The rapid advancements in large language models (LLMs) such as ChatGPT have raised concerns about their potential impact on academic integrity. While initial concerns focused on ChatGPT’s writing capabilities, recent updates have integrated DALL-E 3’s image generation features, extending the risks to visual evidence in biomedical research. Our tests revealed ChatGPT’s nearly barrier-free image generation feature can be used to generate experimental result images, such as blood smears, Western Blot, immunofluorescence and so on. Although the current ability of ChatGPT to generate experimental images is limited, the risk of misuse is evident. This development underscores the need for immediate action. We suggest that AI providers restrict the generation of experimental image, develop tools to detect AI-generated images, and consider adding “invisible watermarks” to the generated images. By implementing these measures, we can better ensure the responsible use of AI technology in academic research and maintain the integrity of scientific evidence.

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ChatGPT 生成逼真实验图像的能力对学术诚信提出了新的挑战

ChatGPT 等大型语言模型 (LLM) 的快速发展引起了人们对其对学术诚信的潜在影响的担忧。虽然最初的担忧集中在 ChatGPT 的写入功能上，但最近的更新集成了 DALL-E 3 的图像生成功能，将风险扩展到生物医学研究中的视觉证据。我们的测试表明，ChatGPT近乎无障碍的图像生成功能可用于生成实验结果图像，例如血涂片、Western Blot、免疫荧光等。尽管 ChatGPT 目前生成实验图像的能力有限，但误用的风险是显而易见的。这一事态发展强调需要立即采取行动。我们建议人工智能提供商限制实验图像的生成，开发检测人工智能生成图像的工具，并考虑在生成的图像中添加“隐形水印”。通过实施这些措施，我们可以更好地确保人工智能技术在学术研究中负责任的使用，并维护科学证据的完整性。