Presentaiton of the paper "Structural Group Unfairness Measurement and Mitigation by means of the Effective Resistance" at the 2nd Workshop on Trustworthy Learning on Graphs (TrustLOG) at the Web Conference (WWW) 2024.
Guest Lecture at the University of Notre Dame (USA) on the course on thics of Data Analytics and AI, imparted by Georgina Curto, member of the Notre Dame-IBM Tech Ethics Lab. The lecture covered the foundamental aspects of polarization in social networks and how different people's information access lead to structural group unfairness
International seminar coorganised by the CCCB and the ERC project Algorithmic Societies about the AI social impacts. I gave a talk and participated on a round table about the role of AI on discrimination. I participated with Thao Phan (Monash University), Scott Wark (University of Kent), Rocco Bellanova (Free University of Brussels), Carlos Castillo (ICREA-Pompeu Fabra University) and Piera Riccio (ELLIS Alicante(). Moderated by Jordi Pérez Colomé (El Pais)
I participated on a round table about the role of AI to be more sustainable. I participated with Jose Fuster (Director of European Funds and Sustainability of Bank Sabadell) and Antonio Sánchez (President of AlicanTec)
30 min technical talk aimed to researchers from Carnegie Mellon University from DDMLab. I presented the technical challenged from algorithmic challenges in data-centric interpretable approahces, Graph Fairness and long-term effects and feedback loops.
The European Parliament sent to ELLIS Alicante their JURI Committee on Legal Affairs, which are responsables of the AI regulation in Europe (AI Act). I presented the current Challenges of Algorithmic discrimiation in AI, getting close technical, social and legal concepts in the same presentation. We then discussed the current gaps between technicians and regulators to overcome the current limitations of AI regulation.
A high level introduction about ethics in Artificial Intelligence, why does discrimination occurs and how to solve it using AI [Scientific Dissemination talk].
A tutorial on Graph Rewiring using learnable spectral node embeddings and distances. We first explain the introductions to spectral theory, then we go trought the proposed methods for transductive rewiring, then we delve into how to performe inductive rewiring in graphs using DiffWire and we finally explain the implications of rewiring in Algorithmic Fairness [Accepted Academic Tutorial].
A high level introduction about algortihmic discriminations and lack of diversity and the AI challenges to solve this problem [Scientific Dissemination talk].