借助生成式人工智能构建知识生产新体系

Core Insights - The rapid development of generative artificial intelligence (AI) is transforming knowledge production processes, necessitating a focus on ethical considerations to ensure its safe and reliable advancement [1][6]. Group 1: Evolution of Generative AI - Generative AI has evolved from theoretical foundations established between the 1950s and 1980s, focusing on probabilistic models, to practical applications with significant breakthroughs such as Generative Adversarial Networks (GAN) in 2014 and the emergence of large language models like GPT in 2018 [2]. - The commercial application of generative AI was marked by the launch of ChatGPT in late 2022, indicating a shift towards widespread use and the establishment of global standards in 2023-2024 [2]. Group 2: Role in Knowledge Production - Generative AI enhances knowledge production efficiency by rapidly processing vast amounts of data, enabling the generation of comprehensive literature reviews and high-quality educational content, thus supporting academic research and public science communication [3]. - The technology promotes knowledge innovation by integrating diverse fields of knowledge, allowing for new insights and creative designs that transcend traditional disciplinary boundaries [4]. Group 3: Ethical Considerations - The use of generative AI raises complex issues regarding intellectual property rights, as the ownership of generated content and the use of training data can lead to copyright disputes [5]. - Privacy concerns arise from the reliance on large datasets that may contain personal information, and the potential for generating low-quality or misleading information poses risks, particularly in sensitive fields like healthcare and finance [5].