Fast and Slow Thinking in Artificial Intelligence: What is Metacognition?

Although artificial intelligence systems are successful in solving complex tasks day by day, they lack the ability to switch between people “fast thinking” and “invest thinking”. New research published in arXiv, metakognition—i.e. thinking about their thinking processes—it explains how the spread can be integrated into artificial intelligence models.

The main findings of the research:

• AI systems currently only provide responsive answers and do not question solution paths
• Metacognition can help models identify incorrect decisions
• A layer structure like “system 1” (automatic) and “system 2” (analytic) in the human brain creates a model for artificial intelligence
• Such an approach can provide more reliable and clear AI decisions

Based on Kahneman’s famous “Fast and Slow Thinking” theory, this study emphasizes the necessity of developing a critical perspective against their outputs of artificial intelligence models. The large language models available are deprived of the ability to do more in-depth analysis when they consider a response or “I’m not stuck” in uncertain situations.

The researchers suggest that metacognition mechanisms are integrated into AI systems, not less faulty of systems, they will be aware of their limitations. This can be a great progress in the use of artificial intelligence in critical areas such as health, law and finance. The study offers a new perspective on artificial intelligence security and interpretation.