Definition
In AI, a black-box model refers to complex systems like deep neural networks where the internal decision-making logic is opaque and difficult for humans to interpret. While these models often achieve high predictive accuracy, their lack of transparency poses challenges for debugging, regulatory compliance, and trust, leading to the field of Explainable AI (XAI) which seeks to uncover their internal reasoning processes.
Summary
A system where internal mechanisms are hidden, and only inputs and outputs are observable.
Key Concepts
- Interpretability
- Opacity
- Input-Output Mapping
- Explainable AI
Use Cases
- Deep Learning Models
- Proprietary Algorithms
- Complex Predictive Systems