The techno-ecological practice as the politics of ontological coalitions

The paper focuses on the art projects aimed at visualizing (grasping) the physical or biological phenomena through interfaces and / or installations designed specifically for such purpose. Such works often mirror the post-­digital condition of our time where the digital technologies constitute the common background for everyday activities, no longer having the allure of "new" and "exciting" (Berry, Dieter et al., 2015). In this process, both the networked technologies of wireless communication and the act of crossing the boundaries between the digital and the physical play the crucial role as the post-­digital networked imagery increasingly becomes directly connected to the physical environment. I would like to ponder on the questions of processuality and relationality involved in such instances where the complexity of the hybrid works of art clearly transgresses the paradigm of representationalism (Thrift, 2008;; Anderson and Harrison, 2010;; Kember and Zylinska, 2012). The particular attention is given to the fact that such artworks bond different ontological realms (discursive, physical, digital) and different agents (human and non-­human, carbon-­based and software-­based) forging “ontological coalitions” (Malafouris, 2013). Throughout the article the mutlirealist and relational perspective is offered, inspired by the propositions of Gilbert Simondon and Etienne Souriau. Based on the research project supported by National Science Centre Poland ("The aesthetics of post-­digital imagery: between new materialism and object-­oriented philosophy", 2016/21/B/HS2/00746)

The deception of an infinite view – exploring machine vision in digital art

This paper examines prediction product called Queryable Earth a project to “make Earth searchable for all”. A project pitched by the company Planet, owner of the largest fleet of Earth-imaging satellites in orbit and an archive of satellite images growing with terabytes of fresh data every day. The aim of Queryable Earth is to combine geospatial intelligence with machine learning. By training artificial neural networks to classify objects, identify geographic features, and monitor change over time, the implied intention is to create a predictive, omniscient oracle. In this paper Queryable Earth functions as an example of a ‘nonconscious cognitive assemblage’ combining aerial image with machine learning techniques such as artificial neural networks. To examine the predictive potential and the assumed objectivity of machine vision systems such as Queryable Earth I turn to histories of aerial photography and examples of contemporary digital art to illustrate how human and technical cognition entwine revealing how seemingly automated processes such as rendering of satellite images and pattern recognition still inherit human biases and are prone to emphasize them. Furthermore, I use digital artworks to illustrate how Queryable Earth as an “all seeing machine” is limited to a singular aerial perspective which cannot penetrate the surface and how predictions produced by such systems are constrained the quality and selection of data they are trained on