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1Computer Science Department, University of Texas at Austin, Austin, TX 78712, USA. kuipers@cs.utexas.edu
Artificial Intelligence in Medicine
|September 9, 2008
Summary
Robots can achieve consciousness by using computational models to understand their environment and experiences. This dynamical systems approach explains subjective experience and intentionality, paving the way for artificial consciousness.
Area of Science:
- Artificial Intelligence
- Cognitive Science
- Robotics
Background:
- Computational concepts from robotics and computer vision offer potential explanations for consciousness.
- Key aspects of consciousness, such as qualia, first-person experience, and intentionality, remain challenging to explain.
Purpose of the Study:
- To present a dynamical systems model for agents (human or robotic) interacting with their environment.
- To explore how computational models can account for consciousness, including subjective experience and intentionality.
Main Methods:
- A dynamical systems model incorporating trackers for sensory input and a self-constructed narrative of sensorimotor interactions.
- Agents autonomously learn intentionality by building and refining computational models of external entities.
Main Results:
- Models of external entities explain sensorimotor regularities and serve as referents for symbolic knowledge.
- High sensory information content drives model evaluation, refutes poor predictions, and accounts for subjective experience vividness.
- The proposed account aligns with 11 key features of consciousness identified by John Searle.
Conclusions:
- The fundamental features of consciousness can be implemented in robots with adequate computational power and sensory systems.
- Embodied and embedded agents within their environments are key to achieving artificial consciousness.
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