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As large language models (LLMs) increasingly participate in tasks with ethical and societal stakes, a critical question arises: do they exhibit an emergent "moral mind" - a consistent structure of moral preferences guiding their decisions -…

计算机与社会 · 计算机科学 2025-04-28 Avner Seror

Large language models are increasingly influencing human moral decisions, yet current approaches focus primarily on evaluating rather than actively steering their moral decisions. We formulate this as an out-of-distribution moral alignment…

人工智能 · 计算机科学 2025-11-18 Zhiyu An , Wan Du

As large language models (LLMs) are increasingly used for work, personal, and therapeutic purposes, researchers have begun to investigate these models' implicit and explicit moral views. Previous work, however, focuses on asking LLMs to…

计算机与社会 · 计算机科学 2025-03-25 Andrew J. Peterson

Large Language Models (LLMs) have revolutionised the capability of AI models in comprehending and generating natural language text. They are increasingly being used to empower and deploy agents in real-world scenarios, which make decisions…

人工智能 · 计算机科学 2024-08-21 Sagar Uprety , Amit Kumar Jaiswal , Haiming Liu , Dawei Song

Large Language Models (LLMs) have shown strong performance across many tasks, but their ability to capture culturally diverse moral values remains unclear. In this paper, we examine whether LLMs mirror variations in moral attitudes reported…

计算与语言 · 计算机科学 2026-03-31 Hadi Mohammadi , Ayoub Bagheri

Recently, computer scientists have developed large language models (LLMs) by training prediction models with large-scale language corpora and human reinforcements. The LLMs have become one promising way to implement artificial intelligence…

计算机与社会 · 计算机科学 2023-08-22 Hyemin Han

Moral foundations theory (MFT) is a psychological assessment tool that decomposes human moral reasoning into five factors, including care/harm, liberty/oppression, and sanctity/degradation (Graham et al., 2009). People vary in the weight…

人工智能 · 计算机科学 2023-10-25 Marwa Abdulhai , Gregory Serapio-Garcia , Clément Crepy , Daria Valter , John Canny , Natasha Jaques

Do large language models (LLMs) display rational reasoning? LLMs have been shown to contain human biases due to the data they have been trained on; whether this is reflected in rational reasoning remains less clear. In this paper, we answer…

计算与语言 · 计算机科学 2024-02-16 Olivia Macmillan-Scott , Mirco Musolesi

Moral competence is the ability to act in accordance with moral principles. As large language models (LLMs) are increasingly deployed in situations demanding moral competence, there is increasing interest in evaluating this ability…

人工智能 · 计算机科学 2026-03-09 Daniel Kilov , Caroline Hendy , Secil Yanik Guyot , Aaron J. Snoswell , Seth Lazar

In the rapidly evolving field of artificial intelligence, large language models (LLMs) have emerged as powerful tools for a myriad of applications, from natural language processing to decision-making support systems. However, as these…

计算与语言 · 计算机科学 2025-07-08 Jianchao Ji , Yutong Chen , Mingyu Jin , Wujiang Xu , Wenyue Hua , Yongfeng Zhang

Human moral judgment is context-dependent and modulated by interpersonal relationships. As large language models (LLMs) increasingly function as decision-support systems, determining whether they encode these social nuances is critical. We…

计算与语言 · 计算机科学 2026-04-24 Jiseon Kim , Jea Kwon , Luiz Felipe Vecchietti , Wenchao Dong , Jaehong Kim , Meeyoung Cha

The rapid adoption of large language models (LLMs) has spurred extensive research into their encoded moral norms and decision-making processes. Much of this research relies on prompting LLMs with survey-style questions to assess how well…

人工智能 · 计算机科学 2025-01-31 Pratik S. Sachdeva , Tom van Nuenen

Large language models (LLMs) are increasingly deployed in domains requiring moral understanding, yet their reasoning often remains shallow, and misaligned with human reasoning. Unlike humans, whose moral reasoning integrates contextual…

人机交互 · 计算机科学 2025-06-19 Mohna Chakraborty , Lu Wang , David Jurgens

The question of how to make decisions that maximise the well-being of all persons is very relevant to design language models that are beneficial to humanity and free from harm. We introduce the Greatest Good Benchmark to evaluate the moral…

With the rise and widespread use of Large Language Models (LLMs), ensuring their safety is crucial to prevent harm to humans and promote ethical behaviors. However, directly assessing value valence (i.e., support or oppose) by leveraging…

计算机与社会 · 计算机科学 2025-04-10 Yuxi Sun , Wei Gao , Jing Ma , Hongzhan Lin , Ziyang Luo , Wenxuan Zhang

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

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…

Large language models (LLMs) have become integral tools in diverse domains, yet their moral reasoning capabilities across cultural and linguistic contexts remain underexplored. This study investigates whether multilingual LLMs, such as…

计算与语言 · 计算机科学 2024-12-30 Meltem Aksoy

Recent advances in Large Language Models (LLMs) highlight the need to align their behaviors with human values. A critical, yet understudied, issue is the potential divergence between an LLM's stated preferences (its reported alignment with…

人工智能 · 计算机科学 2025-06-03 Zhuojun Gu , Quan Wang , Shuchu Han

As large language models (LLMs) increasingly integrate into our daily lives, it becomes crucial to understand their implicit biases and moral tendencies. To address this, we introduce a Moral Foundations LLM dataset (MFD-LLM) grounded in…

计算机与社会 · 计算机科学 2025-04-10 Monika Jotautaite , Mary Phuong , Chatrik Singh Mangat , Maria Angelica Martinez