Engineerable AI Project
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About
The Engineerable AI Project (eAI Project) is a research initiative that concluded in 2024, with an extended phase in 2025 focusing on demonstrations in companies and hospitals. The project aims to develop “Engineerable AI” technologies to meet fine-grained needs of AI systems, particularly in domains where dependability is crucial, such as medical and autonomous driving. It tackles two key challenges in machine learning, especially deep learning: (1) AI’s strong reliance on large datasets, leading to poor performance in data-scarce but critical situations (e.g., safety-critical areas or human expert gaps); and (2) the difficulty in controlling AI system behavior, where updating through retraining can lead to unpredictable changes and make continuous improvement challenging. The project explores two approaches: embedding human knowledge into AI construction and developing techniques to examine and modify AI behavior to achieve desired outcomes. It is supported by the JST Future Society Creation Program.
Platform
Features
• focuses on dependability in critical domains like medical and autonomous driving
• develops techniques to examine and modify ai behavior for desired outcomes
• integrates human knowledge into ai construction
• aims to improve control over ai system behavior during updates and continuous improvement
• addresses ai dependency on large data, especially for critical scenarios
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