Explainability

Explainability refers to how well we can understand and trust the decisions or recommendations made by a machine or computer system, such as an AI. It involves making the process transparent so that people can see why a system arrived at a particular conclusion. This is important for ensuring fairness, identifying errors, and building confidence in technology. Essentially, explainability helps bridge the gap between complex algorithms and human understanding, making it easier to evaluate and rely on the system's outputs in real-world situations.