👉 Answered computing, also known as Explainable AI (XAI), is a field focused on making artificial intelligence systems more transparent and understandable to humans. It aims to provide clear explanations for the decisions and predictions made by AI models, enabling users to comprehend how these systems arrive at their conclusions. This is crucial for building trust in AI, especially in critical applications like healthcare, finance, and autonomous driving. Techniques in answered computing include generating human-readable explanations, visualizing decision-making processes, and developing interpretable models that balance accuracy with transparency. By bridging the gap between complex AI algorithms and human understanding, answered computing seeks to ensure that AI systems are not only effective but also accountable and ethical.
