It is easy to recognize that social media feeds or search results vary for different people. However, it is less clear how much of that bias comes from the way people interact online, and how much is the result of algorithms that are used to filter or rank content. Scholars trying to disentangle this bias recognize the importance of considering diversity in their research. However, analysing algorithmic biases and ways to avoid or overcome them still comes with many challenges. For instance, how do you involve the perspectives of people who are not represented in datasets? Or how do you define what makes an algorithm “fair”, let alone measure fairness?

In this episode of our podcast series Inclusive Research and Innovation (IRI) in Science, Technology, Engineering and Mathematics (STEM), Dr. Claudia Werker (Delft University of Technology) interviews Prof. Dr. Claudia Wagner from RWTH Aachen University. She shares her vision for an infrastructure platform that could facilitate more inclusive methods and data collection in her field of research.