Abstract

Social networks significantly influence our access to opportunities and resources, affecting both individual and societal outcomes. But what are the consequences when these networks amplify inequality? This interactive talk introduces “Network Fairness,” a new area of research where ethical decision-making and a deeper understanding of people’s complex and multifaceted relationships are essential for achieving fairness in complex societies while upholding multiple moral goals. Through a series of thought-provoking scenarios, we will investigate how effort, merit, social capital, and individual choices intersect and create ethical dilemmas. Participants will engage in real-time decision-making exercises, weighing the moral considerations of each scenario. By the end of this talk, you will recognize how personal networks shape our perspectives and opportunities, understand the limitations of traditional fairness approaches within networked systems, and appreciate the need to balance multiple ethical goals in pursuit of fairness. This talk presents a work-in-progress perspective, inviting you to explore rather than adopt a one-size-fits-all solution. It aims to equip you with analytical tools to navigate complex ethical decisions in an increasingly networked world.

Bio

Lisette Espín-Noboa is a Visiting Professor at the Institute of Human-Centred Computing at TU Graz where she teaches computational methods to measure inequality and fairness in social networks. She is also a senior postdoctoral researcher at the Complexity Science Hub (CSH), where she is part of the Algorithmic Fairness and Network Inequality group. She is also affiliated with the Department of Network and Data Science at Central European University (CEU). Her work bridges Computational Social Science, Network Science, and Artificial Intelligence, with a special focus on achieving the UN Sustainable Development Goals (SDGs). At CSH, Dr. Espín-Noboa examines algorithmic fairness through a social network lens, identifying conditions under which network-driven inequalities in decision-making are justifiable or unjust (aligned with SDGs 5, 10, and 16). She also studies the role of collaboration networks, parenthood, and online visibility in academic success and is developing a tool to increase the visibility of under-represented scholars (SDG 5). At CEU, she leverages multi-modal data sources, including satellite imagery and mobility networks, to develop high-resolution poverty maps. To enhance the reliability, she is also designing low-cost, accurate solutions that incorporate contingency plans to address missing data.