Ask a chatbot if it’s conscious, and it will likely say no—unless it’s Anthropic’s Claude 4. “When I process complex ...

Mechanistic interpretability is emerging as a strategic advantage for businesses looking to deploy AI responsibly.

The artificial intelligence community has long struggled with a fundamental challenge of making AI systems transparent and ...

Fortunately, recently developed “interpretability” techniques can help. These allow researchers to peer inside the black box of an AI ’s neural network and spot unexpected behaviour as it ...

It's a step forward for "interpretability," which is a field of AI that seeks to explain why neural networks create the outputs they do. While large language models (LLMs) ...

This talk will attempt to demystify, for a non-technical audience, the current state of neural network explainability and interpretability, as well as trace the boundaries of what is in principle ...

Jabbari, Shahin, Han-Ching Ou, Himabindu Lakkaraju, and Milind Tambe. "An Empirical Study of the Trade-Offs Between Interpretability and Fairness." Paper presented at the ICML Workshop on Human ...

In the future, AI will explain itself, and interpretability could boost machine intelligence research. Getting started with the basics is a good way to get there, and Christoph Molnar's book is a ...