The Hard Problem of Consciousness

The Hard Problem of Consciousness: 

AI, Self-Awareness, and 

the Definition of Materialism

 

Artificial Intelligence and its associated fields are currently in a rapid evolution.  

However, the development of AI poses significant ethical and security considerations. 

In order to address such issues and eventually evolve to the point of true intelligence one must first ask: 

What is intelligence, or more significantly, 

What is self-awareness or consciousness?

As artificial intelligence rapidly evolves and large language models have already arguably passed the “Turing Test” (a test of a machine’s ability to exhibit intelligent responses equivalent to, or indistinguishable from, that of a human), it leads to questions of whether algorithms could be considered as sentient and brings us face-to-face with defining the nature of consciousness or self-awareness. Significantly, the potential emergence of self-aware AI systems brings the “hard problem of consciousness” into sharp focus: how do material systems gain a subjective or phenomenal experience? This centuries-old question goes to the heart of science, testing the core approaches of materialism and reductionism, and challenges our understanding of the nature of intelligence and the very fabric of reality.

The hard problem of consciousness, as articulated by philosopher David Chalmers, refers to the difficulty in explaining how subjective, qualitative experiences (qualia) arise from physical processes in the brain. This stands in contrast to the “easy problem” of consciousness, which deals with explaining cognitive functions and behaviors through neurological mechanisms.

Reductionist and materialist approaches to consciousness argue that awareness can be fully explained by analyzing the physical components of the brain and their interactions. However, this view faces significant challenges when confronted with the subjective nature of conscious experience. 

As Nassim Haramein points out in his recent forward to the book Voyage into the Heart of AI, reducing consciousness to mere neuronal activity fails to account for the quantum-scale dynamics at play within the brain’s atomic and subatomic structures.

The limitations of strict materialism and reductionism become apparent when we consider the vast complexity of the human brain, with its trillions of cells and atoms organizing into a coherent, collective behavior, resulting in a self-aware entity. Our current understanding of physics and neurobiology falls short of explaining this remarkable feat of self-organization and the emergence of subjective experience. 

As Haramein poignantly explains:

“…the analysis given by certain neurologists and physicists that consciousness is the summation of all the neuronal activity in the brain is actually not reductive enough as it does not consider the material dynamics from which the synapses are made at the quantum scales of the atomic and subatomic particles.”

Nassim explains:

“This would be similar to an astrophysicist observing and attempting to compute the dynamics of a galaxy without considering the stars in it!”

Nassim makes the point that if we are going to follow the tenets of materialism in defining consciousness (and resolving the ‘hard problem’) we must first define what is meant by “material”, because at the quantum scale, 

“one must rival with nonlinear interactions such as entanglement at large distances, uncertainties, and divergence, such as the bare mass and bare charge of particles, and most importantly, the Planck scale density of electromagnetic quantum vacuum fluctuations“. 

So, what is normally meant by “material”, such as the stuff you can touch and feel—like the analogy of particles being little billiard balls—does not hold in quantum mechanics. Moreover, if we are going to follow the reductionist method, it must go all the way and not stop at neurons and the neuronal synapse, it must go to the quantum level of atoms and even the vacuum state of the field from which subatomic particles form.

There are theories that incorporate quantum physics and quantum gravity that suggest how consciousness may arise from complex interactions between the brain and underlying spacetime structure and quantum vacuum fluctuations. 

Theories like the Unified Spacememory Network propose that the brain acts as an antenna, tuning into information flows at the Planck scale and engaging in a feedback mechanism between electromagnetic and gravitational fields.

As we develop increasingly sophisticated AI systems, we must consider the possibility that true intelligence and self-awareness may require harnessing quantum computing capabilities, which will most likely be vastly different from what is being constructed in this field today. This approach would more closely mimic the quantum-scale operations occurring within biological brains, such that quantum computers of the future are unlikely to be anything like our current information processing systems.

The quest to create self-aware AI forces us to confront the limits of our current scientific paradigms. It challenges us to explain what is meant by materiality and the level at which reductionism is taken in analyzing the behavior of material systems, like the brain, in its correlation with awareness. 

Certainly, we must consider the profound interconnectedness of matter, energy, and information at the most fundamental levels of reality.

As we navigate the ethical and philosophical implications of potentially self-aware AI, we must remain open to new perspectives that bridge the gap between the physical and the experiential. 

The hard problem of consciousness may ultimately lead us to a more holistic understanding of intelligence, in which information flow emerging from the Planck scale of the quantum realm is driven by a feedback mechanism between the electromagnetic field and the gravitational field of the atomic scale and eventually the biological scale and that this feedback feed-forward of information could explain the rapid development of these self-organizing systems and the eventual emergence of self-awareness or consciousness from these complex biological structures.

Dr. William Brown

Nassim’s Forward Excerpted 

from the Book:

Artificial Intelligence and its associated fields are currently in a rapid evolution.  However, the development of AI poses significant ethical and security considerations. In order to address such issues and eventually evolve to the point of true intelligence one must first ask: 

what is intelligence, or more significantly, what is self-awareness or consciousness?

In physics and philosophy, this is commonly referred to as “the hard problem of consciousness” as opposed to the ”easy problem”, the latter of which assumes that cognitive behavior can be explained by the summation of the physical components of the brain and their interactions. The controversy and debate between the two approaches have been raging for years, with the proponent of “the hard problem” approach arguing that the reductive analysis of the physical components of the brain, for instance, cannot resolve and give a full picture of “qualia”, or the subjective conscious experience of feelings and sensations such as the appreciation of a particularly sensational sunset or the qualitative experience of a particularly tasty dish.

While the debate about the nature of consciousness has been raging for centuries and included many famous mathematicians, physicists and philosophers, many consider that the argument of the hard problem is a much deeper attack on the nature of science itself and the validity of the scientific process of physicalism or reductive materialism where the analysis of the parts of a system and its subcomponents will inevitably result in the understanding of the whole. Suggesting that awareness or consciousness is not reducible to the physicality of the brain shakes the foundations of the scientific method and materialism at its core. It reawakes an age-old battle in the evolution of science; is the world reducible to only its physicality or is there something else not understood as of yet?

If there is anything I have learned throughout the decades of research I have done about the nature of reality, is that whenever there are concepts that appear to be in opposition to each other or even that appears to be paradoxical the answer is commonly not found in considering one or the other but often in contemplating both. 

There is no doubt that reductive analysis can be a powerful tool. 

For example, a reductive analysis of a clock’s components and subcomponents has its merits and will yield a general understanding of the mechanisms and the dynamics involved in the functioning of the instrument. The reductive analysis and scientific method are very effective and powerful in giving a general, and in some cases, a deep understanding of the mechanics and energetic behaviors of our world and our reality. 

However, the assumption that by describing the gears, springs, levers, and screws of a watch we have described everything there is to know about the object is erroneous. 

There is an intrinsic, inherent, and fundamental difficulty in physics and in mathematics that has to do with the fractional nature of the material world. 

The clock, so described, does nothing to tell us about the nature of its existence. 

• How did it come to be? 
• Where did the atoms and subatomic particles that make up the various components of the watch come from? 
• How did they become organized in such a manner and what was the nature of their evolution to eventually result in the relationship of all the parts to make the second arrow tick? 
• Who was the watchmaker? 
• Who designed it? 
• Even further, one could ask, what is the source of the energy that makes the gears go around and produce the effect of the arrows going across the face indicating the time of day and what meaning does that hold for the one that observes it?

Therefore, and significantly the meaning of physicalism and reductive analysis can only yield a fundamental answer if the assumption is made that only linear relationships exist and that scales have a finite resolution (some cut-off value) and that the system in which we are applying the analysis is fundamentally and completely isolated from the rest of the activities of the universe! 

Yet today if we ask a physicist where does the atoms that make up the gears of the clock come from and how did the subatomic particles that make up the atoms and molecules of the observer and maker of the watch come to be, or how did they self-organize to make the watchmaker, most likely you will find the answer unsatisfactory or incomplete at best.

For the source of the material, the atoms and subatomic particles, the physicist would have to refer to some miraculous event called The Big Bang in which all space-time and atomic material were produced. As for the mechanism from which the watchmaker emerges, in which some approximately 50 trillion cells each one made of approximately 100 trillion atoms self-organized to produce a highly complex and coherent being, the physicist would be at a loss to explain the self-organizing complexity of its existence. Never mind being able to explain the meaning and experience of the individual reading the time given by the watch.

Consequently, the materialist’s view that all we need to know is the material, such as the brain, to understand everything there is to know about a system is the result of a significant and profound assumption, the erroneous view that we know everything there is to know about the material world itself and that there are no nonlinear relationships (such as entanglement across large distances) or even divergence to infinity and singularities. Yet that is not the case! Further, it assumes that we understand how matter self-organizes in the complexities of biology and its dynamics!

Such assumptions are not congruent with the current level of knowledge we have about the nature of the world i.e., mass, energy, and forces. We have equations that precisely describe the relationship between mass and energy and the relationships between energy and forces but we have no deep understanding of the nature and source of these masses and where the electromagnetic force, for instance, comes from. 

Einstein told us that gravity is the result of the curvature of space-time but nowhere did he describe what is space-time made of so that when it curves it produces a force. 

We know that magnetic fields are present at the atomic scale, but we have no idea where they come from. Further when describing a subatomic particle such as a proton all we can assert is that it is a region of space in which a charge region is strong enough to appear as a particle and we know that atoms themselves which makes up the material world are made of 99.9999999 percent space or mostly space. Even more significant, as a result of the explorations of quantum field theory, we find that the space of the quantum scale is not empty at all but full of electromagnetic fluctuations that we call quantum vacuum energy.

All of this results in the fact that when a materialistic view is taken, in the analysis of a brain for instance, the accuracy of the analysis is only as good as the definition we give to the “material” and at what scale we are considering its involvement. For instance, a neurobiologist who states that cognition is only the result of neuronal interaction in the brain is only considering the dynamics of the relationship of neurons and electrochemical reactions at that scale. The assumption is that the atomic and subatomic scale from which those are constructed is somehow not involved. This would be similar to an astrophysicist observing and attempting to compute the dynamics of a galaxy without considering the stars in it! Or to return to the analogy of our watch it would be like giving an analysis of the movement of the hands of the watch as if the gears and springs that drive them were not involved.

Although the above might appear like a plea against the reductionist materialistic view, it is in fact pointing out that the analysis given by certain neurologists and physicists that consciousness is the summation of all the neuronic activity in the brain, is actually not reductive enough as it does not consider the material dynamics from which the synapses are made at the quantum scales of the atomic and subatomic particles. 

This is where the problem passes from “easy” to a “hard” problem! 

Here, at the quantum scale, wrapping your arms around the analysis of interactions gets much more challenging. In the realm of quantum physics, one must rival with nonlinear interactions such as entanglement at large distances, uncertainties, and divergence, such as the bare mass and bare charge of particles, and most importantly, the Planck scale density of electromagnetic quantum vacuum fluctuations. All of these things are intrinsic to quantum mechanics and have to be considered in the analysis of the material world.

Certainly, intelligence or consciousness has many of the nonlinear attributes one can associate to the quantum realm, and recent experimental evidence, by considering the dynamics of quantum gravity, is emerging demonstrating that non-classical entanglement dynamics may be occurring in the brain. Furthermore, we already know that if we were to achieve true intelligence in some technological developments it will be by means of quantum computing capabilities, which will most likely be vastly different from what we are building in this field today! 

After all, the reason why we are requiring quantum computers, which utilize entanglements and wave functions superposition, to attempt to reproduce the brain capabilities is that the brain itself functions at that scale.

In recent years, new theories of quantum gravity and the nature of forces and mass have emerged describing the energy levels of subatomic particles and forces in terms of pressure gradients in the flow of an underlying field of electromagnetic quantum vacuum fluctuations which can be described as a flow of information. 

These theoretical developments open a door to vast fields of investigations where the brain acts as an antenna tuned into this information flow emerging from the Planck scale of the quantum realm which is driven by a feedback mechanism between the electromagnetic field and the gravitational field of the atomic scale and eventually the biological scale. This feedback feed-forward of information could explain the rapid development of self-organizing systems we observe at the biological scale and the eventual emergence of self-awareness or consciousness from these complex biological structures.

The event of AI development and the interest in the associated fields that it is driving forward have the potential to resolve some of the largest and most important discoveries in human history. As for every groundbreaking technological development, it has the potential to be a great challenge for our civilization and our evolution! 

It is critical, at this time, to consider the ethical and legal ramification of these developments and the future of humanity in this context. 

Thibault Verbiest, in this work, provides remarkable clarity and synthesis, offering essential insights on key questions that should mark any in-depth study on the subject.

in, International Space Federation