After Image
Radical Networks 2019 Proposal
Format: [Artwork]
Name: [Aarati Akkapeddi]
Pronouns: [ She/Her/Hers]
Location: [NYC, NY]
Email: [aarati.akkapeddi@gmail.com]
Twitter: [@AaratiAkkapeddi]
Repo: [https://github.com/AaratiAkkapeddi/Radical_Networks_Proposal]
Url(s): [http://aarati.me/, http://aarati.me/project.html?project=project-after-image, http://aarati.me/project.html?project=project-after-image-risograph-prints]
Consent to being photographed?: [Yes]
Consent to being on the livestream?: [Yes]
Speaker Bio and Profile Picture
[Aarati Akkapeddi (b. 1992, Edison, New Jersey) is an Indian-American cross-disciplinary artist interested in the poetics and politics of datasets. She works with both personal and institutional archives to explore the ways in which identities and histories are shaped by different ways of collecting, preserving and presenting data. Currently, she is investigating the relationship between archival ethics and the creation of image datasets used in machine learning. Aarati has exhibited at venues such as The Java Project in Brooklyn and The Irregulars Art Fair in New Delhi. She is also an adjunct faculty at The New School.]
[I identify as being a woman of color in tech. I identify as being desi. I identify with the mission of organizations such as AI Now in shedding light on algorithmic bias and algorithmic censorship. All of these communities are important in the work that I do because they allow me to consider the complexities of ethics and technology in different ways. For instance, I do not uphold open-source/transparency as a universal solution as I feel that issues of ownership, appropriation, and cultural heritage call for a more nuanced approach.]
Note: Format for bio picture should be PNG/JPG/GIF, 256x256px.
Description
[After Image is an art installation comprised of a video piece and creative data visualization showcasing a series of experiments done with an archive of my own family photographs in relation to a larger archive of South Indian studio photographs from the Studies in Tamil Studio Archives and Society (S.T.A.R.S). Each of these experiments employs machine learning and computational techniques to sort, average, and analyze the images in order to surface semantic and visual patterns across the hundreds of images. With my experiments, I question the notion of collective and individual identity, and highlight the complexity of the image as a data point.
For the experiments, the images were first grouped by subject matter using a subject detection machine learning model and a clustering algorithm. Images were clustered around common composition, objects, or pose such as "two people standing", or "one person sitting one person standing", or "babies and rocking horses." These clusters are shown on the table around the central video component in the form of an intricate mapping of images. Each group is represented by a cluster of its individual images around a central node image, which is a computational averaging of all the images within the cluster. These averaged or ghost-like images, meant to represent each cluster, are also shown in the form of gold prints on the wall. The video component shows my own family photographs in relation to the larger archive.
After Image highlights images as data and their influence historically with photography as well as in the present with computer vision technology, and particularly in how they shape identity on both the individual and a collective scale. ]
Note: Panels should follow a moderator / discussion format, with possible participation from the audience.
Artwork installation requirements (if applicable)
[outlet, 3 x 4ft floor space, and wall space as well (4ft wide)]
Artworks must be installed on Friday October 18th, 2019.
Note: We are not responsible for damages done to your work! (Although we will take every precaution we can to safely handle your work.)
Additional Info / Links / References
[https://github.com/AaratiAkkapeddi/Radical_Networks_Proposal/tree/master/Images:Video%20Documentation, https://github.com/AaratiAkkapeddi/Radical_Networks_Proposal/tree/master/Paper]
