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Adaptive Relational Zoning: a CAS Framework for Modelling Strategic Social Interaction

13 Juni 2025   13:09 Diperbarui: 13 Juni 2025   19:29 370
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Contextual wisdom
Meta-reflection
Iterative alignment between means and evolving ends
This does not excuse toxic behavior---but it frames ethics as a navigation problem, not a purity contest.

4. Application in Leadership, Therapy, and AI Mediation

Understanding the ethical contours of manipulation is especially urgent in domains like:

Leadership, where emotional framing, ambiguity tolerance, and strategic opacity are tools---but can easily cross into gaslighting or coercion.
Therapeutic relationships, where the therapist's guidance may steer behavior, but must never colonize autonomy.
AI-mediated environments, where algorithmic nudges or data-driven behavioral shaping could be either supportive or dangerously manipulative.
By explicitly encoding zone awareness and variable transparency into these systems, institutions and individuals can foster ethical reflexivity even within complex, shifting dynamics.

5. Conclusion: Toward Ethical Precision, Not Ethical Paralysis

The Six-Zone Model does not prescribe universal rules---it provides a scaffold for ethical navigation in relational uncertainty. It equips individuals, leaders, and institutions with tools to evaluate influence not just by effect, but by context, reversibility, and strategic symmetry.

Ethical precision in this model is not about never manipulating.
 It is about knowing when, why, and how---and being accountable for the outcome.

D. Implications for AI--Human Interaction Models

As artificial intelligence systems increasingly mediate, augment, or even participate in human relationships, the ethical and strategic insights from the Six-Zone Relational Model offer a compelling blueprint for the design of more adaptive, context-sensitive, and ethically informed AI-human interaction frameworks.

1. From Static to Adaptive Relational Modeling

Most current AI systems, particularly in social robotics, recommendation engines, or virtual assistants, operate on static user profiles or linear decision trees. These approaches often fail to capture the temporal evolution, emotional fluctuations, and strategic ambiguity that define real-world human relations.

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