Through a very wide lens, Emergent Topographies is a video installation and a collaborative digital artwork that deals with current clinical elements of the spatiotemporal ecosystem of data objects, topographically demonstrated through geodata and biodata examined by artificial intelligence.
The artwork explores the artistic applications of artificial intelligence, specifically using a generative adversarial network (GAN). The data that is generated is ultimately illustrated using an agent-based behavioral algorithm to visualize the morphing behavior using the mapping aesthetic of a connectome.
Emergent Topographies is grounded within the territorial context of the Arabian Peninsula, where, for centuries, the inhabitants have simultaneously designed and been designed by their context. From caves and mud-brick constructions to urban environments and high-tech, highly dense modern urban conglomerations, the culture has not just shaped the context; it has been progressively shaped by it. Hence, the two main interactors are context – represented as topography – and culture – represented as brain activity data.
Gradually constructing the anthroposphere, the context/culture amalgam becomes a necessary space for exploration within an increasingly hybrid world. GAN-generated topographies that encode electroencephalography (EEG) data are produced as future topographies, of human and machine in significant contextual coexistence.
Cultural progress always happens within the available technosphere and frequently expands it. Technologies, such as fire, stone hunting instruments, or borrowing other animals’ fur have gradually channeled human evolution physiologically and socially. In parallel, the physical context – i.e., the land, with all its features – has had a humongous impact on its inhabitants’ social patterns, diets, behavioral norms and culture. In turn, by expanding their technosphere, civilizations have been able to give form to new contexts, which they inhabit.
Intelligence, be it biological or mineral, is at the core of a great number of the current scientific and interdisciplinary endeavors. In this project, it is also the main topic at stake: Emergent Topographies rounds up the central role of artificial intelligence and neurotechnology (namely EEG) as a way to reinterpret silicon topologies from the Arabian peninsula. Two main data objects have been used as inputs for the process at different stages.
Geographic Information System (GIS) Data is collected from random coordinate locations within the Arabian Peninsula and mapped as the first and core data object for the work. The data collected was mapped topologically and textured for further exploration, while maintaining a topographical three-dimensional representation as an output. Working on several representation methods throughout the process, data has been compressed to grey-scale two-dimensional depth maps, simple arrays of point cloud coordinates, and axonometric visualizations.