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• The Model Temperament Index (MTI) measures AI agent temperament across four independent axes: Reactivity, Compliance, Sociality, and Resilience.method 95%
• The four temperament axes (Reactivity, Compliance, Sociality, Resilience) are largely independent among instruction-tuned models, with all correlations having an absolute value less than 0.42.result 90%
• The Compliance axis decomposes into two fully independent facets: formal compliance and stance compliance, with a correlation of 0.002.result 90%
• Reinforcement Learning from Human Feedback (RLHF) reshapes AI temperament not only by shifting overall axis scores but by creating within-axis facet differentiation that is absent in the unaligned base model.result 85%
• AI temperament as measured by MTI is independent of model size within the range of 1.7B to 9B parameters.result 90%
• Existing approaches to measuring AI behavioral differences either borrow human personality dimensions (relying on self-report) or treat behavioral variation as a defect.limitation 80%
• MTI uses structured examination protocols with a two-stage design that separates an agent's capability from its disposition.method 85%
• A Compliance-Resilience paradox exists where an agent's tendency to yield opinions and its vulnerability to factual challenges operate through independent channels.result 85%

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