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Using AI to enhance scientific discourse by transforming journals into learning communities.

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Generative AI in scientific publishing can amplify problems or foster vibrant knowledge communities. Journals must transform into AI-supported dialogue platforms, not just repositories, to advance science and benefit society.

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Area of Science:

  • Scholarly communication
  • Scientific publishing
  • Artificial intelligence

Background:

  • Generative AI presents both opportunities and risks for the scientific research ecosystem.
  • Current academic publishing systems face challenges that AI could exacerbate.

Purpose of the Study:

  • To propose a vision for transforming scientific journals into AI-supported knowledge communities.
  • To explore how generative AI can facilitate discourse, collaboration, and knowledge translation.

Main Methods:

  • Viewpoint article analyzing the impact of generative AI on scientific publishing.
  • Discussion of AI's potential to enhance peer review and post-publication discourse.
  • Examination of systemic challenges to AI integration in academia.

Main Results:

  • Generative AI can reinforce harmful practices if journals remain metrics-driven.
  • AI can support transformation by surfacing research connections and enabling multimodal translation.
  • Implementing AI-driven transformation requires coordinated stakeholder action and a focus on core scientific values.

Conclusions:

  • Reimagining journals as AI-supported communities, rather than repositories, is crucial.
  • Systemic change necessitates addressing entrenched academic publishing incentives.
  • Transforming journals can better serve the scientific community and society.