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边界的转移,扩展的思维:环境技术与扩展的稳态控制。

Shifting boundaries, extended minds: ambient technology and extended allostatic control.

作者信息

White Ben, Clark Andy, Guènin-Carlut Avel, Constant Axel, Di Paolo Laura Desirée

机构信息

School of Media, Arts and Humanities, University of Sussex, Brighton, UK.

School of Engineering and Informatics, University of Sussex, Brighton, UK.

出版信息

Synthese. 2025;205(2):81. doi: 10.1007/s11229-025-04924-9. Epub 2025 Feb 6.

Abstract

This article applies the thesis of the extended mind to ambient smart environments. These systems are characterised by an environment, such as a home or classroom, infused with multiple, highly networked streams of smart technology working in the background, learning about the user and operating without an explicit interface or any intentional sensorimotor engagement from the user. We analyse these systems in the context of work on the "classical" extended mind, characterised by conditions such as "trust and glue" and phenomenal transparency, and find that these conditions are ill-suited to describing our engagement with ambient smart environments. We then draw from the active inference framework, a theory of brain function which casts cognition as a process of embodied uncertainty minimisation, to develop a version of the extended mind grounded in a process ontology, where the boundaries of mind are understood to be multiple and always shifting. Given this more fluid account of the extended mind, we argue that ambient smart environments should be thought of as extended allostatic control systems, operating more or less invisibly to support an agent's biological capacity for minimising uncertainty over multiple, interlocking timescales. Thus, we account for the functionality of ambient smart environments as extended systems, and in so doing, utilise a markedly different version of the classical thesis of extended mind.

摘要

本文将扩展心智理论应用于环境智能系统。这些系统的特点是,诸如家庭或教室之类的环境中充斥着多个高度联网的智能技术流,它们在后台运行,了解用户情况且无需用户进行明确的界面操作或任何有意的感觉运动参与。我们在以“信任与联结”及现象透明性等条件为特征的“经典”扩展心智研究背景下分析这些系统,发现这些条件并不适合描述我们与环境智能系统的互动。然后,我们借鉴主动推理框架(一种将认知视为身体不确定性最小化过程的脑功能理论),来发展一种基于过程本体论的扩展心智版本,在这个版本中,心智的边界被理解为多重且不断变化的。基于这种对扩展心智更灵活的解释,我们认为环境智能系统应被视为扩展的稳态控制系统,它们或多或少在无形之中运行,以支持个体在多个相互关联的时间尺度上最小化不确定性的生物能力。因此,我们将环境智能系统的功能解释为扩展系统,并在此过程中运用了与经典扩展心智理论截然不同的版本。

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本文引用的文献

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