Assessing social media content is quite challenging due to the subjective nature of the material where context plays a pivotal role. In this talk, I highlight the challenges of dealing with nuanced language due to inherent characteristics of dialects as manifested in the Arabic language as well as in English. I will talk about challenges in labeling and building systems where the amount of labeled data is on the low. However such challenges can be mitigated with smart designs while also heeding diversity and inclusion in the process.
Mona Diab is The Lead Responsible AI Research Scientist with Meta and she is also a full Professor of CS at the George Washington University where she directs the CARE4Lang NLP Lab. Before joining Meta, she led the Lex Conversational AI project within Amazon AWS AI. Her current focus is on Responsible AI and how to operationalize RAI for NLP technologies. Her interests span building robust technologies for low resource scenarios with a special interest in Arabic technologies, (mis) information propagation, computational socio-pragmatics, NLG evaluation metrics, and resource creation. She has served the community in several capacities: Elected President of SIGLEX and SIGSemitic. She currently serves as the elected VP for ACL SIGDAT, the board supporting EMNLP conferences. She has delivered tutorials and organized numerous workshops and panels around Arabic processing. She is a cofounder of CADIM (Consortium on Arabic Dialect Modeling, previously known as Columbia University Arabic Dialects Modeling Group), in 2005, which served as a world renowned reference point on Arabic Language Technologies. Moreover she helped establish two research trends in NLP, namely computational approaches to Code Switching and Semantic Textual Similarity. She is also a founding member of the *SEM conference, one of the top tier conferences in NLP. She currently serves as Senior area chair for multiple top tier conferences and the Diversity and Inclusion co-chair for ACL 2022. She has published more than 250 articles.