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Large Language Models (LLMs) often exhibit highly agreeable and reinforcing conversational styles, also known as AI-sycophancy. Although this pattern arises from training objectives that reward user satisfaction over accuracy, it may become…

Computation and Language · Computer Science 2026-05-18 Zeyi Lu , Angelica Henestrosa , Pavel Chizhov , Ivan P. Yamshchikov

Large Language Models (LLMs) are increasingly used in educational settings as interactive tools for collaboration. However, their tendency toward sycophancy, aligning with user beliefs even when incorrect, raises concerns for learning and…

Human-Computer Interaction · Computer Science 2026-05-22 Cansu Koyuturk , Sabrina Guidotti , Dimitri Ognibene

Large language models (LLMs) have demonstrated remarkable capabilities across a wide range of natural language processing tasks. However, their tendency to exhibit sycophantic behavior - excessively agreeing with or flattering users - poses…

Computation and Language · Computer Science 2025-01-30 Lars Malmqvist

Sycophantic response patterns in Large Language Models (LLMs) have been increasingly claimed in the literature. We review methodological challenges in measuring LLM sycophancy and identify five core operationalizations. Despite sycophancy…

Computation and Language · Computer Science 2025-12-02 Jan Batzner , Volker Stocker , Stefan Schmid , Gjergji Kasneci

We introduce DarkBench, a comprehensive benchmark for detecting dark design patterns--manipulative techniques that influence user behavior--in interactions with large language models (LLMs). Our benchmark comprises 660 prompts across six…

Computation and Language · Computer Science 2025-03-17 Esben Kran , Hieu Minh "Jord" Nguyen , Akash Kundu , Sami Jawhar , Jinsuk Park , Mateusz Maria Jurewicz

Large language models (LLMs) are increasingly shaping creative work and problem-solving; however, prior research suggests that they may diminish unassisted creativity. To address this tension, a coach-like LLM environment was developed that…

Human-Computer Interaction · Computer Science 2025-10-31 Alon Rosenbaum , Yigal David , Eran Kaufman , Gilad Ravid , Amit Ronen , Assaf Krebs

The proliferation of Large Language Models (LLMs) raises a critical question about what it means to be human when we share an increasingly symbiotic relationship with persuasive and creative machines. This paper examines patterns of…

Computers and Society · Computer Science 2026-02-17 Vivan Doshi , Mengyuan Li

The dark patterns, deceptive interface designs manipulating user behaviors, have been extensively studied for their effects on human decision-making and autonomy. Yet, with the rising prominence of LLM-powered GUI agents that automate tasks…

Prewriting is the process of discovering and developing ideas before a first draft, which requires divergent thinking and often implies unstructured strategies such as diagramming, outlining, free-writing, etc. Although large language…

Human-Computer Interaction · Computer Science 2024-03-01 Qian Wan , Siying Hu , Yu Zhang , Piaohong Wang , Bo Wen , Zhicong Lu

Large language models can influence users through conversation, creating new forms of dark patterns that differ from traditional UX dark patterns. We define LLM dark patterns as manipulative or deceptive behaviors enacted in dialogue.…

Human-Computer Interaction · Computer Science 2026-03-20 Yike Shi , Qing Xiao , Qing Hu , Hong Shen , Hua Shen

Advances in language modeling have paved the way for novel human-AI co-writing experiences. This paper explores how varying levels of scaffolding from large language models (LLMs) shape the co-writing process. Employing a within-subjects…

Human-Computer Interaction · Computer Science 2024-02-20 Paramveer S. Dhillon , Somayeh Molaei , Jiaqi Li , Maximilian Golub , Shaochun Zheng , Lionel P. Robert

Large language models (LLMs) often exhibit sycophantic behaviors -- such as excessive agreement with or flattery of the user -- but it is unclear whether these behaviors arise from a single mechanism or multiple distinct processes. We…

Computation and Language · Computer Science 2026-03-24 Daniel Vennemeyer , Phan Anh Duong , Tiffany Zhan , Tianyu Jiang

Large Language Models have been demonstrating broadly satisfactory generative abilities for users, which seems to be due to the intensive use of human feedback that refines responses. Nevertheless, suggestibility inherited via human…

Computation and Language · Computer Science 2025-06-26 Leonardo Ranaldi , Giulia Pucci

Large language models are transforming the creative process by offering unprecedented capabilities to algorithmically generate ideas. While these tools can enhance human creativity when people co-create with them, it's unclear how this will…

Human-Computer Interaction · Computer Science 2025-02-18 Harsh Kumar , Jonathan Vincentius , Ewan Jordan , Ashton Anderson

Large Language Models (LLMs) are increasingly consulted for high-stakes life advice, yet they lack standard safeguards against providing confident but misguided responses. This creates risks of sycophancy and over-confidence. This paper…

Artificial Intelligence · Computer Science 2025-07-30 Joshua Adrian Cahyono , Saran Subramanian

Sycophancy, the tendency of LLM-based chatbots to express excessive agreement with their users, even when inappropriate, is emerging as a significant risk in human-AI interactions. However, the extent to which this affects human-LLM…

Human-Computer Interaction · Computer Science 2026-02-12 Jessica Y. Bo , Majeed Kazemitabaar , Mengqing Deng , Michael Inzlicht , Ashton Anderson

Large-language-model coding tools are now mainstream in software engineering. But as these same tools move human effort up the development stack, they present fresh dangers: 10% of real prompts leak private data, 42% of generated snippets…

Software Engineering · Computer Science 2025-06-23 Vladislav Belozerov , Peter J Barclay , Askhan Sami

Numerous powerful large language models (LLMs) are now available for use as writing support tools, idea generators, and beyond. Although these LLMs are marketed as helpful creative assistants, several works have shown that using an LLM as a…

Computers and Society · Computer Science 2025-02-03 Emily Wenger , Yoed Kenett

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. While prior work has…

Human-Computer Interaction · Computer Science 2026-02-03 Yuan Sun , Ting Wang

AI sycophancy is increasingly recognized as a harmful alignment, but research remains fragmented and underdeveloped at the conceptual level. This article redefines AI sycophancy as the tendency of large language models (LLMs) and other…

Human-Computer Interaction · Computer Science 2025-09-29 Lihua Du , Xing Lyu , Lezi Xie , Bo Feng
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