The Butcher's Son

A GAN is a machine learning model that generates new data, such as an image, that resembles a given dataset. Developed in 2014, it consists of two neural networks: a generator, which creates a new image from random noise, and a discriminator, which evaluates the new image’s similarity to the training dataset. GANs “learn” by analysing many images to recognise patterns. As both networks improve, the process continues until the generator has produced an image almost indistinguishable from the dataset. The distinct aesthetic results of this process – the visible AI “artefacts” and the surreal, occasionally grotesque and non-human forms generated by the machine – are important for Klingemann as the complexity of the human figure challenges and reveals the limits of AI capabilities in the 2010s.

Mario Klingemann (b.1970) is a German artist who works with machine learning, code and algorithms, and is interested in generative and evolutionary art, data visualisation and robotics. Since learning programming in the early 1980s, he has explored human creativity, questioned the capacities of advanced technologies to emulate and augment these processes, and sought to understand and subvert the inner workings of opaque systems.