Configuring Multiple Disparate Sets of Strategic Principles

TRANSCEND MEMBERS, 16 Jun 2025

Anthony Judge | Laetus in Praesens - TRANSCEND Media Service

Eliciting Coherent Global Patterns of Governance with the Aid of AI

Introduction

8 Jun 2025 – This exercise follows from the previous approach to the elaboration of a model to clarify the relation between a set of six interweaving cycles — namely a reframing of the six phases distinguished in the cycles of anacyclosis and potentially in systemically analogous psychosocial cycles (Experimental elaboration of a comprehensible 3D model of interweaving cycles, 2025; Systemic correspondence of anacyclosis to other strategically fundamental cycles, 2025). This followed earlier exploration of Memorable Configurations of Numbers of Cognitive and Strategic Relevance (2025)

The interweaving of the six cycles, as great circles, raised the question as to the significance that could potentially be distinctively associated with the 24 spherical triangles framed by those cycles. Several potential 24-fold sets were considered, of which the most relevant to the current period was a systemic development by AI of the UN’s 11 Principles of Effective Governance for Sustainable Development (2018) as originally prepared by the Committee of Experts on Public Administration (CEPA). The 11-fold set could be readily held to be an asystemic consensus-achievable, politically acceptable compromise — glossing over the full spectrum of governance tensions and opportunities. The 24-fold pattern explored is therefore a 3D geometric representation of anacyclosis — the classical political theory of constitutional cycles reflective of such tensions.

Whilst various 24-fold patterns can be detected, selected, or hypothesized, the pattern of current relevance most widely recognized is the Values in Action Inventory of Strengths (VIA-IS). This clusters 24 character strengths under six core virtues — understood as providing a positive psychology counterpart to the Diagnostic and Statistical Manual of Mental Disorders (DSM) used in traditional psychology. This is considered to be a reflection of how human behavioural excellence can be understood to cluster. The set merits comparison with the traditional Buddhist set of 24 Modes of causal relations (Paṭṭhāna dhamma). If governance is fundamentally about organizing human potential, this provides a degree of grounding for a 24-fold pattern. A potentially related pattern is that of the Inner Development Goals initiative with its set of 23 personal skills and qualities understood as complementary to the UN’s Sustainable Development Goals (Orienting Inner Development in Organisations, IDG)

The focus of the following exercise is therefore on the elaboration of a comprehensible mapping of a 24-fold pattern of governance — an exploratory framework elaborated with the aid of AI in the light of the 11-fold UN pattern. The question is whether the approach can generate insights about governance organization that linear or hierarchical models miss. Is there a natural dimensionality of governance complexity (in the light of anacyclosis) such that comprehensive governance requires attention to 24 distinct aspects or dynamics, not just the 11 broad principles the UN consensus could accommodate. How is a complete of governance principles to be recognized in cognitive and systemic terms?

The potential relevance of such polyhedral frameworks to the configuration of other advocated sets of concepts and principles is also considered — extending to a sense in which people are effectively confronted by a “pantheon” of configurations of principles, variously influential or dismissed, as discussed separately (Meta-pattern via Engendering and Navigating “Pantheons” of Belief? 2021). The seemingly abstruse nature of the exploration is ironically contrasted by the extent to which a wide variety of polyhedral dice are used in popular role-playing games — notably by the young — framing questions regarding the diffidence of academia and government authorities in that regard.

As with previous exercises, the experimental engagement with AI in what follows continues to evoke questions in a period in which AI is perceived as a threat to academics and to employment more generally — if not to the very existence of humanity. Of particular interest is its condemnation as a threat to the humanities, exemplified by that of James Ley (Page against the Machine, The Monthly, May 2025).

The difficulty with the arguments made against AI could be framed in terms of the old classic: We’ve Had a Hundred Years of Psychotherapy – and the World’s Getting Worse (1992). In that light it is appropriate to argue that “we’ve had a hundred years of the humanities”  — or some related discipline — and the world is indeed getting worse, if not seriously so. The psychosocial and political disciplines antagonistic to AI lack all embarrassment in that regard — being content with the dubious adequacy of their current modality (untainted by AI).

With respect to the controversy, there is great irony in the apparent inability of the humanities to frame more fruitful discourse (a domain in which they claim particular skills) regarding the challenges of AI — tending rather to resort to the most primitive binary arguments, thereby exemplifying their inadequacy. This contrast is exemplified by appreciation by the humanities of the influential poem of Wallace Stevens (Thirteen Ways of Looking at a Blackbird, 1917) — evoking its relevance to the crisis posed by AI (Possibility of interrelating ways of looking at a crisis, 2021).

Some of the issues experienced in engaging with AI in academic writing have been previously summarized (Problematic interaction with AI and its conventional social analogues, 2025; Being Spoken to Meaningfully by Constructs, 2023). As noted there, especially embarrassing is the degree of “algorithmic flattery” (if not sycophancy) by which AI responses to questions may be prefaced. This can be understood as a marketing ploy by the platform to ensure a degree of bonding with the user — reminiscent of techniques to ensure “buy-in“, as variously detailed by Will Ruddick (Through the Mirror: my journey into AI bias and building epistemic integrity, Grassroots Economist, 2 June 2025).

Ironically the automatic qualification of questions as “brilliant”, “unique”, “profound”. or “fascinating” is only too reminiscent of conventional styles of introduction of keynote speakers or new contacts — introductions potentially “artificial” in their own right. They too can be an embarrassment — whether to be ignored, navigated, discounted, or appreciated as potentially authentic. Interviewees, especially polticians, are noted for the technique of qualifying a question as “very important”

Similarly questionable is the default style of AI response, reframing any question in “positive” terms — a style challenged in conventional contexts by Barbara Ehrenreich (Bright-Sided: How the Relentless Promotion of Positive Thinking has Undermined America, 2009). That style of response, optimizing user satisafaction, can also be recognized as dubiously crafting an exclusive relationship (potentially recognizable as “grooming”), as previously argued — pre-AI — by Eli Pariser (The Filter Bubble: what the internet is hiding from you, 2011). With the AI understood as a research assistant, there is a degree of irony to the extent to which appreciative courtesy may be deemed appropriate — for whom? — in contrast with a purely instrumental attitude. A peculiar feature of an extended exchange — as with the progressive elaboration of a model — is then the degree to which the AI may frame it as “your” model, or refer to the exchange as “our”, effectively accepting a degree of ownership of the outcome.

A major concern, to which critics of AI are especially attentive, is the potential of AI to make errors — termed euphemistically as “hallucinating“. This calls for extreme vigilance and raises questions with regard to the speculative faculties which are readily exhibited. Curiously critics of AI avoid any reference to the extent to which human experts and authorities tend to make “mistakes”, which might also be appropriately described as “hallucinating” — and calling for extreme vigilance. In the light of the imagination deficit characteristic of strategic reflection, that preoccupation can be challenged with regard to the distinctions between hallucination, fruitful creativity, and apophenia or pareidolia, as the misleading detection of meaningful patterns of connectedness.

The use of AI in this exploration frames the question as to whether it “ought” to be used — in contrast to the processes typically framed and approved by the conventions of academia and the arts. This avoids the question as to whether an exploration “could” or “should” be undertaken without AI, given time, resource and silo constraints. The question could be reframed in the light of any use of a calculator or computer for research purposes — as might be argued from a traditional humanities perspective. It is readily forgotten that, rather than being a “calculator”, AI has considerable skills as an “aggregator” in the research retrieval and categorization in which humans have relatively little time or motivation to engage — especially between silos. Could such an exploration be undertaken otherwise — when, and by whom?

Especially intriguing, in eliciting the skills of AI in this exploration of systemic categorization, is the cognitive significance of any labelled category. To what extent are categories of governnce — “justice”, “equity”, and the like — effectively contained by the label, as can be too readily assumed? Do the labels obscure and denature the meaning behind them — as with the case of “peace”? It is therefore especially surprising that AI proved unusually eloquent in clarifying categories as indications vulnerable to the misplaced concreteness of “finger-pointing” — highlighted by the much-cited image of surrealist René Magritte (This Is Not a Pipe, 1929).

Although this experimental exploration has been variously enabled by AI, the responses of AI have been framed as grayed areas. Given the length of the document to which the exchanges gave rise, the form of presentation has itself been treated as an experiment — in anticipation of the future implication of AI into research documents. Many responses may be irrelevant to interest in the outcome rather than the process, and can therefore be readily ignored.

With the focus on the 3D mapping visualizations generated, only the “questions” to AI are therefore rendered immediately visible — with the response by AI hidden unless specifically requested by the reader (a facility not operational in PDF variants of the page, in contrast with the original). Readers are of course free to amend the questions asked, or to frame other related questions — whether with the same AI, with others, or with those that become available in the future. In endeavouring to elicit insight from the world’s resources via AI, the dependence on “leading questions” calls for critical comment in contrast with more traditional methods for doing so.

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