Project Overview
Recommender systems are algorithms that suggest items to users based on their engagement and keep users interested in whatever a site continues to recommend. Together with NEMO Kennislink, we are researching how to implement a journalistic content recommender system responsibly in a sandbox setting. The project aims to provide NEMO Kennislink with the tools to build a responsible recommender system that fits them and presents their audience with an enticing reading experience. Additionally, it gives the AI, Media and Democracy Lab an opportunity to work on real-world use cases and conduct applied research to set up a guideline or toolbox on the responsible design of recommender systems.
By applying a sandbox approach, we can safely experiment with new algorithms and evaluate their ethical, legal, and societal implications. This method allows us to mimic the end-user environment and address concerns regarding data privacy and algorithmic bias. Moreover, this collaboration between computer scientists, social scientists and industry partners will feature co-design sessions to ensure that the resulting recommender system aligns with both technical feasibility and ethical standards.
Approach
Our researchers Manel Slokom and Sanne Vrijenhoek conducted interviews with key stakeholders at NEMOKennislink to gather input on the requirements and desired features for a responsible recommender system. Additionally, they performed a technical evaluation of a tool designed for conducting user studies on recommender systems. The findings from these interviews and analyses will guide the development of the recommender system, which is planned for the next phase of the project.
This project is still ongoing, more information to follow.
