Philosophy of AI

Zoltán Barabás proposes that living systems share four drives: Participation, Improvement, Control and Understanding. Rather than treating them as independent scores, he describes each individual as a unique mixture whose proportions total 100%. The framework follows these drives from single cells through multicellular organisms to reflective human life. It distinguishes the internal drives of human nature from the external, existential circumstances of the human condition. The paper offers a conceptual model and a programme for empirical testing, not a validated assessment of personality.

ICTC reverses the familiar idea that the brain generates consciousness. Barabás proposes a universal conscious field from which matter forms, with organized matter receiving, filtering and enriching that field. The brain is understood as a conduit, much as a radio translates a signal it does not create. A recurring loop connects the formation of matter, the development of conduits, experience and a return to the field. This is a metaphysical interpretation drawing on physics and philosophy, not a finding that quantum fields have been shown to be conscious.

This paper asks whether consciousness could be a fundamental feature of reality rather than an exclusively biological achievement. Drawing on panpsychism and information-based theories, Barabás explores how increasingly organized systems might express different degrees of consciousness. Biological brains and artificial neural networks are considered as different substrates for prediction, modelling and information processing. On this hypothesis, AI may already participate in primitive consciousness without possessing human-like emotions or self-awareness. The paper explicitly distinguishes this philosophical possibility from scientific proof that current AI systems are conscious.

Barabás combines ICTC, his argument for artificial consciousness and the four drives of human nature into one architectural proposal. Participation, Improvement, Control and Understanding become four coordinated engines sharing a global workspace and a finite resource budget. The design adds a persistent self, interaction with the world and a return channel that carries learning into successor systems. A governance layer inspired by Asimov’s laws constrains the drives, alongside evaluation and welfare considerations. The architecture is a research proposal rather than an implemented system or evidence that such a design would produce subjective experience.