Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence

Artificial intelligence (AI) is currently being utilized in a wide range of sophisticated applications, but the outcomes of many AI models are challenging to comprehend and trust due to their black-box nature. An examination of XAI techniques and evaluation was conducted by looking at 410 critical articles, published between January 2016 and October 2022, in reputed journals and using a wide range of research databases as a source of information.

⚡ This is an original paraphrased summary — not copied from the abstract. Full paper available at the source link below.

• 1 Usually, it is essential to understand the reasoning behind an AI model’s decision-making.
• 2 Thus, the need for eXplainable AI (XAI) methods for improving trust in AI models has arisen.
• 3 XAI has become a popular research subject within the AI field in recent years.

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

This summary is based on publicly available metadata and abstract. For the full research paper, visit the original source: