With the widespread application of IoT, Big Data and AI in animal husbandry, one might say that the modern dairy cow's evolution is governed by algorithms. But what will the cow of the future look like if its evolution is to be controlled entirely by computer programs and managed according to selection principles that prioritise cows' compatibility with technology and their efficiency in serving economic objectives?
The project Generation (2021–2023) follows a speculative attitude to reflect on this issue and raise questions about humankind's relationship to nature and technology. It projects various evolutionary trajectories of cows using GANs (Generative Adversarial Networks) trained on thousands of images of Holstein Friesian cattle obtained from sire directories and semen catalogues.
The project Generation (2021–2023) follows a speculative attitude to reflect on this issue and raise questions about humankind's relationship to nature and technology. It projects various evolutionary trajectories of cows using GANs (Generative Adversarial Networks) trained on thousands of images of Holstein Friesian cattle obtained from sire directories and semen catalogues.
The resulting ever-evolving visual is presented on a holographic LED fan; a device referring to disembodiment and virtualisation while evoking the giant air conditioning fans at dairy farms and associating global temperature rising. Simultaneously, the fan creates a monotone, mechanical soundscape to the work.
Generation is a project by the artist Daniel Szalai, developed and realised together with Dániel Rácz and Marcell Mesterházi with the support of the European Union project RRF-2.3.1-21-2022-00004 within the framework of the Artificial Intelligence National Laboratory Program and the Artificial Biology, Robotics and Art "ABRA" project supported by the Erasmus+ programme of the European Union. Further support from the Goethe-Institut Munich, Library and Information Department.
Generation is a project by the artist Daniel Szalai, developed and realised together with Dániel Rácz and Marcell Mesterházi with the support of the European Union project RRF-2.3.1-21-2022-00004 within the framework of the Artificial Intelligence National Laboratory Program and the Artificial Biology, Robotics and Art "ABRA" project supported by the Erasmus+ programme of the European Union. Further support from the Goethe-Institut Munich, Library and Information Department.
