Summary of Deconstructing the Ethics Of Large Language Models From Long-standing Issues to New-emerging Dilemmas: a Survey, by Chengyuan Deng et al.
Deconstructing The Ethics of Large Language Models from Long-standing Issues to New-emerging Dilemmas: A Survey
by 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
First submitted to arxiv on: 8 Jun 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Computers and Society (cs.CY); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary In this paper, researchers provide a comprehensive review of the ethical challenges associated with Large Language Models (LLMs), which have seen unprecedented success in various natural language processing tasks. The survey highlights concerns around copyright infringement, systematic bias, data privacy, truthfulness, and social norms. It also analyzes existing research aimed at addressing these issues and underscores the importance of integrating ethical standards and societal values into LLM development to create responsible and ethically aligned models. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper looks at big language models that are really good at doing lots of things with language. Right now, people are worried about how these models might be used in everyday life because they can cause problems like copying other people’s work, being unfair or biased, sharing private information, telling lies, and even influencing what we think is socially acceptable. |
Keywords
» Artificial intelligence » Natural language processing
