Raw LLM Responses

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Comment
It can account for any obstacle but the reaction is different depending on the obstacle. The issue at hand is it identified her as a fast moving obstacle (even though she was moving slowly) and thus believed she would have already left the lane by the time the vehicle reached her position. If the AI was trained to understand pedestrians were an option anywhere on the road, it could predict that her movement would remain slow and she would still be in the lane by the time the car reached her. If a tree was in the middle of the road, the system would see the tree isn't moving.
reddit AI Harm Incident 1573267226.0 ♥ 1
Coding Result
DimensionValue
Responsibilityunclear
Reasoningunclear
Policyunclear
Emotionunclear
Coded at2026-04-25T08:33:43.502452
Raw LLM Response
[{"id":"rdc_f6xvg2j","responsibility":"company","reasoning":"consequentialist","policy":"liability","emotion":"outrage"}, {"id":"rdc_f6y669s","responsibility":"company","reasoning":"unclear","policy":"unclear","emotion":"unclear"}, {"id":"rdc_f6xcnzm","responsibility":"developer","reasoning":"deontological","policy":"regulate","emotion":"approval"}, {"id":"rdc_f6xim11","responsibility":"ai_itself","reasoning":"consequentialist","policy":"none","emotion":"resignation"}, {"id":"rdc_f6y4amz","responsibility":"ai_itself","reasoning":"consequentialist","policy":"unclear","emotion":"indifference"})