This text argues for the potential of machine learning infused classification systems as vectors for a technically-engaged and constructive technology critique. The text describes this potential with several experiments in image data creation and neural network based classification. The text considers varying aspects of slippage in classification and considers the potential for discovery — as opposed to disaster — stemming from machine learning systems when they fail to perform as anticipated.

The emergence of new AI algorithms in recent years, especially those concerning deep learning, brings new challenges to the sphere of art, chang-ing how artists creatively use computer systems. Although AI is not new in the universe of art, the new scenario makes it possible for algorithms to produce new types of automated images. Given this picture, this paper proposes to shed some theoretical and practical lights on the processes employed in the generation of visual art using AI. We start exploring the very nature of computer images, having as a theoretical framework the ideas of Dietmar Kamper (1936-2001), Hans Belting (1935-), Christoph Wulf (1944-), and Vilém Flusser (1920-1991). Next, building on this conceptual exploration, we describe the process of using deep learning techniques to generate self-portraits, which are synthetic images pointing to an external index.

Despite regular navigational applications, geographic maps possess a strong aesthetic dimension that can be entirely separated from utilitarian tasks and purposes. We present a computational system that uses neural style transfer and open-access geographic data to generate stylised maps from any region in the world customised in the style of any given image. We showcase and analyse output maps generated by the system while offering insight into how changes to the inputs can result in clearer and more unique outputs. Finally, the real-world applicability of the output maps is addressed, leading us to conclude that they are a viable way to aesthetically establish connections to geographic places, which can happen through their application in purely decorative or more meaningful design contexts.

Reflecting on digital poiesis and what can be thought of as 3D phantasmago-ria, this paper puts forward some considerations about urban media ecologies, focusing on those that dwell directly on space. Considering visual culture indexes such as Face-Filters and the popularization of material simulation and maximalist neu grunge, computer-aided three-dimensional rendering — and its interlink with decentralized computation — will be seen as new spectra for contemporary geographies.

This text aims to create a discussion for socio-spatial justice revolving as a critique of Platform Capitalism and its ability to render power. Neither as a portal for other worlds or a long-lasting overlay, digitality rays out, glimpses from within the surfaces of material reality having 3D as a language negotiator. If the industrial machinery, the prison, and the screen designed the imaginary and social contracts of western modernity, the biopower of algorithms utilizes all space and users’ bodies as quantifiable devices and exploitable resources–feeding augmentations judged desirable.