ANNA RIDLER
Anna Ridler (b. 1985) is an artist and researcher who works with information and data. Born in London, Ridler spent her childhood raised between Atlanta, Georgia and the United Kingdom. A core element of her work lies in the creation of handmade datasets through a laborious process of selecting and classifying images and text. By creating her own datasets, Ridler is able to uncover and expose underlying themes and concepts while also inverting the usual process of constructing large databases. Her interests are in drawing, machine learning, data collection, storytelling, and technology.
Ridler holds an MA in Information Experience Design from the Royal College of Art and a BA in English Literature and Language from Oxford University along with fellowships at the Creative Computing Institute at University of the Arts London (UAL). Her work has been exhibited at cultural institutions worldwide including the Victoria and Albert Museum, Tate Modern, the Barbican Centre, Centre Pompidou, HeK Basel, the ZKM Karlsruhe, Ars Electronica, Sheffield Documentary Festival and the Leverhulme Centre for Future Intelligence. She was a European Union EMAP fellow and the winner of the 2018-2019 DARE Art Prize. Ridler has received commissions by Salford University, the Photographers Gallery, Opera North, Live Cinema UK and Impakt Festival. She was listed as one of the nine “pioneering artists” exploring AI’s creative potential by Artnet and received an honorary mention in the 2019 Ars Electronica Golden Nica award for the category AI & Life Art. She was nominated for a “Beazley Designs of the Year” award in 2019 by the Design Museum for her work on datasets and categorisation.
Ridler lives and works in London.
SOLD OUT
TRUTH TO NATURE FLOWER IV
NFT + PLOTTER DRAWING
by Anna Ridler
2022
Edition 4 of 4 (+ 2 AP)
Unique plotter drawing with watercolored background
Paper size: 35x55cm
Signed by the artist on front
Unique NFT minted on FoundationApp
The practice of making scientific images has a long history and these works reface this. The objects chosen are those that occur frequently in the history of natural history and collecting. Each one is part of my studio and used to test and experiment with different types of emerging technologies. The drawings that are being presented have used various different types of machine learning (a series of GANs, NeRF) which have then been passed through a further series of image making techniques - the results of which can be seen in the different editions (that move between the digital to the analogue - drawing, painting) - to include or exclude new information and datapoints. As Lorraine Dalston writes, each image, no matter how scientifically rendered contains “traces of consequential choice about knowledge, persona and collective sight”. The work also includes an SVG file so that, if desired, further illustrations can be made and experimented with, and questions whether any image can truly be objective.
The NFT will also serve as the certificate of authencity for the physical drawing.