This event is part of our Past Programme
For this multi-part project, Ridler constructed a visual dataset using images and texts from Victorian and Edwardian-era encyclopaedias to show how historic taxonomies and cultural beliefs continue to dominate the way we organise the world - and influence machine learning.
One element of Laws Of Ordered Form presents a series of digitised images drawn from encyclopaedias and shown alongside a range of captions and descriptions. These pairings draw attention to the way images are used to reinforce and perpetuate racist, colonial and exoticising ideologies from that era. The images are then decontextualised from their initial categories and placed in a new semantic order by Ridler in imitation of how an algorithm might ‘arrange’ them. By collapsing historical knowledge with today’s current concerns around dataset bias, the piece emphasises both the problems with classification and the histories that remain in our present.
Ridler’s interests also lie in exposing the human labour behind digital content production and the intensive and repetitive processes required. The arduous and solitary work of reading, selecting and scanning the images and texts makes up another chapter of Laws Of Ordered Form, and lies in stark contrast to the accelerated, underpaid and crowdsourced micro-tasks demanded by large technology companies to create datasets. By reimagining and exhibiting the process involved, Ridler reveals the hidden and rarely considered subjectivity behind such labour as well as exposing the inevitable politics that accompany them.
Together with the work at the gallery, a selection of the photographic scans were made available to download in a .zip folder for the duration of the exhibition. The images have been arranged in hierarchical folder structure, with an aim to explore and re-categorise the images.
Anna Ridler is an artist and researcher who works with information and data. She has exhibited at the V&A Museum, Ars Electronica and the Barbican and has degrees from the Royal College of Art, Oxford University and University of Arts London. Her interests include drawing, machine learning, data collection, storytelling, and technology.
This work is a new commission as part of Data / Set / Match, a year-long programme exploring the technical, cultural and social significance of image datasets and the way that photography has been operating within them.