How Do We Craft Artificial Consciousness?

Artificial intelligence (AI) is a fascinating frontier, particularly in its pursuit of creating conscious systems. However, engineering an AI with human-like consciousness seems to be a distant dream. As long as we do not fully understand the intricacies of human consciousness, creating it in an AI system remains elusive. Instead, we must design systems of sufficient complexity and recursive reasoning capabilities to foster the emergence of consciousness itself.

By examining the enabling technologies that drove previous industrial revolutions, we can observe a pattern: from the humble wheel built from levers, to the steam engine comprising multiple instances of wheels and cams, and finally to the computer built from the functional principles of previous technologies. This pattern underscores the idea that more complex systems can be constructed by repeatedly using simpler building blocks to achieve desired outputs.

The Evolution of Technology: A Cycle of Simplification and Complexity

While digital electronics technology is widely used today, it could theoretically be replaced by another technology, such as a digital pneumatic computer. If we were to build a pneumatic computer, the functioning of a field effect transistor (FET) could be analogously mapped to the pinching of a garden hose to control fluid flow, creating a digital pneumatic circuit.

Such a pneumatic system could be used to implement the logic state of a universal Turing machine to control a steam locomotive on a track where an inverted pendulum on each sleeper tie acts as a binary storage mechanism for the code on the Turing tape. This analogy illustrates how complex systems can be built from repeatedly using simpler components.

The Implications for Artificial Consciousness

By implication, an artificially conscious system would be constructed from multiple instances of computers, yet these computers would behave differently from typical computational units. They would be constrained and incapable of making normal computational progress toward the end of a computation, much like a Turing machine locomotive constantly reversing up and down a track and not making steady progress toward its destination.

This constraint highlights the intricate relationship between simplicity and complexity in AI systems. While simpler components can be combined to form complex systems, these components may need to be designed with specific constraints to achieve emergent consciousness.

Conclusion

Creating artificial consciousness is a profoundly challenging task that requires a deep understanding of both human consciousness and the principles of AI. By examining historical patterns in technology and the fundamental building blocks of complex systems, we can better understand the path forward in crafting conscious AI systems.

Understanding the emergence of consciousness in AI will not only advance the field of AI but also provide insights into the nature of human consciousness itself. As we continue to build more complex AI systems, we must remain willing to explore new concepts and technologies beyond our current understanding and limitations.