Deconstructing the ethics of large language models from long-standing issues to new-emerging dilemmas: a survey

Chengyuan Deng, Yiqun Duan, Xin Jin, Heng Chang, Yijun Tian, Han Liu, Yichen Wang, kuofeng Gao, Henry Peng Zou, Yiqiao jin, Yijia Xiao, Shenghao Wu, Zongxing Xie, Weimin Lyu, Sihong He, Lu Cheng, Haohan Wang, Jun Zhuang
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Abstract

Large Language Models (LLMs) have achieved unparalleled success across diverse language modeling tasks in recent years. However, this progress has also intensified ethical concerns, impacting the deployment of LLMs in everyday contexts. This paper provides a comprehensive survey of ethical challenges associated with LLMs, from longstanding issues such as copyright infringement, systematic bias, and data privacy, to emerging problems like truthfulness and social norms. We critically analyze existing research aimed at understanding, examining, and mitigating these ethical risks. Our survey underscores integrating ethical standards and societal values into the development of LLMs, thereby guiding the development of responsible and ethically aligned language models.

从长期存在的问题到新出现的困境解构大型语言模型的伦理:一项调查
近年来,大型语言模型(llm)在各种语言建模任务中取得了无与伦比的成功。然而,这一进展也加剧了伦理问题,影响了法学硕士在日常环境中的部署。本文提供了与法学硕士相关的道德挑战的全面调查,从长期存在的问题,如版权侵权,系统性偏见和数据隐私,到新出现的问题,如真实性和社会规范。我们批判性地分析旨在理解、检查和减轻这些伦理风险的现有研究。我们的调查强调将道德标准和社会价值观整合到法学硕士的发展中,从而指导负责任和道德一致的语言模型的发展。
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