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With the rapid development of artificial intelligence (AI) in recent years, generative AI, represented by ChatGPT, Gemini and Sora has demonstrated its powerful capabilities in many fields. Such AI tools are “penetrating” scientific research as well. The attitudes and reactions of early-career researchers (ECRs), as a new generation of digital natives and those who just start academic career, to this new technology are crucial, as their behaviors and habits may influence the shaping of scientific communication patterns and the development of order in the scientific field in the future. To explore how Chinese ECRs are doing in this regard, longitudinal qualitative interviews were conducted with twenty-two Chinese ECRs. As the results show, Chinese ECRs use AI tools to assist their academic work to some extent, and make the most of it within certain self-ethical constraints. They are also able to recognize its shortcomings and propose ideas for optimization and control of AI development.

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Understanding AI Tools Adoption in Academic Work: Case from Chinese Early-Career Researchers

  • 会议论文

  • 发表日期：

    2025年

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  • Jie Xu,
  • Chen He

摘要

With the rapid development of artificial intelligence (AI) in recent years, generative AI, represented by ChatGPT, Gemini and Sora has demonstrated its powerful capabilities in many fields. Such AI tools are “penetrating” scientific research as well. The attitudes and reactions of early-career researchers (ECRs), as a new generation of digital natives and those who just start academic career, to this new technology are crucial, as their behaviors and habits may influence the shaping of scientific communication patterns and the development of order in the scientific field in the future. To explore how Chinese ECRs are doing in this regard, longitudinal qualitative interviews were conducted with twenty-two Chinese ECRs. As the results show, Chinese ECRs use AI tools to assist their academic work to some extent, and make the most of it within certain self-ethical constraints. They are also able to recognize its shortcomings and propose ideas for optimization and control of AI development.