Inferring The World's Gender and Ethnic Diversity using Personal Names
The world of artificial intelligence (AI) is evolving at a breakneck pace, transforming industries from healthcare to finance. But as AI systems become more integrated into our daily lives, questions about fairness, representation, and bias are more important than ever. Who is shaping the future of AI research? Are diverse voices and perspectives being included in the conversation?
From June 16–18 in Malmö, the 4th International Forum on Migration Statistics (IFMS 2025) brings together statisticians, policymakers, demographers, and data scientists to advance innovative tools—especially Big Data and AI—for richer, more timely migration statistics.
One particularly promising innovation, already used by the UN International Organization for Migration (IOM) as part of its Diaspora Mapping and Engagement Toolkit, is personal name classification, a technique that leverages large datasets of names to infer migration patterns and origins
Non-discrimination laws in the US represent the only available path to challenge discrimination caused by biased AI. On the other hand, the EU’s legal framework has developed regulations to tackle the challenges posed by biased AI.
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