Fariba Karimi

Complex system approach for addressing structural inequalities 

Structural inequality is one of the important manifestations of social inequalities in which societies create systems of privilege that are structural barriers to equality and inclusiveness. Structural inequalities emerge and evolve in complex multi-dimensional social networks. With the rise of artificial intelligence and algorithms in decision-making processes, such inequalities are being reinforced and exacerbated in a nonlinear, complex manner that is difficult to comprehend and tackle. To address and mitigate such timely issues, we need a complexity science approach and interdisciplinary methods. In this talk, I’ll give an overview of our recent research on this topic and the path ahead. 

About Fariba Karimi

Fariba Karimi leads the research team on Algorithmic Fairness at the Complexity Science Hub. Fariba’s research focuses on computational social science, the emergence of biases and inequality in networks and algorithms, and modelling human behaviour. Her recent research revolves around the topics of the visibility of minorities in social networks, the impact of network structure on ranking and recommender algorithms, and disparities in academia and their impact on under-represented groups. She combines statistical analyses of large datasets of online interactions with computational models, agent-based modelling, and network analysis.

Fariba is a former IceLab member. She received a PhD in physics and computational science from Umea University, in Sweden, in 2015.

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