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In an effort to guarantee that machine learning model outputs conform withhuman moral values, recent work has begun exploring the possibility ofexplicitly training models to learn the difference between right and wrong.This is typically done in a bottom-up fashion, by exposing the model todifferent scenarios, annotated with human moral judgements. One question,however, is whether the trained models actually learn any consistent,higher-level ethical principles from these datasets -- and if so, what? Here,we probe the Allen AI Delphi model with a set of standardized moralityquestionnaires, and find that, despite some inconsistencies, Delphi tends tomirror the moral principles associated with the demographic groups involved inthe annotation process. We question whether this is desirable and discuss howwe might move forward with this knowledge.

Does Moral Code Have a Moral Code? Probing Delphi's Moral Philosophy