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Heightened AI expectations facilitate performance in human-AI interactionsthrough placebo effects. While lowering expectations to control for placeboeffects is advisable, overly negative expectations could induce nocebo effects.In a letter discrimination task, we informed participants that an AI wouldeither increase or decrease their performance by adapting the interface, but inreality, no AI was present in any condition. A Bayesian analysis showed thatparticipants had high expectations and performed descriptively betterirrespective of the AI description when a sham-AI was present. Using cognitivemodeling, we could trace this advantage back to participants gathering moreinformation. A replication study verified that negative AI descriptions do notalter expectations, suggesting that performance expectations with AI are biasedand robust to negative verbal descriptions. We discuss the impact of userexpectations on AI interactions and evaluation and provide a behavioral placebomarker for human-AI interaction

"AI enhances our performance, I have no doubt this one will do the same": The Placebo effect is robust to negative descriptions of AI