Co-evolutionary hybrid intelligence
This addresses the problem of building more efficient and interpretable AI systems for researchers and developers, though it appears incremental as it builds on existing hybridization concepts.
The paper tackles the limitations of data-centric AI, such as data scarcity, high resource demands, and lack of explainability, by proposing a co-evolutionary hybrid intelligence approach that integrates human and machine systems.
Artificial intelligence is one of the drivers of modern technological development. The current approach to the development of intelligent systems is data-centric. It has several limitations: it is fundamentally impossible to collect data for modeling complex objects and processes; training neural networks requires huge computational and energy resources; solutions are not explainable. The article discusses an alternative approach to the development of artificial intelligence systems based on human-machine hybridization and their co-evolution.