Equipping the next generation: addressing the unmet need for artificial intelligence education at research performing organizations.

IF 9.6 Q1 ETHICS
Jeremy Y Ng, Wid Al-Zahraa Al-Khafaji, David Moher
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Abstract

Background: The integration of generative artificial intelligence (GenAI) tools into higher education is rapidly accelerating, yet the educational ecosystem appears largely unprepared for the scale and speed of adoption. Our recent international survey of over 1,200 university students and postdoctoral fellows in the medical and life sciences found that while more than 80% had used GenAI tools, the vast majority had received no formal training, and many were unaware of any institutional policies governing their use. This gap between adoption and institutional preparedness may pose risks to research integrity if left unaddressed.

Main body: Existing research supports a coordinated, evidence-informed approach to AI education in research performing organizations (RPOs), grounded in principles of research integrity, equity, and critical engagement with technology. First, GenAI literacy must be embedded as a core competency in scientific and clinical education, equipping students to critically evaluate tool outputs, recognize hallucination and bias, and understand the distinction between AI-generated inaccuracy and deliberate research misconduct. Second, traditional frameworks for academic integrity would benefit from re-examination. Today, GenAI tools have fundamentally disrupted established notions of authorship, originality, and plagiarism, and the absence of coherent institutional guidance leaves students and educators navigating these questions without support. Third, RPOs must develop clear, transparent, and context-sensitive policies on GenAI use by embedding responsible AI education into curricula, equipping learners not only to use these tools effectively, but to question, verify, and critique their outputs in ways that uphold scientific standards.

Conclusion: RPOs have an urgent responsibility to move beyond reactive responses and toward proactive strategies that uphold scientific standards, promote equity of access, and prepare the next generation of researchers and clinicians to engage with GenAI responsibly and ethically.

装备下一代:解决研究机构对人工智能教育的未满足需求。
背景:生成式人工智能(GenAI)工具与高等教育的整合正在迅速加速,但教育生态系统似乎在很大程度上没有准备好采用的规模和速度。我们最近对医学和生命科学领域1200多名大学生和博士后进行的国际调查发现,虽然80%以上的人使用过GenAI工具,但绝大多数人没有接受过正式培训,许多人不知道任何管理其使用的制度政策。如果不加以解决,这种采用和机构准备之间的差距可能会对研究的完整性构成风险。主体:现有研究支持在研究执行组织(rpo)中采用协调、循证的人工智能教育方法,以研究诚信、公平和对技术的批判性参与为基础。首先,必须将基因人工智能素养作为一项核心能力纳入科学和临床教育,使学生能够批判性地评估工具输出,识别幻觉和偏见,并理解人工智能产生的不准确性和故意的研究不当行为之间的区别。其次,传统的学术诚信框架将受益于重新审查。今天,GenAI工具已经从根本上破坏了作者身份、原创性和抄袭的既定概念,并且缺乏一致的制度指导,使得学生和教育工作者在没有支持的情况下处理这些问题。第三,rpo必须通过将负责任的人工智能教育纳入课程,制定清晰、透明和环境敏感的GenAI使用政策,使学习者不仅能够有效地使用这些工具,而且能够以坚持科学标准的方式质疑、验证和批评其产出。结论:rpo有迫切的责任超越被动反应,转向积极主动的战略,维护科学标准,促进公平获取,并为下一代研究人员和临床医生做好准备,以负责任和合乎道德的方式参与GenAI。
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