Re-imagining ‘Instrumental’

Instrumental began life as an experimental digital interface combining data drawn from social media, geolocation, automated facial recognition and face tracking to turn a user’s facial expressions and evaluative data input into a tonal instrument. In many ways, it grew out of two individual research-based creative practices (Smith and Blignaut) and was the first attempt to enact a crossover of some shared interests. You can read about it here.

Between the completion of an MA Fine Arts (Blignaut) and the end-stages of a PhD analysing the cultures and practices of Forensic Art (Smith), we decided that its first interation as an interactive artwork failed; there was too much going on both within it and outside it. But a recent residency at A4 Art Foundation (Cape Town, South Africa) provided the opportunity to reflect on Instrumental in the context of other projects both past and current, and what it should become instead.

So we moved it here, to a blog that will act as a repository for thoughts, ideas and resources that circle around the face as a technology of both identity and identification, and the ethics of how the face is deployed in contemporary technoculture. Some ideas from artist Trevor Paglen get to the heart of it:

…visual culture has changed form. It has become detached from human eyes and has largely become invisible. The overwhelming majority of images are now mady by machines for other machines, with humans rarely in the loop. Human visual culture is now an exception to the rule. … Images have begun to intervene in everyday life, their functions changing from representation and mediation, to activations, operations, and enforcement. Invisible images are actively watching us, poking and prodding, guiding our movements, inflicting pain and inducing pleasure.

If we want to understand the invisible world of machine-machine visual culture, he says, we need to unlearn how to see like humans [our emphasis]. We need to learn how to see a parallel universe composed of activations, keypoints, eigenfaces, feature transforms, classifiers, training sets, and the like. But it’s not just as simple as learning a different vocabulary. Formal concepts contain epistemological assumptions, which in turn have ethical consequences. The theoretical concepts we use to analyze visual culture are profoundly misleading when applied to the machinic landscape, producing distortions, vast blind spots, and wild misinterpretations.

Trevor Paglen (2016) Invisible Images (Your Pictures Are Looking at You). The New Inquiry, 8 December, 2016.

Thinking about experiments as holding spaces…

Across different computer vision and machine learning techniques, the face is a central motif or space where ‘personhood’ is replaced by pattern-matching. As a biometric, the face becomes a paradox, embodying both absolute individuality and a negation of the Self. Contemporary advances in machine learning are increasingly blurring distinctions between the visual and the algorithmic in applications that range from investigative or security-driven applications to social media, with paradigm-shifting effects. The face thus presents itselfs as a space of new kinds of negotiation.

The face as technology seems to us to be a particularly potent focus in the contemporary moment, because as humans we not only project so many of our assumptions about identity onto the face, we also invest it with much of our hopes and expectations about what it does or should mean to be human. Its presence, to think along with Emmanuel Levinas, is felt as a kind of receptacle for the formlessness that permeates the tragic and the everyday of our lives.

Welcome, and thanks for being here. We see you.

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