The “hungry judge” effect, as presented by a famous study, is a common point of reference to underline human bias in judicial decision-making. This is particularly pronounced in the literature on “artificial intelligence” (AI) in law. Here, the effect is invoked to counter concerns about bias in automated decision-aids and to motivate their use. However, the validity of the “hungry judge” effect is doubtful. In our context, this is problematic for, at least, two reasons. First, shaky evidence leads to a misconstruction of the problem that may warrant an AI intervention. Second, painting the justice system worse than it actually is becomes a dangerous argumentative strategy, as it undermines institutional trust. Against this background, this article revisits the original “hungry judge” study and argues that it cannot be relied on as an argument in the AI discourse or beyond. The case of “hungry judges” demonstrates the lure of narratives, the dangers of “problem gerrymandering,” and, ultimately, the need for a careful reception of social science.

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