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<p>Various belief measurement scales, such as the beliefs and values scale, the degree of believing in God, and the AI attitude scale, have been developed to assess belief structures across psychology, cognitive science, and sociology. However, a unified belief measurement scale encompassing psychology, cognitive science, neuroscience, and sociology is yet to be achieved. Assuming such a unified scale is possible, we theoretically analyze the stability of an individual’s social network through the minimum required pairs of belief systems. We examine the process behind altering existing beliefs and forming new ones, with a specific focus on the stability of groups of approximately 150 members-referred to as Dunbar’s number. Our findings reveal that at least 5,588 mutually non-conflicting belief systems are necessary for stability of an individual’s social network. Additionally, we introduce new perspectives on how IoT devices and personal AI agents influence group stability, affecting both strong and weak interpersonal relationships. For the first time, we derive a formula to quantify the maximum number of IoT devices or personal AI agents an individual can manage before network instability occurs. Furthermore, we examine the impact of a member’s departure or death on group cohesion and identify the threshold of belief instability that leads to group fragmentation. Ultimately, these insights aim to inform the development of machine learning tools for improving both social and artificial intelligence systems. In this paper, the term ‘agent’ refers to either a human individual or an AI expert system, depending on the context.</p>

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Balance in belief systems to shape group stability: an approach from evolutionary biology, the internet of things, and artificial intelligence

  • 期刊论文

  • 发表日期：

    2025年11月25日

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  • Santanu Acharjee,
  • Amlanjyoti Oza

摘要

Various belief measurement scales, such as the beliefs and values scale, the degree of believing in God, and the AI attitude scale, have been developed to assess belief structures across psychology, cognitive science, and sociology. However, a unified belief measurement scale encompassing psychology, cognitive science, neuroscience, and sociology is yet to be achieved. Assuming such a unified scale is possible, we theoretically analyze the stability of an individual’s social network through the minimum required pairs of belief systems. We examine the process behind altering existing beliefs and forming new ones, with a specific focus on the stability of groups of approximately 150 members-referred to as Dunbar’s number. Our findings reveal that at least 5,588 mutually non-conflicting belief systems are necessary for stability of an individual’s social network. Additionally, we introduce new perspectives on how IoT devices and personal AI agents influence group stability, affecting both strong and weak interpersonal relationships. For the first time, we derive a formula to quantify the maximum number of IoT devices or personal AI agents an individual can manage before network instability occurs. Furthermore, we examine the impact of a member’s departure or death on group cohesion and identify the threshold of belief instability that leads to group fragmentation. Ultimately, these insights aim to inform the development of machine learning tools for improving both social and artificial intelligence systems. In this paper, the term ‘agent’ refers to either a human individual or an AI expert system, depending on the context.