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Large language models (LLMs) are increasingly used to simulate human decision-making, but their intrinsic biases often diverge from real human behavior--limiting their ability to reflect population-level diversity. We address this challenge…

计算机科学与博弈论 · 计算机科学 2025-08-27 Ayato Kitadai , Yusuke Fukasawa , Nariaki Nishino

Large Language Models (LLMs), such as GPT-4 and BERT, have rapidly gained traction in natural language processing (NLP) and are now integral to financial decision-making. However, their deployment introduces critical challenges,…

计算机与社会 · 计算机科学 2024-10-29 Hui Zhong , Songsheng Chen , Mian Liang

Do generative AI models, particularly large language models (LLMs), exhibit systematic behavioral biases in economic and financial decisions? If so, how can these biases be mitigated? Drawing on the cognitive psychology and experimental…

综合经济学 · 经济学 2026-02-11 Pietro Bini , Lin William Cong , Xing Huang , Lawrence J. Jin

Large language models (LLMs) are increasingly proposed as agents in strategic decision environments, yet their behavior in structured geopolitical simulations remains under-researched. We evaluate six popular state-of-the-art LLMs alongside…

计算与语言 · 计算机科学 2026-03-03 Veronika Solopova , Viktoria Skorik , Maksym Tereshchenko , Alina Haidun , Ostap Vykhopen

Large language models (LLMs) have rapidly become indispensable tools for acquiring information and supporting human decision-making. However, ensuring that these models uphold fairness across varied contexts is critical to their safe and…

计算机与社会 · 计算机科学 2026-03-05 Xulang Zhang , Rui Mao , Erik Cambria

Large language models are increasingly used in decision-making tasks that require them to process information from a variety of sources, including both human experts and other algorithmic agents. How do LLMs weigh the information provided…

人工智能 · 计算机科学 2026-02-26 Jessica Y. Bo , Lillio Mok , Ashton Anderson

The emergence of Large Language Models (LLMs), has opened exciting possibilities for constructing computational simulations designed to replicate human behavior accurately. Current research suggests that LLM-based agents become increasingly…

计算与语言 · 计算机科学 2024-12-18 Amir Taubenfeld , Yaniv Dover , Roi Reichart , Ariel Goldstein

Cognitive biases often shape human decisions. While large language models (LLMs) have been shown to reproduce well-known biases, a more critical question is whether LLMs can predict biases at the individual level and emulate the dynamics of…

人工智能 · 计算机科学 2026-02-27 Stephen Pilli , Vivek Nallur

Large Language Models (LLMs) have made substantial progress in the past several months, shattering state-of-the-art benchmarks in many domains. This paper investigates LLMs' behavior with respect to gender stereotypes, a known issue for…

计算与语言 · 计算机科学 2023-08-30 Hadas Kotek , Rikker Dockum , David Q. Sun

While advances in fairness and alignment have helped mitigate overt biases exhibited by large language models (LLMs) when explicitly prompted, we hypothesize that these models may still exhibit implicit biases when simulating human…

计算与语言 · 计算机科学 2025-01-30 Yuxuan Li , Hirokazu Shirado , Sauvik Das

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 increasingly used both to make decisions in domains such as health, education and law, and to simulate human behavior. Yet how closely LLMs mirror actual human decision-making remains poorly understood. This…

人工智能 · 计算机科学 2025-11-26 Andrea Cera Palatsi , Samuel Martin-Gutierrez , Ana S. Cardenal , Max Pellert

With the impressive performance in various downstream tasks, large language models (LLMs) have been widely integrated into production pipelines, like recruitment and recommendation systems. A known issue of models trained on natural…

计算与语言 · 计算机科学 2025-01-22 Damin Zhang , Yi Zhang , Geetanjali Bihani , Julia Rayz

Large language models (LLMs) acquire beliefs about gender from training data and can therefore generate text with stereotypical gender attitudes. Prior studies have demonstrated model generations favor one gender or exhibit stereotypes…

计算与语言 · 计算机科学 2024-10-16 Sharon Levy , William D. Adler , Tahilin Sanchez Karver , Mark Dredze , Michelle R. Kaufman

We explore the potential of Large Language Models (LLMs) to replicate human behavior in economic market experiments. Compared to previous studies, we focus on dynamic feedback between LLM agents: the decisions of each LLM impact the market…

综合经济学 · 经济学 2025-05-13 R. Maria del Rio-Chanona , Marco Pangallo , Cars Hommes

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 increasingly being deployed as autonomous agents on behalf of institutions and individuals in economic, political, and social settings that involve negotiation. Yet this trend carries significant risks if…

计算机科学与博弈论 · 计算机科学 2025-12-19 Manuel S. Ríos , Ruben F. Manrique , Nicanor Quijano , Luis F. Giraldo

Large Language Models (LLMs) have been increasingly used in real-world settings, yet their strategic decision-making abilities remain largely unexplored. To fully benefit from the potential of LLMs, it's essential to understand their…

人工智能 · 计算机科学 2024-10-16 Nathan Herr , Fernando Acero , Roberta Raileanu , María Pérez-Ortiz , Zhibin Li

Are large language models (LLMs) biased in favor of communications produced by LLMs, leading to possible antihuman discrimination? Using a classical experimental design inspired by employment discrimination studies, we tested widely used…

计算与语言 · 计算机科学 2025-08-12 Walter Laurito , Benjamin Davis , Peli Grietzer , Tomáš Gavenčiak , Ada Böhm , Jan Kulveit

Large language models (LLMs) exhibit expert-level performance in tasks across a wide range of different domains. Ethical issues raised by LLMs and the need to align future versions makes it important to know how state of the art models…

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