(Co)Presence:

Enfolded Response-ability and Relational Ontologies

Helen Colton

Absence has a palpable presence for those seeking truth and reconciliation in the wake of erasure. Struggles for visibility and representation are bound to the ontoepistemological and ethical implications of discursive practices. Karen Barad’s post-humanist theory of “agential realism” draws upon diffraction as a theoretical and performative modality for understanding phenomena as threaded through, not separate from, self and other. Presence and absence, past and present, nature and culture, matter and energy, human and non-human are co-present agents enfolded in a continual process of becoming. Rafael Lozano-Hemmer’s intra-active artworks, when considered through the diffractive lens of Barad’s theories, bring visibility to absence as an indicator of what is lacking or excluded from knowledge production and warrants representation. Public space is reimagined as a platform in which assemblages of biometric data, architecture, light and technology can initiate possibilities for absence to be (re)presented. These “situations,” as Lozano-Hemmer refers to them, reconfigure presence and absence in terms of co-presence and activate transcorporeal entanglements between the living, disappeared and otherwise missing. The artworks are performatively embodied and distributed across time, space, matter and memory to reveal traces of loss, exclusion and displacement. Intra-actions bring the artworks into being, evoking an openness to the ubiquitous alterity that is already, inextricably, iteratively constitutive of bodies (including but not limited to humans). Lozano-Hemmer’s “relationship-specific situations” are discursive practices in which co-presence is materialized and reconstituted within the artwork as an ongoing dialogue with absent others, prompting actions that attend to Barad’s call for “formulations of realism (and truth)” premised on the performative nature of post-anthropocentric response-able knowledge making.

Rafael Lozano-Hemmer, "Level of Confidence", 2015, face-recognition algorithms, computer, screen, webcam. Shown here: Montréal, Québec, Canada. Photo by: Antimodular Research.