Consciousness - both as a term and a state - has been in the spotlight this year, thanks to the mind-boggling advancements in Artificial Intelligence. The question of whether AI can achieve consciousness has sparked diverse opinions. While it may have seemed implausible in the past, it is now a topic of serious consideration.
In light of this ongoing discourse, it is important to revisit and understand two famous problems of consciousness: the easy problem and the hard problem.
The easy problems of consciousness, although not truly "easy" to solve, can be addressed using standard methods of neuroscience and cognitive science. These problems involve cognitive functions and behaviors, and examples include:
- How do we integrate information from different sources to form a unified perception of the world? (Integration problem)
- How does consciousness affect and control our behavior? (Control of Behavior problem)
- How do different aspects of perception, such as color, smell, and shape, combine to create a unified experience? (Binding problem)
On the other hand, the hard problem of consciousness delves into the "why" and "how" of conscious experience itself. It seeks to answer questions like: why do we have subjective experiences? Why does the color red appear red, and why does pain feel painful? How does the processing of data in the brain give rise to personal experiences? These are challenging problems because they involve the subjective nature of consciousness, making it difficult to find objective answers.
In summary, the "easy" problems of consciousness focus on understanding the mechanisms and processes underlying conscious experience, while the "hard" problem grapples with the fundamental nature and origins of subjective experience itself.