Learning Machine

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This work was made on the unceded land of the Kaurna people, and presented on the land of the Wurundjeri and Boon Wurrung people of the Kulin Nation.

Words by Gabi Lane

Who is the learning machine?

Is the art a learning machine? Perhaps the exhibition is the learning machine? Or even the artist himself? Dave Court is certainly an artist who strives towards knowledge and understanding; of new ideas, of technologies, of modes of digital and analogue communication. In many ways he is the original learning machine, one who can still recall the shrill tones of dial-up internet but also understand how his iPhone knows what ads to conjure in his feed. So how might an artist with such a predilection for learning, provide us with any answers? Simple. He doesn’t. Instead, he puts forward information and empowers us with ideas.

The exhibition Learning Machine presents us with work that is as multiplicitous in its form as it is in the meaning it embodies. Encompassing laser-cut paintings, Virtual Reality drawings, DALL-E interventions, projection, and infinite scrolls of painting, Court offers an overwhelming abundance of media and the information these hold. Rendered in vibrant colours, moving shapes, and melodic sounds, Learning Machine is indeed an onslaught of information. Taking its cue from the algorithms and data collection of the World Wide Web, which is itself a deep well of encyclopaedic knowledge, this exhibition is indulgent in its excess.

Dave Court cleverly utilises digital techniques in both his conceptual starting point and the processes of making. Referencing Aza Raskin’s web-design technique of the infinite scroll, where content automatically and continuously loads as the user scrolls down the page, Court has created an endless loop of painting titled Infinite Scroll.1 We watch with rapt attention, perpetually enticed by the possibility of something new appearing in the next nano-second. This is the power of the infinite scroll; it is designed to be addictive, to lure you in and encourage you to keep watching and scrolling.

Upon entering, the feeling of immersion is instantaneous and your senses are heightened as attention is drawn to the different parts of the exhibition. We become more attentive to the seemingly random unfolding moments generated by the works themselves.

1 Knowles, Tom, 2019, “I’m so sorry, says inventor of endless online scrolling”, The Times, accessed August 2022 <https://www.thetimes.co.uk/article/i-m-so-sorry-says-inventorof-endless-online-scrolling-9lrv59mdk>

But painting is just the starting point for Court. Indeed, this is certainly the case for his series of paintings, in which digitally rendered versions of the same work sit across from their physical counterparts, referencing the process of their construction. Half of these counterparts can be viewed as a display of machine learning. They were born using the artificial intelligence program DALL-E, an Artificial Intelligence (AI) model that was trained on a set of images drawn from the entire internet and now exists as a standalone repository.2 Placed in juxtaposition with one another, the first gestural loop straight from the artist’s hand and the second digitally derived from an input of visual cues, they spark a conversation between analogue and digital. Like DALL-E, our brains are wired to make sense of seemingly disparate bits of information. We seek to collate information from our past experience and existing knowledge, to find connections and form them into a larger coherent narrative.

But online platforms do not neatly present information to us in the way that a traditional book or a ‘Dummy’s Guide’ might, instead it is a chaotic assemblage put together by computer calculated algorithms. By exercising online literacy in engaging with these platforms, we are training our brains to assemble a story using fragments of information. In this exhibition, we are invited to implement these skills and take on the role of learning machine.

2 DALL-E is a multimodal form of the GPT-3 language model, created by Open AI, with 12 billion parameters trained on text-image pairs from the internet. In response to prompts, DALL-E generates multiple images which are then ranked by CLIP – a neural network and image processor trained on over 400 million image-text pairs.

Depending on how these sculptural forms are arranged and rearranged, the effect varies from melodic tunes to frenetic and jarring tones.

The spatial arrangement further implicates us as an active participant as we are required to negotiate around and through the installation of painted foam objects. Recalling Nicholas Bourriaud’s relational aesthetics of the late 1990s, we are encouraged to pick-up and move the brightly coloured sculptures that are arranged in a grid on the gallery floor. Court creates what Bourriaud would refer to as a ‘microtopia’, filled with relational objects, in which interactivity and experience are central.3 When one of the forms is moved, the soundscape alters and changes responsively.

If our brains are hardwired to collate information together in a satisfying harmonious way, then it would make sense for us to arrange the sculptures to elicit this effect. But, just as you can never truly predict what will happen in the next moment, you can never anticipate exactly what the outcome will be – therefore presenting the possibility for unbridled disorder. Regardless of the outcome, this process instils a sense of power in the individual, giving the impression that one is able to find and create something new by their own intervention. By this interactive process, we are implicated in the production of the work and, by extension, in the production of meaning.

3 Bourriaud, Nicholas, 2002, Relational Aesthetics: Collection Documents sur l’art, Le presses du reel (1998) pp. 13-25

These works ultimately rely on audience contribution for their continued creation, reproduction, and evolution. Technology is not only the subject but the means. As we move through the space, so too does the projection cast on the wall of the gallery. The projection responds in real-time to our motions in the space and transforms before our eyes in swirling colours and abstract shapes. Abstract and non-representational, our brains scramble to process the dazzling visual effect. With his paintings and objects, and then through video installation, Court explores the processes by which technology mediates our everyday experiences through exposure to and reliance on digital interfaces. Indeed, he inaugurates us into an interactive relationship with the works. The machine is learning from us and us from it.

Gabi Lane is an independent curator and arts writer working on Kaurna Country/Adelaide, with a MA in Art History & Curatorship.

Words by Freya Langley

Can AI generate “good” art? The advent of AI has been viewed as a threat to the creativity, ambiguity, spontaneity, and uncertainty which are hallmarks of our humanity. The launch of AI image generators has been met with backlash from artists who fear that the technological development threatens their autonomy and creativity. Through Learning Machine, Dave Court explores the collapse in the dichotomies of digital and analogue, the predictable and the unprecedented, and the blurring of lines between human and machine. In so doing, he opens questions around the convergence of physical and virtual worlds, and it’s impact on our understanding of ourselves and our realities.

For this body of work, Court was granted access to DALL-E, an AI tool that generates images based on text input, as well as creating variations of images uploaded. Trained on a massive collection of pictures and text descriptions, DALL-E not only recognises images, but understands their relationships to other objects and actions; and demonstrates that when prompted by text. Like humans, DALL-E is the sum of its experiences and relations. However, while we continue to experience growth and change, DALL-E is frozen in time; it only knows and understands through the snapshot taken when its training dataset was collated.

AI, like the phonetic alphabet or the computer, is an “extension of man that causes deep and lasting changes in him and transforms his environment” 1. If we view AI as an extension of ourselves, all AI, including DALL-E, inextricably contains the biases and subjectivities of those who program it. Objectivity and ambiguity are therefore unattainable goals because humans are the sum of all of their experiences, relations, and social contexts, the AI we teach is too. Indeed, AI is widely criticised for its lack of ambiguity and its reproduction and reinforcement of unequally distributed social orders and how this privileges a few, subjecting many to injustice.

How is it possible to create something new? AI-generated art raises questions of authenticity, legitimacy, process and purpose – surrounding the artwork and its creator. Learning Machine explores the space in between human creativity and the

(im)possibility of machine creativity and what it means to exist in a world that is at once analogue and digital. “Creativity stands in stark opposition to certainty and predictability. It requires unexpected and spontaneous behaviour and not repeating past patterns and trajectories. Creativity, by definition, defies expectation”2 Thus, if creativity is something that is unprecedented and unimagined prior, AI is then inherently uncreative. Its knowledge is bound by the strictures of what it has been trained on, its understanding frozen in time. It is unable to account for the messiness and unpredictability of human variables, and therefore only holds the ability to replicate the past in the future, or to make the future an extension of the past.

1 Marshall McLuhan, “The Playboy Interview” Playboy Magazine; 1969 (modified and redacted by Philip Rogaway 1994) 2 Alicia Juarrero, “Dynamics in action: Intentional Behavior as a complex system” Emergence; 2000; 2(2), 24-57 quoted in Abeba Birhane “The Impossibility of Automating Ambiguity. Artif Life 2021; 27 (1): 44–61

Does AI’s ability to generate art make the artist expendable? AI holds the ability to remix and replicate, but it cannot behave with the requisite originality and spontaneity to be considered a creative entity. AI, therefore, appears to stand in direct opposition to creativity. However, Court complicates this, through collaboration with DALL-E. ‘Collaboration with’ rather than ‘use of’ is a tongue-in-cheek distinction Court makes – blurring the lines between artist and forger and poking fun at popular conceptions which humanise AI as a “smart guy inside a computer”. In his view, DALL-E is an extension of himself and his creative practice - a tool no different to the paintbrushes and laser cutters used to create physical works.

It represents the convergence of analogue human movements, and their digital representations. Court’s VR gestures, and DALL-E’s recreations of them are near indistinguishable from each other; except to those familiar with the language of the media. Court’s work is an attempt to make audiences conscious of the AI medium, prompting them to consider the meaning contained within it. After all, as McLuhan asserts, the medium is the message.3

Learning Machine is a creative use of a tool that is inherently uncreative – an augmentation of the artist’s creative capacity, rather than a replacement. Court’s Loop Gestures, for example, are based on organic, human gestures, created in VR, and reproduced by DALL-E. 3 Marshall McLuhan “Understanding Media; the Extensions of Man”. New York :Signet Books, 1966.

But what is the message that the medium of AI-generated artwork carries? The influence and impact of media, such as AI, is not to be underestimated. It matters that part of this work is created by AI and it matters that Court and DALL-E’s works are nearly indistinguishable from each other. This signals a “revolutionary environmental transformation” that we ought to be prepared for. Already, there are very real concerns that this kind of technology runs the risk of human replacement (among a barrage of intellectual property and ethical concerns – especially its reinforcement of societal biases and injustice). Learning Machine reminds us that while AI is an extension of us, it cannot fully replace or replicate us - in all our messy complexity, unpredictability and variability. As Birhane writes, “Automation as complete understanding, therefore stands at odds with human behaviour, which is inherently incomplete, making machine classification futile”4 4 44–61.

Abeba Birhane “The Impossibility of Automating Ambiguity” Artif Life 2021; 27 (1):

Learning Machine is also a reminder that “We are not only responsible for the knowledge that we seek but, in part, for what exists”5. As humans, we are wholly responsible for the social realities we create – whether they are embedded within AI or reinforced through interaction. It is also a reminder that human creativity, which is key to reimagining our world and our relationship to the digital, cannot be programmed or replicated. Learning Machine is not necessarily a cry for resistance to AI and machine learning, but a call for consideration of its role, use and impact. Court views it as a learning experience, a lesson in the language of AI and an attempt at understanding it. For as McLuhan writes, “If we understand the revolutionary transformations caused by new media, we can anticipate and control them; but if we continue in our self-induced subliminal trance, we will be their slaves.”6

Freya Langley is a writer, researcher, and media and cultural studies scholar based in Meanjin (Brisbane, QLD)

5 Karen Barad “Getting real: Technoscientific practices and the materialisation of reality” Differences: A Journal of Feminist Cultural Studies; 1998; 10(2) 87-91 quoted in Abeba Birhane “The Impossibility of Automating Ambiguity” Artif Life 2021; 27 (1): 44–61. 6 Marshall McLuhan, “The Playboy Interview” Playboy Magazine; 1969 (modified and redacted by Philip Rogaway 1994)

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This body of work was made in collaboration with, assistance from and gratitude to: Arlon Hall Anthea Schubert Backwoods Gallery Bel Caruso Benen Hamon Chiara Graetz DALL-E

Freya Langley Gabi Lane Hari Koutlakis Ismail Alizada Jimmy Dodd Matt Fortrose Max Brading

Michael Carney Miles Dunne Motez Reuben Gore Rosina Possingham Sam Rosenzweig Tom Groves