Towards an NP-Hard Model of Consciousness

Overview

Exploring computational complexity of consciousness, analyzing arguments for non-computability, and proposing conditions for implementable conscious systems in artificial intelligence.

Syllabus

• Introduction to Consciousness
Definition and key theories of consciousness
Philosophical perspectives on consciousness
• Computational Complexity
Basics of computational complexity theory
Definition of NP-hard and related terms
• Consciousness and Computation
Historical perspectives on consciousness as computation
Overview of computational models of consciousness
• Arguments for Non-Computability of Consciousness
Analysis of prominent non-computability arguments (e.g., Gödelian arguments)
Counterarguments and critiques
• Towards an NP-Hard Model of Consciousness
Characteristics of NP-hard problems
Hypothetical frameworks for modeling consciousness as NP-hard
• Implementability of Conscious Systems
Conditions necessary for implementing conscious systems
Assessment of current AI architectures in relation to these conditions
• Case Studies and Applications
Review of existing AI systems claiming or exhibiting elements of consciousness
Analysis of their computational complexity and ethical implications
• Future Directions and Ethical Considerations
Potential advancements and their implications for AI and humanity
Ethical challenges in creating conscious AI systems
• Conclusion
Summarization of key concepts
Open questions and areas for further research

Subjects

Conference Talks