Meaningful Explanation

Meaningful explanation in artificial intelligence focuses on making the decision-making processes of complex models, such as deep learning and reinforcement learning systems, understandable to both experts and non-experts. Current research emphasizes developing methods that generate explanations tailored to specific audiences and tasks, often leveraging large language models or interactive interfaces to improve comprehension. This work is crucial for building trust in AI systems, ensuring accountability, and facilitating effective human-AI collaboration across diverse applications, from recommender systems to security analysis.