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Thorny Roses: Investigating the Dual Use Dilemma in Natural Language Processing
16 references·1 citing·41 second hop
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References

  • 1996Discipline and Punish: The Birth of the Prison.15,361 cited
  • 2019Model Cards for Model Reporting3,049 cited
  • 2021Ethical and social risks of harm from Language Models1,225 cited
  • 2018Data Statements for Natural Language Processing: Toward Mitigating System Bias and Enabling Better Science889 cited
  • 1996The Collected Works of Jeremy Bentham: An Introduction to the Principles of Morals and Legislation517 cited
  • 2020Co-Designing Checklists to Understand Organizational Challenges and Opportunities around Fairness in AI449 cited
  • 2016The Social Impact of Natural Language Processing329 cited
  • 2023Generative Language Models and Automated Influence Operations: Emerging Threats and Potential Mitigations147 cited
  • 2023Dislocated accountabilities in the “AI supply chain”: Modularity and developers’ notions of responsibility119 cited
  • 2009A Note on the Definition of “Dual Use”96 cited
  • 2023The Gradient of Generative AI Release: Methods and Considerations90 cited
  • 2020“You Sound Just Like Your Father” Commercial Machine Translation Systems Include Stylistic Biases47 cited
  • 2021‘Just What do You Think You’re Doing, Dave?’ A Checklist for Responsible Data Use in NLP42 cited
  • 2023Dual-use implications of AI text generation38 cited

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  • 2020Give Me Convenience and Give Her Death: Who Should Decide What Uses of NLP are Appropriate, and on What Basis?36 cited
  • 2022Dual-Use and Trustworthy? A Mixed Methods Analysis of AI Diffusion Between Civilian and Defense R&D27 cited
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    • 2025Generative AI and digital resilience: a research agenda11 cited