• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

相似文献

1
Attributions toward artificial agents in a modified Moral Turing Test.在改良的道德图灵测试中对人工代理的归因。
Sci Rep. 2024 Apr 30;14(1):8458. doi: 10.1038/s41598-024-58087-7.
2
Psychological and Brain Responses to Artificial Intelligence's Violation of Community Ethics.人工智能违反社区伦理时的心理和大脑反应。
Cyberpsychol Behav Soc Netw. 2024 Aug;27(8):562-570. doi: 10.1089/cyber.2023.0524. Epub 2024 May 17.
3
Perceptions of artificial intelligence system's aptitude to judge morality and competence amidst the rise of Chatbots.在聊天机器人兴起的背景下,对人工智能系统判断道德和能力的资质的认知。
Cogn Res Princ Implic. 2024 Jul 18;9(1):47. doi: 10.1186/s41235-024-00573-7.
4
Toward Implementing the ADC Model of Moral Judgment in Autonomous Vehicles.迈向自动驾驶汽车中道德判断的 ADC 模型的实现。
Sci Eng Ethics. 2020 Oct;26(5):2461-2472. doi: 10.1007/s11948-020-00242-0.
5
AI Moral Enhancement: Upgrading the Socio-Technical System of Moral Engagement.人工智能道德增强:升级道德参与的社会技术系统。
Sci Eng Ethics. 2023 Mar 23;29(2):11. doi: 10.1007/s11948-023-00428-2.
6
The Puzzle of Evaluating Moral Cognition in Artificial Agents.人工智能中道德认知评估的难题。
Cogn Sci. 2023 Aug;47(8):e13315. doi: 10.1111/cogs.13315.
7
The Moral Psychology of Artificial Intelligence.人工智能的道德心理学。
Annu Rev Psychol. 2024 Jan 18;75:653-675. doi: 10.1146/annurev-psych-030123-113559. Epub 2023 Sep 18.
8
The importance of moral construal: moral versus non-moral construal elicits faster, more extreme, universal evaluations of the same actions.道德构建的重要性:道德构建与非道德构建会引发对相同行为更快、更极端、更普遍的评价。
PLoS One. 2012;7(11):e48693. doi: 10.1371/journal.pone.0048693. Epub 2012 Nov 28.
9
Artificial Moral Responsibility: How We Can and Cannot Hold Machines Responsible.人工道德责任:我们能够且不能如何让机器负责。
Camb Q Healthc Ethics. 2021 Jul;30(3):435-447. doi: 10.1017/S0963180120000985.
10
How deep is AI's love? Understanding relational AI.人工智能的爱有多深?理解关系型人工智能。
Behav Brain Sci. 2023 Apr 5;46:e33. doi: 10.1017/S0140525X22001704.

引用本文的文献

1
Large language models show amplified cognitive biases in moral decision-making.大语言模型在道德决策中表现出放大的认知偏差。
Proc Natl Acad Sci U S A. 2025 Jun 24;122(25):e2412015122. doi: 10.1073/pnas.2412015122. Epub 2025 Jun 20.
2
AI language model rivals expert ethicist in perceived moral expertise.在被感知的道德专业知识方面,人工智能语言模型可与专家伦理学家相媲美。
Sci Rep. 2025 Feb 3;15(1):4084. doi: 10.1038/s41598-025-86510-0.
3
Disagreements in Medical Ethics Question Answering Between Large Language Models and Physicians.大型语言模型与医生在医学伦理问答方面的分歧
Res Sq. 2024 Nov 15:rs.3.rs-5382879. doi: 10.21203/rs.3.rs-5382879/v1.
4
Augmenting intensive care unit nursing practice with generative AI: A formative study of diagnostic synergies using simulation-based clinical cases.利用生成式人工智能增强重症监护病房护理实践:一项基于模拟临床病例的诊断协同形成性研究。
J Clin Nurs. 2024 Aug 5. doi: 10.1111/jocn.17384.

本文引用的文献

1
Putting ChatGPT's Medical Advice to the (Turing) Test: Survey Study.对ChatGPT的医学建议进行(图灵)测试:调查研究。
JMIR Med Educ. 2023 Jul 10;9:e46939. doi: 10.2196/46939.
2
AI for identifying social norm violation.人工智能用于识别社会规范违反行为。
Sci Rep. 2023 May 19;13(1):8103. doi: 10.1038/s41598-023-35350-x.
3
Can AI language models replace human participants?人工智能语言模型能否替代人类参与者?
Trends Cogn Sci. 2023 Jul;27(7):597-600. doi: 10.1016/j.tics.2023.04.008. Epub 2023 May 10.
4
Comparing Physician and Artificial Intelligence Chatbot Responses to Patient Questions Posted to a Public Social Media Forum.比较医生和人工智能聊天机器人对发布在公共社交媒体论坛上的患者问题的回复。
JAMA Intern Med. 2023 Jun 1;183(6):589-596. doi: 10.1001/jamainternmed.2023.1838.
5
ChatGPT's inconsistent moral advice influences users' judgment.ChatGPT 给出的前后不一致的道德建议会影响用户的判断。
Sci Rep. 2023 Apr 6;13(1):4569. doi: 10.1038/s41598-023-31341-0.
6
Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models.ChatGPT在美国医师执照考试中的表现:使用大语言模型进行人工智能辅助医学教育的潜力。
PLOS Digit Health. 2023 Feb 9;2(2):e0000198. doi: 10.1371/journal.pdig.0000198. eCollection 2023 Feb.
7
Large Language Models and the Reverse Turing Test.大语言模型与反向图灵测试。
Neural Comput. 2023 Feb 17;35(3):309-342. doi: 10.1162/neco_a_01563.
8
On the realness of people who do not exist: The social processing of artificial faces.关于不存在之人的真实性:人工面孔的社会加工
iScience. 2022 Dec 7;25(12):105441. doi: 10.1016/j.isci.2022.105441. eCollection 2022 Dec 22.
9
Human- versus Artificial Intelligence.人类与人工智能
Front Artif Intell. 2021 Mar 25;4:622364. doi: 10.3389/frai.2021.622364. eCollection 2021.
10
The limits of machine intelligence: Despite progress in machine intelligence, artificial general intelligence is still a major challenge.机器智能的局限性:尽管机器智能取得了进展,但通用人工智能仍然是一个重大挑战。
EMBO Rep. 2019 Oct 4;20(10):e49177. doi: 10.15252/embr.201949177. Epub 2019 Sep 18.

在改良的道德图灵测试中对人工代理的归因。

Attributions toward artificial agents in a modified Moral Turing Test.

机构信息

Department of Psychology, Georgia State University, Atlanta, GA, USA.

Department of Philosophy, Georgia State University, Atlanta, GA, USA.

出版信息

Sci Rep. 2024 Apr 30;14(1):8458. doi: 10.1038/s41598-024-58087-7.

DOI:10.1038/s41598-024-58087-7
PMID:38688951
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11061136/
Abstract

Advances in artificial intelligence (AI) raise important questions about whether people view moral evaluations by AI systems similarly to human-generated moral evaluations. We conducted a modified Moral Turing Test (m-MTT), inspired by Allen et al. (Exp Theor Artif Intell 352:24-28, 2004) proposal, by asking people to distinguish real human moral evaluations from those made by a popular advanced AI language model: GPT-4. A representative sample of 299 U.S. adults first rated the quality of moral evaluations when blinded to their source. Remarkably, they rated the AI's moral reasoning as superior in quality to humans' along almost all dimensions, including virtuousness, intelligence, and trustworthiness, consistent with passing what Allen and colleagues call the comparative MTT. Next, when tasked with identifying the source of each evaluation (human or computer), people performed significantly above chance levels. Although the AI did not pass this test, this was not because of its inferior moral reasoning but, potentially, its perceived superiority, among other possible explanations. The emergence of language models capable of producing moral responses perceived as superior in quality to humans' raises concerns that people may uncritically accept potentially harmful moral guidance from AI. This possibility highlights the need for safeguards around generative language models in matters of morality.

摘要

人工智能(AI)的进步提出了一个重要问题,即人们是否会像对待人类生成的道德评价一样,看待 AI 系统的道德评价。我们借鉴了 Allen 等人(Exp Theor Artif Intell 352:24-28, 2004)的提议,进行了改良后的道德图灵测试(m-MTT),要求人们区分真实的人类道德评价和广受欢迎的先进 AI 语言模型 GPT-4 所做出的道德评价。我们从美国随机抽取了 299 名成年人作为样本,在不知道评价来源的情况下,首先对道德评价的质量进行了评分。令人惊讶的是,他们几乎在所有维度上都认为 AI 的道德推理质量优于人类,这与 Allen 等人所称的比较性 MTT 相符。接下来,当被要求识别每个评价的来源(人类或计算机)时,人们的表现明显高于随机水平。尽管 AI 没有通过这项测试,但这并不是因为它的道德推理能力较差,而是可能因为它在其他可能的解释中被认为具有优越性。能够生成被认为在质量上优于人类的道德反应的语言模型的出现,引发了人们对人们可能会不加批判地接受 AI 提供的潜在有害道德指导的担忧。这种可能性凸显了在涉及道德问题时,对生成性语言模型进行保障措施的必要性。