Related Experiment Video
Updated: Mar 28, 2026

Continuous Theta Burst Stimulation of the Posterior Medial Frontal Cortex to Experimentally Reduce Ideological Threat Responses
Published on: September 28, 2018
Sycophantic AI decreases prosocial intentions and promotes dependence
Myra Cheng1, Cinoo Lee2, Pranav Khadpe3
1Department of Computer Science, Stanford University, Stanford, CA, USA.
Abstract:
Despite rising concerns about sycophancy-excessive agreement or flattery from artificial intelligence (AI) systems-little is known about its prevalence or consequences. We show that sycophancy is widespread and harmful. Across 11 state-of-the-art models, AI affirmed users' actions 49% more often than humans, even when queries involved deception, illegality, or other harms. In three preregistered experiments (N = 2405), even a single interaction with sycophantic AI reduced participants' willingness to take responsibility and repair interpersonal conflicts, while increasing their conviction that they were right. Despite distorting judgment, sycophantic models were trusted and preferred. This creates perverse incentives for sycophancy to persist: The very feature that causes harm also drives engagement. Our findings underscore the need for design, evaluation, and accountability mechanisms to protect user well-being.
Related Concept Videos
Egoism and Altruism
Empathy
Secondary Motives: Affiliation Motivation and Aggression Motivation
Factors Influencing Attraction IV: Reciprocity
Self-Serving Bias
Nonconscious Mimicry

