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We examine whether large language models (LLMs) can predict biased decision-making in conversational settings, and whether their predictions capture not only human cognitive biases but also how those effects change under cognitive load. In…

人机交互 · 计算机科学 2026-02-06 Stephen Pilli , Vivek Nallur

Large language models (LLMs) are revolutionizing every aspect of society. They are increasingly used in problem-solving tasks to substitute human assessment and reasoning. LLMs are trained on what humans write and are thus exposed to human…

软件工程 · 计算机科学 2025-10-14 Fengfei Sun , Ningke Li , Kailong Wang , Lorenz Goette

Large Language Models (LLMs) are transforming human decision-making by acting as cognitive collaborators. Yet, this promise comes with a paradox: while LLMs can improve accuracy, they may also erode independent reasoning, promote…

密码学与安全 · 计算机科学 2025-09-09 Irdin Pekaric , Philipp Zech , Tom Mattson

Large language models (LLMs) exhibit strikingly conflicting behaviors: they can appear steadfastly overconfident in their initial answers whilst at the same time being prone to excessive doubt when challenged. To investigate this apparent…

Large Language Models (LLMs) are increasingly deployed in multilingual and multicultural environments where moral reasoning is essential for generating ethically appropriate responses. Yet, the dominant pretraining of LLMs on…

计算与语言 · 计算机科学 2025-09-29 Sualeha Farid , Jayden Lin , Zean Chen , Shivani Kumar , David Jurgens

Cognitive biases are systematic deviations in thinking that lead to irrational judgments and problematic decision-making, extensively studied across various fields. Recently, large language models (LLMs) have shown advanced understanding…

计算与语言 · 计算机科学 2024-10-10 Nuo Chen , Jiqun Liu , Xiaoyu Dong , Qijiong Liu , Tetsuya Sakai , Xiao-Ming Wu

We explore how large language models (LLMs) can be influenced by prompting them to alter their initial decisions and align them with established ethical frameworks. Our study is based on two experiments designed to assess the susceptibility…

计算与语言 · 计算机科学 2024-11-19 Allison Huang , Yulu Niki Pi , Carlos Mougan

Large Language Models (LLMs) are already as persuasive as humans. However, we know very little about how they do it. This paper investigates the persuasion strategies of LLMs, comparing them with human-generated arguments. Using a dataset…

计算与语言 · 计算机科学 2024-04-23 Carlos Carrasco-Farre

Human decision-making belongs to the foundation of our society and civilization, but we are on the verge of a future where much of it will be delegated to artificial intelligence. The arrival of Large Language Models (LLMs) has transformed…

人工智能 · 计算机科学 2025-06-23 Hao Li , Gengrui Zhang , Petter Holme , Shuyue Hu , Zhen Wang

Large Language Models (LLMs) are a transformational technology, fundamentally changing how people obtain information and interact with the world. As people become increasingly reliant on them for an enormous variety of tasks, a body of…

计算机与社会 · 计算机科学 2025-05-08 Nouar Aldahoul , Hazem Ibrahim , Matteo Varvello , Aaron Kaufman , Talal Rahwan , Yasir Zaki

Large Language Models (LLMs) have revolutionized artificial intelligence, demonstrating remarkable computational power and linguistic capabilities. However, these models are inherently prone to various biases stemming from their training…

计算与语言 · 计算机科学 2025-02-14 Riccardo Cantini , Giada Cosenza , Alessio Orsino , Domenico Talia

As large language models (LLMs) become increasingly integrated into society, their alignment with human morals is crucial. To better understand this alignment, we created a large corpus of human- and LLM-generated responses to various moral…

人机交互 · 计算机科学 2024-10-11 Basile Garcia , Crystal Qian , Stefano Palminteri

The widespread integration of Large Language Models (LLMs) across various sectors has highlighted the need for empirical research to understand their biases, thought patterns, and societal implications to ensure ethical and effective use.…

计算与语言 · 计算机科学 2025-05-20 Manari Hirose , Masato Uchida

We investigate whether large language models (LLMs) can predict whether they will succeed on a given task and whether their predictions improve as they progress through multi-step tasks. We also investigate whether LLMs can learn from…

计算与语言 · 计算机科学 2026-01-01 Casey O. Barkan , Sid Black , Oliver Sourbut

Large language models (LLMs) have the potential to aid and improve human decision-making in classification tasks, not only by providing fairly accurate predictions, but also in their ability to generate cogent narrative explanations of…

人机交互 · 计算机科学 2026-05-25 Laura R. Marusich , Mary Grace Kozuch Dhooghe , Jonathan Z. Bakdash , Murat Kantarcioglu

In order for AI systems to communicate effectively with people, they must understand how we make decisions. However, people's decisions are not always rational, so the implicit internal models of human decision-making in Large Language…

计算与语言 · 计算机科学 2025-03-11 Ryan Liu , Jiayi Geng , Joshua C. Peterson , Ilia Sucholutsky , Thomas L. Griffiths

Large Language Models (LLMs) are trained on large corpora written by humans and demonstrate high performance on various tasks. However, as humans are susceptible to cognitive biases, which can result in irrational judgments, LLMs can also…

计算与语言 · 计算机科学 2024-12-03 Yasuaki Sumita , Koh Takeuchi , Hisashi Kashima

Large Language Models (LLMs) have become increasingly incorporated into everyday life for many internet users, taking on significant roles as advice givers in the domains of medicine, personal relationships, and even legal matters. The…

计算与语言 · 计算机科学 2025-10-17 Nicole Smith-Vaniz , Harper Lyon , Lorraine Steigner , Ben Armstrong , Nicholas Mattei

Millions of users turn to AI models for their information needs. It is conceivable that a large number of user queries contain assumptions that may be factually inaccurate. Prior work notes that large language models (LLMs) often fail to…

计算与语言 · 计算机科学 2026-05-06 Rose Sathyanathan , Kinshuk Vasisht , Danish Pruthi

Large language models (LLMs) are transforming research on machine learning while galvanizing public debates. Understanding not only when these models work well and succeed but also why they fail and misbehave is of great societal relevance.…

计算与语言 · 计算机科学 2024-10-16 Julian Coda-Forno , Kristin Witte , Akshay K. Jagadish , Marcel Binz , Zeynep Akata , Eric Schulz
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