Large language models show remarkable potential in healthcare but face critical explainability challenges that must be addressed before widespread clinical deployment. Here, we examine technical and ...

Deep Neural Networks (DNNs) have achieved remarkable accuracy for numerous applications, yet their complexity often renders the explanation of predictions a challenging task. This complexity contrasts ...

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

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

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 ...

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 ...

Customers of artificial intelligence (AI) models may have certain rights under the Consumer Protection Act, Ajay Kumar, Partner at Triumvir Law, mentioned at MediaNama’s AI and Fintech event on April ...

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 ...

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 ...

In the fast-paced world of Artificial Intelligence (AI), where algorithms drive everything from personalized recommendations to autonomous vehicles, the demand for transparency and accountability has ...