@conference {1548857,
	title = {How can computer vision widen the evidence base around on-screen representation},
	booktitle = {IJCAI 2021 Workshop on AI for Social Good},
	year = {2021},
	abstract = {There is strong demand for more complete and better data around diversity in the screen industries. Focusing on on-screen diversity and representation in the UK, the evidence base around representation on-screen has been narrow so far. Diversity evaluation needs to consider more than on-screen presence {\textendash} it should also consider prominence and portrayal. In this position paper, the ethics of applying computer vision to study on-screen characters is discussed via a conceptual framework of on- screen diversity metrics. Computer vision should be applied to identify character occurrences, rather than demographic classification. An illustrative ex- ample of measuring character prominence using a short video clip is shown. It concludes with four areas of applications where adopting computational methods can create a measurably more inclusive and representative broadcast landscape.},
	author = {Raphael Leung}
}
