In this work, we analyze more than two million news photos published in January 2016. We demonstrate i) which objects appear the most in news photos; ii) what the sentiments of news photos are; iii) whether the sentiment of news photos is aligned with the tone of the text; iv) how gender is treated; and v) how differently political candidates are portrayed. To our best knowledge, this is the first large-scale study of news photo contents using deep learning-based vision APIs.

Using machine learning, the algorithm produces a daily score based on the types of photos used in global news reports.

It might not be obvious to a human, but an artificial intelligence programme sees distinct similarities in, say, the composition of the subjects, or colour of their outfits. Called Recognition, the AI programme compares current photojournalism provided by Reuters with works from the Tate's collection to find its best match. It pairs the images based on image recognition techniques that analyse objects, faces, composition, and context gleaned from metadata. The AI matches a photo of eunuchs putting on makeup in Mumbai (Image: REUTERS/Danish Siddiqui TPX IMAGES OF THE DAY) with Sir Peter Lely's Two Ladies of the Lake Family c.1660 (Image: Tate) "We wanted to understand how we could bring artificial intelligence into a museum, and how rational and objective thinking could be applied to a subjective thing like art," said Angelo Semeraro of Italian research centre Fabrica. He and teammates Coralie Gourguechon, Monica Lanaro, and Isaac Valentin created the project to enter (and win) the Tate's 2016 IK Prize for digital innovation, which is run in partnership with Microsoft.

In this work, we analyze more than two million news photos published in January 2016. We demonstrate i) which objects appear the most in news photos; ii) what the sentiments of news photos are; iii) whether the sentiment of news photos is aligned with the tone of the text; iv) how gender is treated; and v) how differently political candidates are portrayed. To our best knowledge, this is the first large-scale study of news photo contents using deep learning-based vision APIs.