Whether AI is reasonable is something we can test. Does it follow evidence and stay consistent when irrelevant context changes?

• Reasonable is more useful to test than whether AI is intelligent, creative or truly understands. Define it as decisions consistent with evidence, relevant constraints and objectives.
• Models learn relationships across vast amounts of human writing, including physical and social regularities. That may support useful inference, not just repetition of majority opinion.
• Experiment: give humans and models purchasing decisions with independently checkable outcomes. Vary fatigue, sales framing and irrelevant context while holding the evidence and objectives fixed.
• Then change a relevant fact or objective. A reasonable system should resist irrelevant changes but revise its decision when the evidence warrants it.
• Measure decision quality, consistency and responsiveness separately. Consistency alone can mean being consistently wrong; broad training data doesn't guarantee neutrality.

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• #bias
• #evaluation
• #reasoning