We present preliminary indications from an examination of the relationship between stimulus fixation and subsequent motor activity in art drawing. We utilize eye-tracking technology to observe the complex vision cycles of an artist's drawing process, and a digital drawing tablet to capture motor activity. Early results suggest that deeper investigation of the relationship of eye and hand movement during artistic drawing may help to extend access to cognitive processes involved in the behavior and embodied response of artistic practice. We propose that a synthesis of phenomenological and technological modalities helps extend creative interactivity in computationally mediated self-expression.
This article presents a phenomenology of artistic painting as an anticipatory process. I propose that the artist seeks to establish a state of equilibrium in a model of self-awareness expressed and represented in a self-constituted physical artefact intended to communicate to others,
not representationally but affectively. ‘Neural painting’ is an arts-based research method employing a simple computational model of human aesthetic discrimination to study the creative realization of the artistic image. I use this method to explore the relationship of self and
‘other’ in computationally mediated self-portraiture. I develop an image in an exchange with a neural network by reflecting on its output and inputting autographic modifications to those images, blending visceral gesture with the ‘black box’ of artificial intelligence.
Through this deeply personalized and perhaps agonistic interchange between organic self and algorithmic reflection, I seek to expose the tacit mediation implicit in the technical artefact, opening an understanding of the existential relations between natural systems (the artist) and technical
entities positioned as collaborators in an anticipatory aesthetics.
Recent developments in neural network image processing motivate the question, how these technologies might better serve visual artists. Research goals to date have largely focused on either pastiche interpretations of what is framed as artistic “style” or seek to divulge heretofore unimaginable dimensions of algorithmic “latent space,” but have failed to address the process an artist might actually pursue, when engaged in the reflective act of developing an image from imagination and lived experience. The tools, in other words, are constituted in research demonstrations rather than as tools of creative expression. In this article, the authors explore the phenomenology of the creative environment afforded by artificially intelligent image transformation and generation, drawn from autoethnographic reviews of the authors’ individual approaches to artificial intelligence (AI) art. They offer a post-phenomenology of “neural media” such that visual artists may begin to work with AI technologies in ways that support naturalistic processes of thinking about and interacting with computationally mediated interactive creation.
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