Research project

This PhD project examines how film/television workers deploy audience data and AI tools. The research is carried out in the Department of Culture, Media and Creative Industries at King’s College London. It is supported by the London Arts and Humanities Partnership (LAHP), which is an AHRC-funded doctoral training partnership.

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Algorithms and data analytics are making deeper inroads into screen production in Europe. As film and TV viewers migrate to the web, real-time data from streaming content provide an increasingly granular picture of taste and viewing patterns. It is possible for screen workers to leverage these data to drive creative decisions – whether it’s with insights from an internal analytics department, AI tools, or a streaming service. In fact, big data companies like Netflix and Amazon are currently investing heavily in European content. As a result, they are upending business models and restructuring power relations. What does this mean for film and TV talent in Europe?


My research examines how these developments affect creative labour in the European screen industry. More specifically, I zoom in on the experiences of screenwriters, directors, and producers: How do audience data and AI tools impact their creative practices in the development stage? What are the perceived possibilities and limitations? I cast a wide geographical net and collect data from several European countries. These insights will prove useful for industry professionals and policymakers alike. 

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This project draws on concepts and methods from media industry studies, critical algorithm studies, and critical data studies. The methodological toolkit is qualitative in nature. Semi-structured interviews with film and television workers form a cornerstone of the study. So far, I have met with people at their workplace, but due to the Covid-19 pandemic, I am conducting the rest of the interviews online. Another key data source is industry documents, including articles from trade publications (e.g. Variety) and industry federations.