I2SC Lecture Series

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Society-centered AI: An Integrative Perspective on Algorithmic Fairness

In this talk, I will share my never-ending learning journey on algorithmic fairness. I will give an overview of fairness in algorithmic decision-making, reviewing the progress and wrong assumptions made along the way, which have led to new and fascinating research questions. Most of these questions remain open to this day and become even more challenging in the era of generative AI. Thus, this talk will provide only a few answers but many open challenges to motivate the need for a paradigm shift from owner-centered to society-centered AI. With society-centered AI, I aim to bring the values, goals, and needs of all relevant stakeholders into AI development as first-class citizens to ensure that these new technologies are at the service of society.

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Statistical innovation for population estimation: integrating administrative records, geospatial data, and real-time streams

Reliable subnational population estimates are essential for effective governance, service provision, and humanitarian response, yet many low- and middle-income countries lack recent or comprehensive census data. This talk explores emerging strategies for estimating population counts when traditional sources are unavailable. I will focus on the integration of diverse and incomplete data sources—including administrative records (e.g., health, education), satellite imagery, and geospatial covariates—combined through Bayesian modeling frameworks to generate high-resolution estimates. In the second part of the talk, I will extend these methods to the problem of nowcasting population distributions in crisis contexts, including forced displacement and conflict. Here, I will explore the utility of real-time or near real-time data streams—such as mobile phone metadata, satellite-derived indicators, and social media signals—for capturing rapid demographic shifts at fine spatial and temporal scales. Throughout the talk, I will emphasize not only the technical and methodological advances enabled by the digital data but also the ethical considerations around data use, privacy, and representation.