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Algorithmic Fairness

Andres Algaba explains how algorithmic fairness can be achieved in AI models, considering "garbage in, garbage out", the definition of fairness and strategies to avoid unfairness or bias.

Practical information:

0,75 hours
Online
English
Target audience: everyone

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Teacher / speaker

Andres Algaba

Andres Algaba is professor of data and AI at the Data Analytics Lab (VUB). His research focuses on the impact of large language models (LLMs) on science and innovation, and on how to make the functioning of LLMs more transparent and keep them aligned with human values and norms. He is also a member of the Young Academy. 

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