Algorithms increasingly shape the flow of information in societies. Recently, public service media organisations have begun to develop algorithmic recommender systems and automated systems in their internet services, which makes sense given their importance as mediators of information. In the emerging era of big data and growing personalisation, this makes sense strategically and can have instrumental importance for networked societies. This chapter draws on relevant development projects in European and Australian public service media organisations. In relation to the core principles of public service media, five challenges in operationalising automated rulebased systems are identified: 1) balancing popularity and distinctiveness, 2) diversity of exposure to programming, 3) transparency of the logic underlying recommendations, 4) user sovereignty and, 5) the issue of dependence on or independence from commercial intermediaries. The chapter examines a new set of conditions that affect provision public service provision in societies that feature growing use and reliance on networked media
