In past roles, I’ve spent countless hours trying to understand why state-of-the-art models produced subpar outputs. The underlying issue here is that machine learning models don’t “think” like humans ...

Krishna, Satyapriya, Tessa Han, Alex Gu, Steven Wu, Shahin Jabbari, and Himabindu Lakkaraju. "The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective." Transactions on ...

Scientists in Australia have developed an “explainable” artificial intelligence (AI) tool that could help doctors diagnose schizophrenia by analyzing brainwave patterns, AzerNEWS reports, citing ...

A practical review of explainable AI examines how transparency and interpretability improve trust in high-stakes applications. By introducing ...

You will be redirected to our submission process. The accelerating pace of global environmental change driven by climate change, biodiversity loss, land degradation, and urbanization demands ...