Boyd’s Emergent Information Theory

Independent researcher Daniel Boyd presents Emergent Information Theory (EIT) as a unifying explanation of all biological and technological information systems (Boyd, 2024). In this explanatory framework consciousness is not fundamental, nor even a unique extension to materialism. EIT proposes that all systems that have evolved or been designed to work on the basis of information do so by invoking the causal influence of non-physical entities and processes. Consciousness is thus seen as only one member of a vast family of non-physical phenomena.

Direct evidence for the theory is seen in programmed computers, whose functions are ultimately based on binary values. These binary values are examples of the type of ‘information’ the theory refers to. While associated with a physical state (e.g., a magnetic polarity), these values are not themselves composed of matter or energy and therefore cannot be detected using any physical device. Given only the polarity there is no way to determine whether it is associated with a 0 or a 1. This can only be deduced from the system's design.

As basic units of information, these values are of no use individually. For this reason, they are combined into hierarchical levels of organization—bytes, subroutines, and programs. Each level has its own unique properties that are based on, but do not exist at, the underlying level. This is the type of ‘emergence’ the theory refers to: comparable to the way in which physical reality is stratified from the subatomic to the cosmic scales. Since these non-physical phenomena cannot be located in the three physical dimensions, EIT goes further to conclude that an additional ‘information dimension’ is required to house them.

Like the binary values they are based on, the entities and processes constructed from them are non-physical phenomena and therefore cannot be detected—or be influenced—by any physical device. The trick used to solve this dissociation is coding. By using strict coding protocols, the sequential levels of organization can be constructed by altering the underlying bit value sequences as required. Subsequently, if we want to know what has been created in this way (or the output of some high-level process), we can reconstruct this, using the same coding protocols in reverse, from measurable bit states and visualise the result on a computer screen.

This relationship between the physical and the informational creates a mutual dependency. The informational can only exist because of the specific processes taking place in the material substrate but, causally, what happens in that substrate is determined by high-level informational processes. Just as the movements of the iron atoms in a piston are determined by the operation of the running car engine, so too are the binary values (and therefore necessarily the bit states they are connected to) determined by the operation of the running program. Physical determinism then becomes incomplete: causal closure requires the inclusion of informational phenomena.

Neural networks, both biological and artificial, are also systems with an informational function. EIT therefore proposes that their function is also based on hierarchical emergent phenomena; in this case, constructed from fundamental informational entities associated with neuronal states. The significant difference is that, because function arises through self-organization rather than coded design, there is no way to reconstruct their high-level informational phenomena from measurable neuronal states. This makes empirical demonstration and experimentation problematic.

The evidence is therefore indirect: to begin with, these systems demonstrate complex information functions that necessitate functional emergence comparable to that observed in programmed computers. More convincing is the subjective experience of phenomenal consciousness. Stubbornly brushed off by some materialists as ‘less than real,’ EIT shows how non-physical phenomena such as consciousness are to be expected and need to be acknowledged as equally real as any physical phenomenon. Returning to causality, EIT provides a mechanism whereby such non-physical mental activity can determine the physical activity of the brain’s neurons, thus controlling our expressed behaviour: our choices do not fall under physical determinism.

The association between neural states and fundamental informational entities explains both the neural correlates of consciousness and the dependency of consciousness on brain activity. It also explains why it is not possible to detect or explain consciousness (or non-conscious mental functions) by looking at neural activity. It does not exist at this level of organisation any more than life exists at the level of the atoms from which a living cell is constructed. While EIT does not specifically predict qualia, it does predict organic transitions of equal significance between fundamental informational entities and the high-level phenomena constructed from them (Boyd, 2024).

In summary, EIT bridges the mind-body gap by proposing that the brain creates a “non-material mind” (as defined in an informational context) that is capable of influencing events in the physical body. As such, EIT can be considered as an alternative form of emergent dualism that unifies all biological and technological information systems.