Consciousness and Artificial Intelligence

3.

The Intersection: Can Machines Be Conscious?

3.1.

3.1.1.

Is Consciousness Computable?

3.1.1.1.

Computationalism

3.1.1.1.1.

Church-Turing Thesis

3.1.1.1.2.

Computational Theory of Mind

3.1.1.2.

Limits of Computation

3.1.1.2.1.

Gödel's Incompleteness Theorems

3.1.1.2.2.

Halting Problem

3.1.1.2.3.

Non-Computable Functions

3.1.1.3.

Quantum Computation and Consciousness

3.1.2.

The Strong AI vs. Weak AI Distinction

3.1.2.1.

Strong AI: Genuine Understanding

3.1.2.1.1.

3.1.2.1.2.

Semantic Content

3.1.2.2.

Weak AI: Simulation of Intelligence

3.1.2.2.1.

Behavioral Mimicry

3.1.2.2.2.

Tool Perspective

3.1.2.3.

Searle's Position

3.1.3.

Simulation vs. Instantiation of Consciousness

3.1.3.1.

Emulation of Processes

3.1.3.2.

Genuine Subjective Experience

3.1.3.3.

Substrate Independence

3.1.3.4.

Multiple Realizability

3.2.

Historical Perspectives on Machine Consciousness

3.2.1.

Cybernetics and Early Speculations

3.2.1.1.

Feedback and Control Systems

3.2.1.2.

Norbert Wiener's Contributions

3.2.1.3.

Early Machine Models of Mind

3.2.1.4.

Grey Walter's Tortoises

3.2.2.

The Role of Embodiment and Enactivism

3.2.2.1.

Situated Cognition

3.2.2.2.

Sensorimotor Integration

3.2.2.3.

The Importance of Physical Interaction

3.2.2.4.

Embodied Cognition Theory

3.2.2.5.

Enactive Approach to Cognition

3.2.3.

Artificial Life and Emergence

3.2.3.1.

Complex Systems

3.2.3.2.

Emergent Properties

3.2.3.3.

Self-Organization

3.3.

Contemporary Debates

3.3.1.

Panpsychism and AI

3.3.1.1.

Integrated Information Theory

3.3.1.2.

Consciousness as Fundamental

3.3.2.

Biological Naturalism

3.3.2.1.

Searle's Position

3.3.2.2.

Causal Powers of Biology

3.3.3.

Functionalist Responses

3.3.3.1.

Multiple Realizability

3.3.3.2.

Substrate Independence

Previous

2. Foundations of Artificial Intelligence

Go to top

Next

4. Theoretical Frameworks for Artificial Consciousness