Dataset of Loss - Fabienne Hess

If algorithms are doing more and more seeing, then what distinguishes human engagement with images? 

Algorithms are trained on labelled datasets. They see only what they are told that images depict, remaining blind to images' histories, associations, and metaphors. The organising principle of the images collected here - the theme of loss - is not a label stating what they depict. The images in the Dataset of Loss ask questions about origin and content while resisting easy categorisation. They require curiosity to be seen. 

Fabric frays, names are lost, objects discarded. Images of fleeting moments, such as wave in full crest, reflect the continuous vanishing of the present. This image sequence is an exploration of ways in which to understand loss visually. It is also an enquiry into algorithmic ways of seeing and the profound loss of vision to which these new processes lead. 

Edition Fink, 2024
Softcover card folder with image index, texts and 5 loose fold-out poster sheets. 
Text by Alice Hattrick. 
300 x 200mm