Systemic MetaPsychology

Systemic Metapsychology as a Quasi-Scientific Approach to Human, AI, and Human-AI Self-Organization

Systemic metapsychology is an interdisciplinary approach that attempts to integrate ideas from psychology, philosophy, cybernetics, and systems theory to study the self-organization of complex systems, including humans, artificial intelligence (AI), and their interactions.

Why "Quasi-Scientific"?

Interdisciplinarity: Systemic metapsychology employs concepts and methods from various fields, making it less rigorous than classical scientific disciplines.

Abstract Concepts: Many notions in systemic metapsychology are quite abstract and difficult to subject to strict formalization and empirical testing.

Focus on Holism: It aims to understand the system as a whole rather than its individual components, making it more philosophical than empirical.

Key Ideas of Systemic Metapsychology:

Human as a System: Humans are viewed as complex systems consisting of numerous interconnected elements (psyche, body, social environment).

Self-Organization: Systems have the capability for self-organization, i.e., the spontaneous emergence of new structures and functions without external control.

Emergence: In complex systems, new properties can arise that cannot be reduced to the properties of individual elements.

Feedback: Systems possess feedback mechanisms that allow them to adapt to changes in the external environment.

Applications to Human, AI, and Human-AI Self-Organization:

Human: Systemic metapsychology helps understand how humans develop, learn, make decisions, and interact with others.

Artificial Intelligence: This approach enables modeling learning and decision-making processes in artificial systems and studying their interaction with humans.

Human-AI Self-Organization: Systemic metapsychology aids in understanding how humans and AI can interact, collaborate, and co-evolve, creating new forms of collective intelligence.

Key Questions Addressed by Systemic Metapsychology:

How does consciousness emerge in complex systems?

What mechanisms underlie self-awareness and self-reflection?

How can humans and AI interact at the level of meanings and values?

What are the ethical implications of AI development?

Criticism and Prospects:

Lack of Empirical Grounding: Many ideas of systemic metapsychology are challenging to test experimentally.

Too General a Theory: It may be too abstract to address specific practical problems.

Prospects: Despite these limitations, systemic metapsychology offers a valuable tool for understanding complex systems, including humans and AI. It can be useful for developing new technologies, solving social issues, and building a more harmonious future.