Researchers have developed AdapGNN, a novel model-agnostic framework that addresses the oversmoothing problem in graph neural ...

In my previous article, I discussed the importance of AI explainability and the different categories of AI explainability, explainable predictions, explainable algorithms and interpretable ...

OpenAI today published a research paper that outlines a new way to improve the clarity and explainability of responses from generative artificial intelligence models. The approach is designed to ...

As enterprises shift from AI experimentation to scaled implementation, one principle will separate hype from impact: explainability. This evolution requires implementing 'responsible AI' frameworks ...

In a global report issued by S&P, 95% of enterprises across various industries said that Artificial Intelligence (AI) adoption is an important part of their digital transformation journey. We’re ...

Evan Hackstadt is a computer science major with minors in biology and math. He is a 2025-26 health care ethics intern at the Markkula Center for Applied Ethics at Santa Clara University. Views are his ...

As the impact of artificial intelligence (AI) grows in our world, the University of Adelaide is exploring the role that technology can play in the health sphere, particularly in clinical ...

Would you blindly trust AI to make important decisions with personal, financial, safety, or security ramifications? Like most people, the answer is probably no, and instead, you’d want to know how it ...

Researchers have created a taxonomy and outlined steps that developers can take to design features in machine-learning models that are easier for decision-makers to understand. Explanation methods ...