Integrated information theory

EN Texto em inglês Ainda não há artigo no seu idioma: trecho em inglês.

Integrated information theory (IIT) proposes a mathematical model for the consciousness of a system. It comprises a framework ultimately intended to explain why some physical systems (such as human brains) are conscious, and to be capable of providing a concrete inference about whether any physical system is conscious, to what degree, and what particular experience it has; why they feel the particular way they do in particular states (e.g. why our visual field appears extended when we gaze out at the night sky), and what it would take for other physical systems to be conscious (Are other animals conscious? Might the whole universe be?). The theory inspired the development of new clinical techniques to empirically assess consciousness in unresponsive patients. According to IIT, integrated information (Φ) corresponds to the quantity of consciousness. That is, a system's consciousness (what it is like subjectively) is conjectured to be mathematically described by the system's causal structure (what it is like objectively). Therefore, it should be possible to account for the conscious experience of a physical system by unfolding its complete causal powers. IIT was proposed by neuroscientist Giulio Tononi in 2004. Despite significant interest, IIT remains controversial. In 2023, a number of scholars characterized it as unfalsifiable pseudoscience for lacking sufficient empirical support, a claim reiterated in a 2025 Nature Neuroscience commentary. A survey of researchers in the field found only a small minority fully endorsing the "pseudoscience" label. Other researchers have defended the theory in response.