure whether a model produces a capable answer. They rarely measure what repeated use leaves behind in the person: whether they can still reason independently, tolerate disagreement, generate diverse ideas, and own consequential decisions without AI.
Existing single-session studies are also poorly suited to an AI-native cohort for whom exposure is continuous across work, learning, relationships, and judgment.
Approach
Designed BETA-MIND as a longitudinal research program organized around four dimensions of human agency: independent reasoning, socialization, creativity, and decision accountability. Specified two open artifacts—a multi-agent simulator for long-horizon dependency dynamics and a Human Agency Benchmark for scored behavioral evaluation.
Defined comparative study arms, observable success gates, a non-compensatory agency index, and a bounded twelve-month work package separating synthetic simulation from later human-subject validation.
What changed
Produced a proposal-ready research architecture with defined hypotheses, behavioral measures, evaluation thresholds, open deliverables, and a phased execution plan.
The framework makes human agency a first-class AI evaluation target and prevents gains in task capability from concealing losses in reasoning, dissent, creativity, or accountability.
Why it matters