Mathematical Modelling of Silo Thinking in Interdisciplinary Contexts

AI perspectives on balancing integration and identity faced by strategic complexity

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Introduction

The discipline of mathematics, notably through the complexity sciences, is widely upheld as vital to insightful understanding of complexity. Governance of global society is only too obviously faced with complexity -- as is frequently stated. Various world models have been developed to clarify the challenges, most recently with respect to climate change and the pandemic. The use of such models has been variously called into question (Misleading Modelling of Global Crises, 2021).

A question of interest is whether there are mathematical insights of great potential relevance which are a challenge to comprehension by those who might usefully apply them (Engaging with Elusive Connectivity and Coherence, 2018). It is therefore appropriate to inquire about the mathematical complexity of potential keys to strategic responses to the crises of the world. Of further interest is how these resources are presented and rendered comprehensible -- given the inherent constraints of complexity (Uncritical Strategic Dependence on Little-known Metrics, 2009). The latter focused on the risks associated with the Gaussian copula fundamental to the subprime mortgage crisis and with the Kaya identity fundamental to assessment of climate change.

The science on which global strategy claims to be dependent is held to be beholden fundamentally to mathematics -- as the discipline recognized as the first among equals (primis inter pares). There is therefore a case for exploring the relevance of mathematics to strategic articulation and comprehension. Provocatively it may be asked: Is the House of Mathematics in Order? (2000) and how is this determined?

Given its inherent complexity as a discipline, it may be asked whether adequate consideration is given to the organization of mathematics -- in the light of its powerful insights into possibilities of multidimensional organization, and why they might be neglected (Higher Dimensional Reframing of Unity and Memorable Identity, 2024; Neglect of Higher Dimensional Solutions to Territorial Conflicts, 2024; Â And When the Bombing Stops? Territorial conflict as a challenge to mathematicians, 2000).

Why, for example, are 64 branches of mathematics distinguished by a seemingly rigid alphanumerical Mathematics Subject Classification -- and how might they be configured more beneficially otherwise (Configuring the 64 subjects of mathematics as a 64-edged drilled truncated cube, 2021). Where is there any indication of the relative relevance of each branch to the strategic challenge of the times? Or is that question inherently irrelevant?

This exercise is undertaken in the spirit of the annual questions by the Edge Foundation. These have included responses to: What scientific term or concept ought to be more widely known (2017), What scientific concept would improve everybody's cognitive toolkit (2011). A similar initiative is that of the American Association for the Advancement of Science in identifying 125 issues for science (What Don't We Know, Science, 1 July 2005).

Arguments are frequently highlighted concerning the vital role of interdisciplinary approaches. It is however evident that development of these possibilities is constrained by what is deprecated as "silo thinking" -- a failure to "connect the dots" and its relation to "joined up thinking". Given the increasing potential of AI in handling complexity, it is therefore appropriate to explore how AI might reframe silo thinking -- and other forms of "resistance" -- in relation to interdisciplinarity and its strategic role.

As with several earlier exercises of some relevance to this question, the following exploration makes extensive use of AI in the form of ChatGPT (and specifically its Scholar.ai plugin). Reservations regarding such use have been previously noted, both with regard to the questionable verbosity and style of responses, and what could be termed a degree of "algorithmic enthusiasm" for the relevance of the questions posed (Eliciting integrative insight via ChatGPT, 2024).

In this transitional period of adjustment to the potential of AI facilities, the following exchange constitutes an experiment in its own right -- potentially reframing the current relevance of information derived and presented in this way, as discussed separately (Being Spoken to Meaningfully by Constructs, 2023).

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