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How will the state think with ChatGPT? The challenges of generative artificial intelligence for public administrations
14 references·3 citing·49 second hop
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References

  • 2024GPTs are GPTs: Labor market impact potential of LLMs826 cited
  • 2022Human–AI Interactions in Public Sector Decision Making: “Automation Bias” and “Selective Adherence” to Algorithmic Advice462 cited
  • 2023AI as Agency Without Intelligence: on ChatGPT, Large Language Models, and Other Generative Models402 cited
  • 2023More human than human: measuring ChatGPT political bias326 cited
  • 2023Auditing large language models: a three-layered approach287 cited
  • 2023The Political Biases of ChatGPT273 cited
  • 2022Algorithmic Transference: People Overgeneralize Failures of AI in the Government122 cited
  • 2023Prompting meaning: a hermeneutic approach to optimising prompt engineering with ChatGPT112 cited
  • 2016Politiques de l’organisation96 cited
  • 2023ProcessGPT: Transforming Business Process Management with Generative Artificial Intelligence90 cited
  • 2023ChatGPT: deconstructing the debate and moving it forward79 cited
  • 2018Machine justice: Governing security through the bureaucracy of algorithms60 cited
  • 2023ChatGPT for Research and Publication: Opportunities and Challenges51 cited
  • 2018On the Media-political Dimension of Artificial Intelligence44 cited

Cited by

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2025
Integrating Artificial Intelligence into Public Administration: Challenges and Vulnerabilities
76 cited
  • 2025Generative AI in public administration in light of the regulatory awakening in the US and EU11 cited
  • 2025Technological, organizational and environmental determinants influencing the intention to adopt GEN-AI of public sector organizations: a cross-country comparative analysis5 cited