Panel discussion, chaired by Hannah Fry – Interpretability, Safety and Security in AI

Hannah Fry – Mathematician, author and science presenter ; Isaac Kohane – Harvard University ; Aleksander Madry – Massachusetts Institute of Technology ; Cynthia Rudin – Duke University ; Manuela Veloso – Carnegie Mellon University

Introduction

This conference – organized under the auspices of the Isaac Newton Institute “Mathematics of Deep Learning” Programme — brings together leading researchers along with other stakeholders in industry and society to discuss issues surrounding trustworthy artificial intelligence.

This conference will overview the state-of-the-art within the wide area of trustworthy artificial intelligence including machine learning accountability, fairness, privacy, and safety; it will overview emerging directions in trustworthy artificial intelligence, and engage with academia, industry, policy makers, and the wider public.