Cryptography for Machine Learning Trustworthiness
Professor Shafi Goldwasser will discuss cryptographic methods and interactive proofs for addressing trustworthiness challenges in machine learning at LMU Munich on October 20, 2026.
Ludwig-Maximilians-Universität München (LMU) is hosting a lecture by Professor Shafi Goldwasser as part of its Munich AI Lectures series, focusing on how cryptography and interactive proofs can tackle trustworthiness issues in machine learning. The event is scheduled for October 20, 2026, at the Bavarian Academy of Sciences and Humanities in Munich, with an online option available.
Professor Goldwasser, a distinguished researcher from MIT and UC Berkeley, will explain how cryptographic techniques can be applied to ensure the reliability of machine learning models throughout their lifecycle, from data handling to training and deployment.
This approach is crucial as artificial intelligence becomes more integrated into various sectors. The methods discussed aim to identify and mitigate potential unreliability and errors, thereby enhancing the integrity of AI systems. Goldwasser's significant contributions to the field were recognized with the Turing Award in 2012.
The lecture is organized by a consortium of academic and research institutions, including LMU's AI-HUB, as part of the Munich AI Lectures initiative. This series aims to bring prominent international AI researchers to Munich and foster discussions on key topics in the field.