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Epistemic integration and social segregation of AI in neuroscience
Applied Network Science Pub Date : 2024-04-17 , DOI: 10.1007/s41109-024-00618-2
Sylvain Fontaine , Floriana Gargiulo , Michel Dubois , Paola Tubaro

In recent years, Artificial Intelligence (AI) shows a spectacular ability of insertion inside a variety of disciplines which use it for scientific advancements and which sometimes improve it for their conceptual and methodological needs. According to the transverse science framework originally conceived by Shinn and Joerges, AI can be seen as an instrument which is progressively acquiring a universal character through its diffusion across science. In this paper we address empirically one aspect of this diffusion, namely the penetration of AI into a specific field of research. Taking neuroscience as a case study, we conduct a scientometric analysis of the development of AI in this field. We especially study the temporal egocentric citation network around the articles included in this literature, their represented journals and their authors linked together by a temporal collaboration network. We find that AI is driving the constitution of a particular disciplinary ecosystem in neuroscience which is distinct from other subfields, and which is gathering atypical scientific profiles who are coming from neuroscience or outside it. Moreover we observe that this AI community in neuroscience is socially confined in a specific subspace of the neuroscience collaboration network, which also publishes in a small set of dedicated journals that are mostly active in AI research. According to these results, the diffusion of AI in a discipline such as neuroscience didn’t really challenge its disciplinary orientations but rather induced the constitution of a dedicated socio-cognitive environment inside this field.



中文翻译:

神经科学中人工智能的认知整合和社会隔离

近年来,人工智能 (AI) 显示出惊人的插入各种学科的能力,这些学科利用它来促进科学进步,有时还根据其概念和方法的需求改进它。根据 Shinn 和 Joerges 最初构想的横向科学框架,人工智能可以被视为一种工具,通过其在科学领域的传播,逐渐获得普遍性。在本文中,我们从经验上探讨了这种扩散的一个方面,即人工智能对特定研究领域的渗透。我们以神经科学为案例,对该领域人工智能的发展进行科学计量分析。我们特别研究了围绕该文献中包含的文章、其代表期刊及其作者通过时间协作网络连接在一起的时间自我中心引用网络。我们发现人工智能正在推动神经科学中特定学科生态系统的构建,该生态系统与其他子领域不同,并且正在收集来自神经科学或其他领域的非典型科学资料。此外,我们观察到,神经科学领域的人工智能社区在社会上被限制在神经科学协作网络的特定子空间中,该网络也在一小部分主要活跃于人工智能研究的专用期刊上发表文章。根据这些结果,人工智能在神经科学等学科中的传播并没有真正挑战其学科方向,而是诱导了该领域内专门的社会认知环境的构成。

更新日期:2024-04-17
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