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

Artist Pindar Van Arman’s work centers itself on these new developments by posing a modern version of Benjamin’s 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. The synthetically creative systems he builds are an attempt to see the world from an algorithmic perspective. By capturing a creative process with code, he is able to dissect and parse to reveal insights into human creativity. At its core, his art is an exploration of the unique ways of seeing that emerge from a machine's perspective. Moreover, it is about finding humanity in an age where humanity is increasingly being imitated by algorithms.

Exploring these themes for more than twenty years, Van Arman has observed that for AI to successfully create like a human, it needs to reflect like a human. Influenced by Marvin Minsky’s Society of Mind concept, Van Arman approaches creativity as something that is not a singular process but multiple ‘agents’ collaborating to discover emergent ways of seeing. His robots use multiple algorithms that evaluate the structural, dynamic and aesthetic elements of an 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. This reflection is fundamental to the creative act.

Feedback Genesis, Pindar Van Arman, Machine Painting, 12"x12", 2023

Today’s mainstream AI lacks reflection. This is the ability of generative algorithms to critically evaluate their outputs and re-work them based on internal feedback. Currently, the vast majority of AI is linear and used in “zero-shot mode” where it generates final outputs without ever revising the outputs. As Andrew Ng, the cofounder and head of Google Brain, has recently noted (March 2024)

“This is akin to asking someone to compose an essay from start to finish, typing straight through with no backspacing allowed, and expecting a high-quality result. Despite the difficulty, LLMs do amazingly well at this task!" (March 2024)

While AI works well despite this disadvantage, many AI researchers are coming to the conclusion that AI needs to become reflective. Peter Lewis and Stefan Sarkadi recently wrote:
 

“One core feature that humans bring to the tasks that they perform, when dealing with the ambiguity, emergent knowledge, and changing circumstances presented by the world, is reflection. Yet this capability is completely missing from current mainstream AI.” (From Reflective Artificial intelligence, May 2024)

In recognition of this problem, researchers are leaning into a framework suggested by Ng where AI is given 1) a variety of tools that can 2) collaborate to solve problems and 3) reflect on the validity of its solutions. Initial results have shown that this approach dramatically improves the creative capabilities of AI and implementations are already appearing in applications like chatGPT and Claude.

A Look Inside

Generative AI is currently a black box where you can only see the outputs but not the process itself. Many AI researchers even admit to not fully understanding how neural networks work, just that if trained on the correct data, it produces the correct results. Van Arman’s art is a peek inside the black box. He shows viewers how his AI ‘thinks’, ‘decides’ and ultimately creates. At its core, his Reflection series is an exploration of the “aura” of creativity itself. Instead of just showing the final results from a prompt, it takes its viewers on a step by step journey through its creative process. It is a look inside a synthetically creative mind. 

Hunter, Pindar Van Arman, Machine Painting, 20"x20", 2020

Van Arman uses algorithms and robots to create paintings on canvas. But that is not his art. His art is the system that coordinates the algorithms and robots. A system that replicates the reflective processes of an artist engaging with a canvas as an embodiment of creativity itself. But, his robotic art was not always reflective. It came about when he recognized a critical issue.

“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 his robotic system in 2010. This enabled it to not just ‘see’ the work but also to respond to the changes instead of simply iterating through commands. These robots were soon noticed by academia and resulted in a citation in Oliver Deussen’s paper Feedback-guided Stroke Placement for a Painting Machine. From this early basis, he has gone on to fine-tune his feedback loops around increasingly nuanced and reflective algorithmic decision-making processes.

Paul Klee's "The Thinking Eye"

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 work titled The 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 of human action (genesis) is productive as well as receptive. It is continuity.”

Van Arman’s work attempts to translate this perspective into his AI in order to discover new ways of seeing that are unique to computational creativity. As an artist makes marks on a canvas, analyzes the mark, and uses the analysis to make the next mark, so too do his robots.

Emergence in Generative Art

Another major influence on Van Arman’s artistic practice is Harold Cohen, with whom he was in correspondence until his passing in 2016. One of the limitations to computational creativity that Cohen highlighted was its deterministic nature. 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….”

Harold Cohen coloring a design made by AARON

Photograph from the Computer History Museum

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. Furthermore, he rightfully believed that all generative art, including AI art, was deterministic and even when variations were programmed in, the results would fall on a bell curve of possibilities. Increasing a generative algorithm's complexity only made the bell curve larger, but never escaped it. Cohen was focused on art that was not on the bell curve of possibilities. He was interested in emergent art that transcended algorithmic determination, and speculated with Van Arman that generative art might not be capable of achieving such emergence.

“Cohen and I used to talk in depth about artificial creativity. When we talked about whether or not my robotic system was creative, he pushed back telling me they were merely executing deterministic commands. I countered that new neural nets were not deterministic, and told him about Style Transfer and Generative Artificial Networks (GANs). But he never agreed with me. He saw them as filters that merely transformed images. Despite our disagreement, I took this critique seriously and focused on achieving true emergence.”

Responding to the challenge, 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, Reflection leverages the unpredictable nature of low viscosity paint, brushes 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 mechanical system's own emergent way of seeing and creating.

Reflections on Mechanical Creativity, Pindar Van Arman, Machine Painting, 12"x12", 2024

By collaborating with his creative systems, Pindar Van Arman is exploring the existential questions that humans, especially artists, face with the rise of AI. In his essay, Walter Benjamin was responding to a historic shift arising from the age of industrialization. Van Arman too is responding to a historical shift, this time in the age of AI. His work endeavors to bring audiences inside the site of this transformation, to make synthetic creative processes into an active artistic experience. Perhaps here we can find a kind of reflection that makes it possible for people to understand shape the technologies that are changing the world. 

Further Reading on PINDAR VAN ARMAN

"Inside the Studio With an AI-Guided Painting Robot" Time Magazine
D.W. Pine

"Can AI Create True Art" Scientific American
Ken Weiner

"You Can Give A Robot A Paintbrush, But Does It Create Art?" NPR

Allie Caren 

REFERENCES

“The Work of Art in the Age of Mechanical Reproduction”  link to PDF
Walter Benjamin

The Society of Mind  link
Marvin Minsky

“Generative Adversarial Networks”  link to PDF

 IJ Goodfellow

“A Neural Algorithm of Artistic Style”  link to PDF

Leon Gatys et al.

“Reflective Artificial Intelligence”  link to PDF
Peter Lewis and Stefan Sarkadi

"Parallel to Perception"  link to PDF
Harold Cohen

"Colouring Without Seeing: a Problem in Machine Creativity" link to PDF
Harold Cohen

"A Self-Defining Game for One Player" link to PDF
Harold Cohen

"Where Does A.I. End and We Begin?" New York Times
Sougwen Chung

"Readyweights" Mirror
Holly Herndon & Mat Dryhurst

Conversation with Ira Greenberg and Ivona Tau  Outland
Ira Greenberg and Ivona Tau

"Art’s Intelligence: AI and Human Systems" The Brooklyn Rail
Charlotte Kent

Pedagogical Sketchbook  link to PDF
Paul Klee, translated by Sibyl Maholy-Nagy 

"Creativity and Artificial Intelligence" link to PDF
Margaret A. Boden

"Bricolage Programming in the Creative Arts" link to PDF
Alex Mclean & Geraint Anthony Wiggins

"The Phenomenal Concept Strategy"  link to PDF
Peter Carruthers & Bénédicte Veillet

"Minds, Brains, and Programs" link to PDF
John R. Searle

"Creativity in the age of generative AI" Nature Human Behaviour
Janet Rafner, Roger E. Beaty, James C. Kaufman, Todd Lubart & Jacob Sherson

Categories  https://classics.mit.edu/Aristotle/categories.1.1.html
Aristotle

Brief Bio

As an innovative, award-winning artist pioneering the emerging field of synthetic creativity, Pindar Van Arman has blazed a unique trail in both the physical and digital art worlds. His reflective AI system uses robots and a variety of collaborating algorithms to paint emergent art on stretched canvases.

Van Arman’s works are the focus of frequent solo, group shows, and major art installations including acceptance into LACMAs permanent collection. His work has also been covered in publications around the world including Time, Fine Art America, Artnet News, MIT Technology Review, Smithsonian Magazine, The Washington Post, Scientific American, and more.

Throughout this journey Van Arman has focused on portraiture, examining what it means to be human in the age of mechanical creativity. His creative systems interact with its subject as it develops new ways of seeing from a machine's perspective.