North Penn Now

Neel Somani Sets a Higher Standard for AI Interpretability

In artificial intelligence research, scientists often describe parts of a model using simple algorithmic language. A small ...

Interpretability in deep learning for finance: A case study for the Heston model

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known Heston option pricing model as a benchmark, researchers show that global ...
mccormick.northwestern.edu

Exploring the Connections Among Machine Learning, Interpretability, and Logic

The field of interpretability investigates what machine learning (ML) models are learning from training datasets, the causes and effects of changes within a model, and the justifications behind its ...

AI Researcher Mahfuz Islam Khan Jabed Advances Ethical, Explainable AI for Workforce and Healthcare Applications

This research initiative highlights the importance of ethical and explainable artificial intelligence in workforce ...
Reuters

Dan Herbatschek Leads New Initiative in New York and Los Angeles to Advance Transparency and Interpretability in Machine Learning

NEW YORK, NY, November 28, 2025 (EZ Newswire) -- Dan Herbatschek, opens new tab, founder and CEO of Ramsey Theory Group, opens new tab, has announced a new initiative to strengthen transparency, ...
Quanta Magazine

The Computer Scientist Peering Inside AI’s Black Boxes

Machine learning models are incredibly powerful tools. They extract deeply hidden patterns in large data sets that our limited human brains can’t parse. These complex algorithms, then, need to be ...