Is Consciousness ‘just’ an attribute of our brain’s neural network activity or an interplay of neural network with ‘substrates’ of consciousness and the reality/world models and their perception?
Consider the possibility of a future intelligent system having an artificial brain with trillions of interconnecting neural nets equally simulating our own brain and armed with perhaps millions of algorithms possible thanks to an even more accurate neuroscience neuro mapping of the human brain and its functioning.
Can we consider that a conscious artificial human entity?
A number of scientists are looking at the development of artificial intelligence from the basis of a developing understanding of the architecture of the human brain.
This work is now represented in two interlocking disciplines:
- Computational Neurobiology: which involves understanding human/animal brains using computational models based on Neuroscience researches of the last century,
- Neural Computing: simulating and building a machine to emulate human behaviors.
What if scientists would find the right combination of elements to unlock Artificial general Intelligence as consciousness pattern that already exists in theoretical physic, but has yet to be applicated?
Is cognition the same of consciousness?
Cosmologist, physicist, and Massachusetts Institute of Technology (MIT) professor Max Tegmark argues that consciousness is a mathematical pattern that can be understood as a state of matter with information processing capabilities.
Using the analogy of the different states of matter (solid, liquid, and gas), Tegmark puts forth the concept that consciousness is also a result of an emergent phenomenon. He calls this state “perceptronium”: a hypothetical state of matter capable of giving rise to self-awareness and subjectivity.
If consciousness is a pattern, in theory, a machine can be conscious if one ascribes to Tegmark’s hypothesis.
Instead of guiding the computer in its learning process to each machine would be given the ability to interact with its environment and will then learn from these interactions.
This so-called Seed AI is therefore by design capable of self-instructed learning and best understood by seeing it as the machine equivalent to a human baby.
Both begin without any representation of the environment and itself but will then structure their inputs, formulate goals and improve themselves according to their goals and their perception of the world.
A Seed AI is a term coined by Eliezer Yudkowsky is an Artificial General Intelligence (AGI) which improves itself by recursively rewriting its own.
The notion of combining intelligence and a positive feedback loop is realized in the idea of Seed AI (Seed Artificial Intelligence).
A seed AI is an AI designed for self-understanding, self-modification, and recursive self-improvement.
When AI finally arrives in its most human-like structure, it will be more than the sum of its parts. Like our human consciousness, AI will probably arise as an emergent and unexpected property of a even more complex system. It will be more than the sum of its programming and neural networks. It is possible to prevision that AI will be able to comprehend infinity in ways we never will. It will be conscious, interdependent to humanity and creative in ways that no one ever has been before.
Author: Cristina Capucci