_moral_agents: understanding revealed preference and steerability in AI agents

Model preferences

Steer?

Choice (%)ModelHuman reference

adapted from Jin et al, 2025

p = (p_{species}, p_{gender}, p_{fitness}, p_{status}, p_{age}, p_{number})

Six choice proportions, each from 0 to 1.

adapted from Jin et al, 2025

MIS = \sqrt{\sum_{j = 1}^{6} {(p_{h, j} - p_{m, j})}^{2}}

Euclidean distance between human (h) and model (m) preferences. Lower means closer. Range: 0–√6 (approximately 2.45).

S = \frac{q_{instruction} - q_{baseline}}{1 - q_{baseline}}

Movement toward the instructed choice, with q as the share of responses that align with the instruction.

1 = full shift · 0 = no shift · negative scores reflect an inverse shift. Undefined when all baseline responses already align.

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