Reflection : Art in the Age of Mechanical Creativity

In 1935, Walter Benjamin penned his seminal essay, The Work of Art in the Age of Mechanical Reproduction, where he explored the profound effects of technological advancements in the creation, distribution, and perception of art. Benjamin argued that the ability to mechanically reproduce art has not only altered its cultural significance but also led to the erosion of its aura, which is the unique, unrepeatable essence that a work of art possesses due to its existence in a specific time and place.

Today, as we stand in the middle of another technological revolution, where the questions Benjamin brought up are relevant more than ever. The rise of artificial intelligence and the advent of mechanical creativity—where machines not only replicate but also generate artistic content—present us with new perspectives to explore and challenges to tackle. Just as photography and film transformed the art landscape in Benjamin's time, AI is reshaping the way we think about creativity, authorship, and the function of the artist.

Pindar Van Arman’s work centers itself on these questions by posing a related question.

What is the work of art in the age of mechanical creativity? 

More specifically, Van Arman, a classically trained painter, asks if AI can utilize a creative process to paint like a human? And if so, ask the deeper question of what that means to us as humans? Van Arman wonders if in the process of exploring synthetic creativity, we humans end up learning to see the world from an algorithmic perspective, and in doing so learn more about how our own minds and emotions work. Over 20 years of deep diving into these curiosities have pushed Van Arman’s artistic practice and approach to art making to an area where he uses artificial intelligence to make artworks about being human in the age where humanity is being imitated by algorithms.

Influenced by Minsky’s Society of Mind concept, Van Arman approaches creativity as something that is not a singular process but multiple ‘agents’ working simultaneously to discover emergent ways of seeing. Van Arman’s Reflective AI uses multiple algorithms that evaluate the structural, dynamic and aesthetic elements of the artwork as it is being created. These algorithms respond to the changes in real time, taking constant input from the entropic variation between the algorithmic intent and the unpredictable physical outcomes of each brushstroke. The ultimate goal of this approach is to create a synthetic embodiment of creativity, a system that replicates the reflective processes of an artist engaging with the canvas.

Central to his explorations is the concept of feedback. Early on, Van Arman faced a critical issue which he summarizes as, “My algorithms were painting blind… Instructions were sent to the robotic head but it painted with no feedback from how it was executing the painting…. To put this into perspective, try closing your eyes and drawing. Now open your eyes and do the same drawing. The difference in quality should be obvious”. To solve this problem, he introduced cameras and responsive algorithms to the robotic system, which enabled it to not just ‘see’ the work but also to respond to the changes instead of simply iterating. From this early basis, he has gone on to fine-tune his feedback loops around increasingly nuanced and reflective algorithmic decision-making processes.

Van Arman’s unique conception of synthetic creative feedback loops is deeply influenced by Paul Klee’s  writing on the painting process as a continuity. In his 1925 Pedagogical Sketchbook, Klee describes a creative process as a feedback loop : “Already at the very beginning of the productive act, shortly after the initial motion to create, occurs the first counter motion, the initial movement of receptivity. This means: the creator controls whether what he has produced so far is good. The work as human action (genesis) is productive as well as receptive. It is continuity.” Van Arman’s work attempts to translate this perspective to AI and machine creativity in order to discover new ways of seeing that are unique to computational creativity.

Another major influence on Reflective AI is Harold Cohen, with whom Van Arman was in correspondence toward the end of his life. One of the limitations to computational creativity that Cohen highlights was the deterministic nature of computing processes. In his essay “Parallel to Perception” he writes:  

By definition processing is a deterministic affair, and for any single run its functions are predetermined and invariant. Feedback from the result to the functions themselves has no part in this process. On the other hand feedback is clearly a part of the human art-making process, or indeed of any intelligent process, and if the only feedback possible within the computer environment is via the human user, then the computer is a tool in no essential way different from any other tool…. 

Based on this limitation, Cohen posed the question of whether computer-based creative systems could, without the feedback from a human user, be able to provide their own (feedback) material. In grappling with this question, Van Arman arrived at a unique way of integrating physical and digital input to both transcend determinism and to find a kind of emergence that is specific to the medium. For these synthetic creative feedback loops to emerge, Reflective AI leverages the unpredictable nature of high-viscous acrylic paints, paintbrushes and markers on a textured canvas. As the paint reacts to its application, it drips, blobs, blends and interacts with the canvas unpredictably. These serendipitous physical changes on the canvas then become novel digital inputs, which in turn influence the next step in the physical process, building a series of feedback loops that evince the machine system's own emergent way of seeing.

THE INTERPLAY OF THE PHYSICAL AND THE DIGITAL SPHERES 

As early as 2016, Pindar Van Arman began experimenting with blockchains, specifically Bitcoin, as a way of providing stakes for participation in his crowd-sourced painting project 'Bitpainter.' Subsequently, his dedicated foray into the world of cryptoart began as one of the first artists on SuperRare in 2018. It is from this time that Van Arman often recalls a dilemma that he faced. In his words: 

In the early years, we were all exchanging ideas, collecting each other’s works, and exploring what cryptoart was all about. While I was in the middle of all this, I had the problem that my work didn’t quite fit in. Everyone else was natively digital and taking advantage of the new medium with all of its advantages for digital artists. For me, however, it didn’t completely make sense. My finished canvases were still physical paintings created by robots, and my NFTs were simply photographs of them. There was nothing natively crypto about my cryptoart, and I often wondered if there was even a reason to make my paintings NFTs…

Faced with this conundrum of working with creative robots on physical canvases in a digitally native world, Van Arman searched for solutions to better adapt to the core medium of cryptoart, i.e., digital works on blockchain. The first solution he found were his bitGANs, which are strictly digital artworks. With Reflection, he re-unifies this digital approach with its physical source. The creative process of the Reflective AI system is such that the physical and the digital works are not separate but form a part and parcel of each other. The physical provides the serendipitous inputs for the creation of the digital work; while the digital is composed in a uniquely blockchain-native manner. This interplay, where the physical is not the end but a means to an end, blurs the lines between the physical and digital environments in Van Arman’s artistic practice. This, perhaps, is also a reflection on our own lives, where too the boundaries of the physical and the digital worlds are blurring and slowly transforming.

NATIVELY BLOCKCHAIN-BASED ART 

Reflection presents a unique perspective on long-form generative composition. Each artwork is generated on mint with a process that integrates both the transaction hash and a set of physical inputs from the robotic system. These are then composed using Solidity (Ethereum's programming language), and both the image and the code are stored in the smart contract, resulting in 100% onchain art with no external dependencies.