复杂性范式:走向分析社会系统和社会问题的模型

Artur Parreira, Ana Lorga Silva
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引用次数: 0

摘要

本文提出了复杂性范式作为分析行为科学问题的一种创新推理方法。它开始解释复杂推理范式的主要作者的贡献:Gödel, Prigogine和Morin。它们为复杂系统和问题的分析和评估模型(ACSIP模型)提供了基础。解释了模型的四个假设,强调了模型的主要假设——认知操作水平是系统复杂性的最重要因素;然后,为了理解它,分析的认知水平必须至少等于所分析的系统或问题的认知水平。在文章的第二部分,将ACSIP模型应用于分析联合国20/30议程中的可持续发展目标9,展示了在复杂性推理模型的指导下对一个复杂问题的分析。随后,提出了一项实证研究,以验证模型第四个假设的假设。研究结果证实了一个假设:一个群体对信息的使用与权力(权威)的使用成反比。这些结果使我们得出结论,复杂推理范式是在科学分析和解决具体社会问题以及面对人工智能系统带来的复杂挑战时获得协同结果的有希望的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
THE COMPLEXITY PARADIGM: TOWARDS A MODEL FOR THE ANALYSIS OF SOCIAL SYSTEMS AND PROBLEMS
The article proposes the complexity paradigm as an innovative reasoning for analyzing problems in behavioral sciences. It begins to explain the contributions of the major authors of the complex reasoning paradigm: Gödel, Prigogine and Morin. They offer the basis to a model of analysis and assessment of complex systems and problems (ACSIP Model). The four postulates of the Model are explained, emphasizing the principal hypothesis of the Model – the level of cognitive operations is the most important factor of complexity of a system; then to understand it, the cognitive level of analysis must be at minimum equal to that of the system or the problem under analysis. In the second part the article, an illustrative application of the ACSIP Model is applied to the analysis of the SDG 9 from the UN 20/30 agenda, showing the analysis of a complex problem, guided by the complexity reasoning model. Following that, an empirical research is presented, to verify the hypothesis underlying the fourth postulate of the model. The results confirm the hypothesis: the use of information by a group is inversely proportional to the use of power (authority).  These results allow us to conclude that the complex reasoning paradigm is a promising tool to obtain synergic results in the scientific analysis and resolution of concrete social problems and to face the complex challenges brought by artificial intelligence systems.
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