Date: 19th of July, 2021
Time: 16:00 (CET)
Title: Building public service recommenders: Logbook of a journey
Abstract: The BBC is one of the world's leading broadcasters, producing a large amount of content including video, audio and text, spanning topics such as news, sport, education, and entertainment. In order to fulfil its public service remit, the BBC must serve all its audiences, providing each audience member with the most relevant and engaging content for them.
Up to now, manual curation has been the main approach used by the organisation to achieve that. However, that is unable to scale and to be tailored to each user. To support the BBC in developing and deploying recommendations at scale our team, Datalab, has taken an approach centred around the collaboration across teams and different professional figures, i.e. product, editorial, and data people, and around the concept of public service AI. In this talk, Alessandro reflects upon the challenges and lessons learnt in the years since the creation of our team.
Speaker Biography: Alessandro Piscopo is a principal data scientist at the BBC, in a team called Datalab. His work focusses on developing and deploying public service recommendations algorithms across the organisation, to connect BBC audiences with relevant content. During his PhD, obtained in 2019 at the University of Southampton, Alessandro studied the effects of socio-technical dynamics on data quality in collaborative knowledge engineering projects. His current interests include online collaboration, knowledge graphs, and fairness and ethics in AI.