We like to invite you to our upcoming Invited talk by Prof. Dr. Elena Cabrio from the Université Côte d’Azur, France. The talk will take place on Tuesday, June 4, 2024 at 16:00, as part of our graduate seminar in Room 1101-F128 (Welfengarten 1):
# Speaker
Prof. Dr. Elena Cabrio
Université Côte d’Azur, Inria, CNRS, I3S, France
https://www-sop.inria.fr/members/Elena.Cabrio/
# Time and location
Tuesday, June 4, 2024 at 16:00, 1101-F128 (Welfengarten 1)
# Title
AM-based Decision Making in the Medical and Political Domains
# Abstract
Intelligent machines enriched with computational argumentation models can extract, analyse, summarise and generate natural language argumentative structures from different contexts and from various textual resources. In this talk, I will discuss how such methods can be used in two different scenarios: 1) on medical texts: to enhance evidence-based medicine with natural language argumentative analysis of clinical trials and to generate argument-based natural language explanations for the correct and incorrect answers of standardized medical exams, and 2) on political texts: to identify fallacious arguments in political debates. I will then conclude with some thoughts on recent work on the automatic generation of counter-arguments to fight online disinformation and hate speech.
# Bio
Elena Cabrio is Full Professor at Université Côte d’Azur and member of the Inria-I3S team Wimmics. She holds a Chair in AI at the Interdisciplinary Institute for Artificial Intelligence 3IA Côte d’Azur on “AI and Natural Language”. Her main research interests are Argumentation Mining, Information Extraction and abusive language detection. Goal of her research is to design debating technologies for advanced decision support systems, to support the exchange of information and opinions in different domains (as healthcare and politics), leveraging interdisciplinarity and advances in machine learning for NLP. She currently coordinates the ANTIDOTE (ArgumeNtaTIon-Driven explainable AI fOr digiTal mEdicine) project (CHIST-ERA XAI19).
External participants (i.e. neither students nor employees of LUH) are kindly requested to send a short, informal email to office@ai.uni-hannover.de to register.
