Explanation Capability

Explanation capability in artificial intelligence focuses on generating understandable justifications for AI decisions, aiming to improve trust, transparency, and user understanding. Current research explores various methods for generating explanations, including those based on logic rules, conversational approaches leveraging large language models, and techniques that adapt explanations to specific user needs and tasks. This field is crucial for responsible AI development, particularly in high-stakes domains like medicine and law, where understanding the reasoning behind AI predictions is paramount for both accountability and effective human-AI collaboration.