The Norval Sovereign African Art Prize 2022 Benefit Auction | Hosted by Sotheby’s

Mohamed Bourouissa

Network #07

No reserve

No Reserves

Lot Closed

February 22, 05:22 PM GMT

Estimate

7,400 - 8,500 USD

Lot Details

Description

Mohamed Bourouissa

French/Algerian

b.1978

Network #07

editioned 1 of 3 + 1 AP on accompanying certificate of authenticity

digital image generated by IA, printed on blue back paper

55 by 55cm., 21½ by 21½in.

Please be aware of the Conditions of Sale when bidding. As a benefit auction, there is no buyer’s premium charged. The only additional costs due to the winning bidder are applicable sales tax and shipping. Works auctioned are sold “as is,” and condition reports are included with lot descriptions as available. In-person previews of the auction artwork will be available at Norval Foundation at 4 Steenberg Rd, Tokai, Cape Town, 7945, South Africa from 26 January – 22 February, Monday to Sundays 9 AM – 5:00 PM (Closed on Tuesdays). Please note that while this auction is hosted on Sothebys.com, it is being administered by Norval Foundation (“the museum”), and all post-sale matters (inclusive of invoicing and property pickup/shipment) will be handled by the museum. As such, Sotheby’s will share the contact details for the winning bidders with the museum so that they may be in touch directly post-sale.

This work has been kindly donated by the artist

Mohamed Bourouissa (b. 1978, Algeria) is an artist who works through a long immersion phase, which is premised on the opportunity to articulate conceptual explorations across different artistic iterations. Bourouissa describes contemporary society implicitly, by its contours. With a critical take on the mass media image, the subjects of his photographs and videos are people left behind at the crossroads of integration and exclusion.

The Network series, based on the figure of Assa Traoré, aims to question the power and impact of political influence on social media. The image was generated using artificial intelligence. More precisely, a GAN (Generative Adversarial Networks) assembly that was fed images that Bourouissa selected. This GAN is made up of two "adversary" networks that have two different missions: the first, the generator, is in charge of generating "false" images, as close as possible to the example images of the dataset; the second, the discriminator, is in charge of distinguishing between false images and example images. As the algorithm works, a composite image is generated - representing a network of visuals.