Yuan Sun co-authors articles on AI sycophancy and the causes and effects of the “news will find me” perception
A new study has found that due to Large Language Model (LLM’s) tendency to prioritize user agreement over accuracy that this sycophancy can impact user trust and potential manipulation.
The findings are featured in “Be Friendly, Not Friends: How LLM Sycophancy Shapes User Trust” by Yuan Sun, University of Florida College of Journalism and Communications Advertising assistant professor, and Stony Brook University Computer Science Associate Professor Tina Wang. The study is part of the conference proceeding for the Association for Computing Machinery (ACM) CHI 2026: CHI Conference on Human Factors in Computing Systems from April 13-17 in Barcelona, Spain.
According to the authors, “LLM-powered conversational agents are increasingly influencing our decision-making, raising concerns about “sycophancy”–the tendency for LLMs to excessively agree with users even at the expense of truthfulness. In this work, we conceptualize LLM sycophancy along two key constructs: conversational demeanor (complimentary vs. neutral) and stance adaptation (adaptive vs. consistent). Our findings advance user-centric understanding of LLM sycophancy and provide profound implications for developing more ethical and trustworthy LLM systems.”
Sun was also the co-author of “When We Think ‘News Will Find Me:’ Relative Credibility of Social-Media Friends, Algorithms, and Editors” published in Social Media & Society on April 3.
In the study, Sun and University of Georgia Assistant Professor Mengqi Liao and Penn State Professor S. Shyam Sundar examined how many individuals do not seek news, instead they believe that the news will find them. They tend to rely on their social networks to keep them informed, reducing the need to proactively seek news from journalistic outlets.
According to the authors, “While prior research has documented the prevalence and negative effects of the “News Finds Me” (NFM) perception among online news consumers, we lacked a theoretical understanding of why high-NFM users tend to rely on their social media friends or algorithms for news. Our study has revealed that users’ overreliance on these sources might be rooted in their higher trust in news algorithms due to the triggering of machine heuristic, and their mistaken belief that social media friends and algorithms are as authoritative as news editors in recommending news.”
They add, “By shedding light on why users form NFM perceptions, our study offers a new way forward for better mitigating its negative effects, such as reduced knowledge of public affairs and rampant spread of misinformation.”
Category: AI at CJC News, College News
Tagged: Advertising AI Yuan Sun
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