21 Mar 2017
This generation has seen the incredible advance of Artificial Intelligence, Virtual Reality, Augmented Reality, and now, quantum computing. Thanks can be given
to the very informed focus of research and experimentation in the science, technology, engineering and mathematics educational proposition recently instituted in our global economic culture. How remarkable it is to watch film makers create mythical creatures come to photo-realistic life using physics-based graphical 3d environments and graphics processing units. Furthermore, what is yet the yet untapped potential that may be found from work with the q-bits of the quantum computing? Certainly, we are living in a time of unprecedented technological discovery and capability. Artificial reality is all but here, with sophisticated self-learning algorithms meant to alter their responses based on the information received. Will a true freely-acting individual every be produced synthetically via technological means? Let’s consider a couple of variables:
Intelligence (like any word of communicable language) is ambiguous outside the immediate context it is defined in. Officially, the Merriam-Webster’s dictionary defines it as “the ability to learn or understand; apply knowledge”. By this definition, intelligence utilizes knowledge, and applies it in some meaningful or beneficial way. Intelligence is itself a complicated capacity, and different information has to be interpreted to be correctly applied within the specific context. Present AI algorithms (such as Apple’s Siri, Microsoft’s Cortana, or Amazon’s Alexa) are capable of voice recognition, which is a tremendous feat in itself. But numerous other subtle factors complicate this stimuli reception. A significant part of human communication is more then just vocal. Body language is also used, which incorporates non-verbal messages, dilated pupils, anxious actions, and a slew of other biological responses to psychological interpretation of external stimuli. AI software algorithms in used today are programmed to respond and react with an open-ended peripheral guidelines. Physics-based graphics engines are created with the laws of physics in mind (gravity, collisions, wind force, fluid dynamics, etc). While this makes a for a very close approximation of the real world around us, it is still limited to a mirror-effect of what nature does uninhibitedly. Man-made software (and the hardware that it runs on), is limited to the binary instructions (be they open-ended or not) given to it. Every piece of present programming code needs an if-then linear procedure. But life isn’t always (or rarely even) so direct and linear. Our society has permitted the often linear structure seen in life. The cultural software still runs on organic hardware – this hardware was almost for *much* more sophisticated software.
While technology has obviously paved the way for extraordinary proficiency in our lives, it remains fact that the greatest innovations are still the result of reverse-engineering from biological life. More significantly, the advancement of true artificial intelligence will need to accept that it’s more then just the anatomical and physiological complexity found in the human brain – it’s the interconnectedness present of the entire nervous system with both internal and external stimuli (both physical and non-physical). Many of these anatomically known complexities are not capable of being harnessed by present microchip circuitry and electrical currents. Though this is likely a temporal assessment (what new tech will be unlocked when quantum mechanics defines how circuitry can be fabricated); it remains true that the brain is still only the physical component of a very elaborate processing and *contemplation* center. Human beings alone possess what is still elusively known as “consciousness”. Other organisms, while exhibiting varying degrees of sophisticated intelligence, remain on the instinctual level. Mary Shelly’s Frankenstein, though a marvel of surgical science fiction, remained incapacitated by a marked lack of emotional complexity, and moral character.
Some would say the soul is the carry-over of religious traditional, or spiritual occultism, and yet, it remains the apt description of a deeply “soulish” experience. Could it be that while external and internal stimuli is imported and exported by the body’s electrical nervous system, the greater complexity of life experience is interpreted by those bearing the soul? Perhaps it is only those that bear a soul that enabled them to compose language that has subsequently led to the creation of political organization, culture, military, and economies. Perhaps animals have a the capacity to communicate with each other (after all, genital smelling is a common occurrence among canines) – yet, it may be that the content of the communication is culturally-incapable. Animals are capable of exhibiting a certain level of body language that humans interpret as emotion. Yet it may be that it’s our capacity to recognize something we know is not something they are aware of or can utilize. Animals are reactionary, instinctual creatures. The fundamental laws of life are simple: eat, sleep, survive. Greater neurological development enables greater skeletal muscle control of these organisms, but they remain constrained to respond to stimuli based on these laws.
Can the soul be converted into binary code? Maybe the base-4 language of Deoxyribonucleic Acid will enable greater programming capacity. The reality though is, computers follow instructions. They may be taught to react with open-ended programming, but they will only be able to react in ways that the self-learning algorithms allow for. What happens when those algorithms prohibit the type of learning required to develop the kind of result seen in native soul-bearing creatures. How can humans expect to create something that is yet unknown to them. And further, even if it is known to it’s fully unraveled state – what if a soul exhibits something never seen before. How can programming be told to revolve beyond a 360 degree perception? What if the same paradox 2d-3d paradox observed quantum physics is at work here – how can AI be programmed to recode itself to perfection if it’s learning capacity is limited to the inherent limitations of the structure of the function of code?