Welcome to my research corner! I am a second year Ph.D. student at LAMSADE, Université Paris Dauphine-PSL, CNRS.
My research revolves around fairness and social responsibility of algorithms. I had the opportunity to delve into the fascinating world of fairness in AI during the first year of my master's degree. My interest in this topic was sparked by a profound commitment to ethics and social justice that had always been a guiding force in my life. Exploring the intersection of AI and fairness not only intrigued me but also resonated deeply with my personal values. In many ways, it marked a pivotal moment in my career journey, where everything finally seemed to fall into place and make perfect sense.
Fairness is a concept deeply ingrained in human society. It has been extensively explored in various academic fields, each with its own interpretation and context. Thus, attempting to force a singular, AI-centric definition of fairness can neglect these rich historical and disciplinary perspectives. To address these challenges effectively, we aim to adopt an interdisciplinary perspective. By integrating insights from fields like ethics, sociology, law, and beyond, we can create a holistic framework that embraces the multifaceted nature of fairness.
Therefore, instead of considering fairness as an objective property, related to a ressource allocation norm, we prefer study this notion as a subjectively defined necessity by one or more stakeholders of the decision process. Under such a perspective we explore explicability and interpretability as tools to prove fairness.