This is the Problem, the Solution, the Past and the Future

2017, Conceptual dataset for machinge learning and machine vision,
commissioned by The Photographers' Gallery,

This is the Problem, the Solution, the Past and the Future is a conceptual dataset for machine learning and machine vision: In Decision Space, Visitors of the website of The Photographers’ Gallery were invited to assign all the images available on the website to one of four categories: Problem, Solution, Past and Future. This assignment process of almost 30.000 makes it possible to teach computers how to understand images within this set of concepts.

The dataset consists of 2.931 photos and includes artists like Cindy Sherman, Jacques-Henri Lartigue, Elliott Erwitt, Sebastião Salgado, Weegee, Valie Export, Francesca Woodman, Simon Fujiwara, Trevor Paglen and many more. Furthermore, the dataset contains the complete data generated through Decision Space (for each image: amount of clicks per concept, original url, and url of the webpage on which the image is embedded).

It raises a series of questions: How do we make decisions? What can we agree on? Can we agree at all? Can we teach machines to understand meaningful and complex concepts? What happens when machines are used to identify problem and solution, or to discard something or somebody as the past, and to identify and privilege somebody or something else as the future?