This article discusses the concept of self-orientation and its significance in human learning compared to artificial intelligence (AI). The research highlights the limitations of AI in terms of flexibility and adaptability, which are innate qualities in humans. AI currently lacks a notion of the self, hindering its ability to navigate changing environments and solve problems efficiently. The study conducted a comparison between human players and AI algorithms in four video games, demonstrating that humans outperformed AI in terms of self-orientation. The research emphasizes the need for AI to improve its ability to handle unexpected situations by adopting self-orienting capabilities similar to humans. The article also provides recommendations for companies on the cautious deployment of AI in fast-changing conditions and the acknowledgement of the gap between AI and human abilities.
| Signal | Change | 10y horizon | Driving force |
|---|---|---|---|
| AI lacks self-orienting capabilities | AI needs to develop a notion of self | AI will gain the ability to flexibly navigate changing environments | The desire for AI to be more adaptable and effective |
| Humans outperform AI in self-orienting tasks | Humans excel at flexible problem-solving | AI will need to improve its problem-solving abilities | The gap in performance between AI and humans |
| AI struggles in fast-changing conditions | Caution is necessary when using AI | Companies will need to carefully consider when and how to use AI | The limitations of AI in dynamic environments |
| Acknowledging the gap between AI and humans | Recognizing the disparity in capabilities | Efforts will be made to bridge the gap between AI and human performance | Identifying the need for improvement in AI systems |