Description: Model insights in the context of explainable artificial intelligence (XAI) refer to the understanding gained by analyzing the behavior and outputs of an AI model. This approach seeks to unravel how and why a model makes specific decisions, which is fundamental for building trust in automated systems. XAI focuses on transparency and interpretability, allowing users and developers to understand the internal processes of algorithms. This is especially relevant in critical applications across various domains, such as medicine, justice, and finance, where automated decisions can significantly impact people’s lives. Model insights not only help identify biases and errors in systems but also facilitate the continuous improvement of models by providing insights into their functioning. In summary, this concept is essential to ensure that AI operates ethically and responsibly, promoting a safer and more effective use of technology across various fields.
