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Political biases and inconsistencies in bilingual GPT models—the cases of the U.S. and China
16 references·0 citing·50 second hop
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References

  • 2013How Censorship in China Allows Government Criticism but Silences Collective Expression2,410 cited
  • 2017How the Chinese Government Fabricates Social Media Posts for Strategic Distraction, Not Engaged Argument1,025 cited
  • 2015Sources of Authoritarian Responsiveness: A Field Experiment in China635 cited
  • 2021Persistent Anti-Muslim Bias in Large Language Models476 cited
  • 2023More human than human: measuring ChatGPT political bias326 cited
  • 2021Gender and Representation Bias in GPT-3 Generated Stories287 cited
  • 2024Bias of AI-generated content: an examination of news produced by large language models193 cited
  • 2023The political ideology of conversational AI: Converging evidence on ChatGPT’s pro-environmental, left-libertarian orientation172 cited
  • 2003Perceptions of Danger: The China threat theory156 cited
  • 2023Which Humans?151 cited
  • 2023Leveraging AI for democratic discourse: Chat interventions can improve online political conversations at scale143 cited
  • 2023Large language models show human-like content biases in transmission chain experiments137 cited
  • 2012The ‘China Threat’ through the Lens of US Print Media: 1992–200694 cited
  • 2022Importance and limitations of AI ethics in contemporary society53 cited

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2023
Leverage zones in Responsible AI: towards a systems thinking conceptualization
28 cited
  • 2023Bias of AI-Generated Content: An Examination of News Produced by Large Language Models16 cited
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