Newsfeed by Anastasia Kulagina won both the vote of the visitors of our online exhibition and the vote of the professional judging panel.
Anastasia’s project, based on the work of neural networks, deals with the problem of trust in fake news and the surrealism of events, in which you can’t tell the difference between meme and news, or sarcasm and reality.
This is how Anastasia described her artwork in the submission for the contest:
“Reading the news has become a dangerous and energy-consuming way to spend time lately, it raises anxiety, causes panic. Looking for reliable sources of information in the post-truth era becomes more and more difficult. This project brings up the issue of trusting fake news and surrealism of the current events, when a meme is indistinctive from a piece of news, and sarcasm from reality.
All images were generated by a neural network on the basis of descriptions with the ruDALL-E Malevich model by Sber. The descriptions themselves were generated by another neural network — Russian model GPT-3 that had been trained on a dataset of publications by Meduza, Lenta, Breakingmad and Radio Adonezh. By these means I project the machine’s view onto a flat surface to show an abstract image of modern Russia, where the issue of corruption is interpreted in a distinctive way. These images with titles are just a material. The project can live on as a news telegram-channel or indefinite news feed with pictures and inscriptions.”
Watch a short interview with Anastasia, in which she talks more about her work and shares her impressions of our online exhibition:
Member of the judging panel of anti-corruption contest Fighting Corruption with Art Marat Guelman discussed ways in which artists can portray corruption and art can make a contribution in civil society in an interview with journalist Denis Kataev on the YouTube channel “Bakaleyko and Kataev”: