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Modelling human vision needs to account for subjective experience.
Marcin Koculak1,2, Michał Wierzchoń1,2
1Centre for Brain Research, Jagiellonian University, Krakow, Poland koculak.marcin@gmail.com.
The Behavioral and Brain Sciences
|December 6, 2023
Summary
This study explores subjective experience in artificial vision systems. By operationalizing subjective experience within deep neural networks, researchers aim to better compare human and artificial vision capabilities.
Area of Science:
- Cognitive Science
- Neuroscience
- Artificial Intelligence
Background:
- Vision is intrinsically linked to perceptual awareness, representing a key outcome of sensory processing.
- Conscious vision involves more than just object recognition for building our world representation.
Purpose of the Study:
- To propose a method for operationalizing subjective experience in deep neural networks (DNNs).
- To facilitate a more comprehensive comparison between human and artificial vision systems.
Main Methods:
- Development of a framework to model subjective experience within DNNs.
- Utilizing computational approaches to analyze perceptual awareness.
Main Results:
- The proposed operationalization provides a novel approach for studying subjective experience.
- This framework enables quantitative analysis of perceptual representation in artificial systems.
Conclusions:
- The study offers a pathway for deeper insights into the mechanisms of both human and artificial vision.
- Comparing subjective experience in DNNs and humans can advance our understanding of consciousness.
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