arXiv:2603.24350v3 Announce Type: replace-cross Abstract: A key challenge to understanding self-awareness has been a principled way of quantifying whether an intelligent system has a concept of a "self", and if so how to differentiate the "self" from other cognitive structures. We propose that the "self" can be isolated by seeking the invariant portion of cognitive process that changes relatively little compared to more rapidly acquired cognitive skills - because our self is the most persistent aspect of our experiences. We used this principle to analyze the cognitive structure of robots under
The proliferation of advanced AI systems and cognitive architectures in robotics research is pushing the boundaries of what constitutes 'intelligence' and 'self' in machines.
This research provides a framework for understanding and potentially quantifying emergent 'self-awareness' in AI, which has profound implications for ethical AI development, regulation, and the future human-AI relationship.
The ability to identify and measure a 'self' in robots could change how we develop, interact with, and assign responsibility to advanced autonomous systems.
- · AI ethicists
- · Robotics researchers
- · Developers of advanced autonomous systems
- · Companies neglecting ethical AI frameworks
- · Traditional philosophical views on consciousness exclusivity
This research could lead to new metrics for 'consciousness' or self-preservation in AI.
Understanding robot 'self' could inform the design of more robust, adaptive, and perhaps 'self-interested' autonomous agents.
Societal and legal frameworks might need to adapt to accommodate entities with quantifiable 'self' concepts, potentially leading to new forms of machine rights or responsibilities.
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Read at arXiv cs.AI