Thinking Fast and Slow in AI: The Role of Metacognition
3 hours ago
- Current AI successes are narrow, limited to specific tasks like image recognition and NLP.
- Advancements rely heavily on large datasets and computational resources, not general intelligence.
- Human metacognitive mechanisms can guide the development of more capable AI systems.
- The paper applies Kahneman's dual-system theory: system 1 (fast, reactive) and system 2 (slow, deliberative) processing.
- A multi-agent AI architecture is proposed where system 1 agents handle routine problems from experience, while system 2 agents are activated for complex reasoning and optimization.
- Both agent types use a world model (domain knowledge) and a self-model (past actions and skills).