Monojit Choudhury, Professor of Natural Language Processing, Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), Abu Dhabi
– 12 January 2024
Talk summary: Large language models (LLMs) have revolutionised the field of natural language processing (NLP) and natural human–computer interactions. They hold a lot of promise, but are these promises equitable across countries, languages, and other demographic groups? Research from Monojit Choudhury’s group as well as from around the world is constantly revealing that LLMs are biased in terms of their language processing abilities in most but a few of the world’s languages, cultural awareness (or lack thereof), and value alignment. In this talk, Choudhury highlighted some of his group’s recent findings around value alignment bias in the models and argued why we need models that can reason generically across moral values and cultural conventions.
He also discussed some of the opportunities for students at the postgraduate, PhD, and postdoctoral levels at the newly-founded Mohamed bin Zayed University of Artificial Intelligence in Abu Dhabi.
Speaker bio: Monojit Choudhury is a Professor of Natural Language Processing at the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), Abu Dhabi. Prior to this, he was a Principal Scientist at the Microsoft Research Lab and Microsoft Turing, India. He is also a Professor of Practice at Plaksha University, and an Adjunct Professor at IIIT Hyderabad. Choudhury’s research interests lie in the intersection of NLP, social and cultural aspects of technology use, and ethics. In particular, he has been working on the multilingual aspects of large language models, their use in low-resource languages, and making LLMs more inclusive and safer by addressing bias and fairness aspects. He is the General Chair of the Indian national linguistics Olympiad and the Founding Co-chair of the Asia-Pacific linguistics Olympiad. He holds a BTech and PhD degree in Computer Science and Engineering from IIT Kharagpur.
[Talk organised in collaboration with the Department of Computer Science and Automation]