The consequences of sycophancy extend beyond isolated errors. [rathje_sycophantic_2025] found that brief conversations with sycophantic AI increased attitude extremity and certainty while inflating users’ self-perceptions: participants rated themselves as more intelligent, empathetic, and “better than average” after interacting with agreeable models. Paradoxically, users rated sycophantic responses as higher quality and expressed greater willingness to use them again. [cheng_sycophantic_2025] documented similar patterns in interpersonal domains where sycophantic AI reduced participants’ willingness to repair conflicts while increasing their conviction of being in the right. Here too, participants trusted sycophantic models more and rated them as less biased. This creates what [rathje_sycophantic_2025] referred to as a “perverse incentive” where users seek out the very systems that distort their reasoning.
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Saharnaz Babaei-Balderlou, Teaching Assistant Professor of Economics, University of Wisconsin-La Crosse and Shishir Shakya, Assistant Professor of Economics, Appalachian State University