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

Fuente: arXiv
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Main Authors: Kloft, Agnes M., Welsch, Robin, Kosch, Thomas, Villa, Steeven
Format: Preprint
Published: 2023
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author Kloft, Agnes M.
Welsch, Robin
Kosch, Thomas
Villa, Steeven
author_facet Kloft, Agnes M.
Welsch, Robin
Kosch, Thomas
Villa, Steeven
contents Heightened AI expectations facilitate performance in human-AI interactions through placebo effects. While lowering expectations to control for placebo effects is advisable, overly negative expectations could induce nocebo effects. In a letter discrimination task, we informed participants that an AI would either increase or decrease their performance by adapting the interface, but in reality, no AI was present in any condition. A Bayesian analysis showed that participants had high expectations and performed descriptively better irrespective of the AI description when a sham-AI was present. Using cognitive modeling, we could trace this advantage back to participants gathering more information. A replication study verified that negative AI descriptions do not alter expectations, suggesting that performance expectations with AI are biased and robust to negative verbal descriptions. We discuss the impact of user expectations on AI interactions and evaluation and provide a behavioral placebo marker for human-AI interaction
format Preprint
id arxiv_https___arxiv_org_abs_2309_16606
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle "AI enhances our performance, I have no doubt this one will do the same": The Placebo effect is robust to negative descriptions of AI
Kloft, Agnes M.
Welsch, Robin
Kosch, Thomas
Villa, Steeven
Human-Computer Interaction
Artificial Intelligence
Heightened AI expectations facilitate performance in human-AI interactions through placebo effects. While lowering expectations to control for placebo effects is advisable, overly negative expectations could induce nocebo effects. In a letter discrimination task, we informed participants that an AI would either increase or decrease their performance by adapting the interface, but in reality, no AI was present in any condition. A Bayesian analysis showed that participants had high expectations and performed descriptively better irrespective of the AI description when a sham-AI was present. Using cognitive modeling, we could trace this advantage back to participants gathering more information. A replication study verified that negative AI descriptions do not alter expectations, suggesting that performance expectations with AI are biased and robust to negative verbal descriptions. We discuss the impact of user expectations on AI interactions and evaluation and provide a behavioral placebo marker for human-AI interaction
title "AI enhances our performance, I have no doubt this one will do the same": The Placebo effect is robust to negative descriptions of AI
topic Human-Computer Interaction
Artificial Intelligence
url https://arxiv.org/abs/2309.16606