Manuel Herranz - The Importance of Data Anonymization to Build Ethical AI

0:00 Intro
2:35 Lecture
35:20 Q&A

Title: The Importance of Data Anonymization to Build Ethical AI

Speaker: Manuel Herranz

Abstract: Data provenance and the use and inclusion of personal data have not been historically a consideration in the building of machine translation systems and, lately, Large Language Models (LLMs). Manuel’s convergence lecture will touch upon concepts such as Ethical AI and the need to build ethics all along the data generation and data acquisition pipelines when building AI products and services, GDPR, compliance, EU anonymisation projects, the data-for-AI market, etc. He will also discuss the challenges involved in anonymisation of multilingual content in the context of machine translation.

Short bio: Manuel is Pangeanic CEO and MIT Sloan School of Management graduate. He is a language technology veteran with 25 years industry experience. His concept of DIY Statistical MT underpins current approaches for MT customisation by Bing Translator, Google AutoML, ModernMT and Amazon’s self-training mechanisms. He has written or co-written nearly 20 academic papers – several being the result of the numerous EU projects he’s led or been involved in as a partner. You can find more details about Manuel’s and his work at https://pangeanic.com/

This event took place online on Wednesday 18th October 2023, 16:00 pm BST (GMT+1)