Parham Ghalamdar, an Iranian artist based in Manchester, UK, holds a Master's degree in Painting from the Manchester School of Art. At the school, he deepened his understanding of oil painting, yet his artistic pursuits span various mediums including stop-cell animation, ceramics, digital design, and radical archiving. Ghalamdar's art engages in a conversation between traditional forms and modern themes, particularly merging painting with new technologies like artificial intelligence. He also addresses pressing issues like climate change and its effects on refugees. His career milestones include a major solo exhibition at HOME, participation in the R.I.O.T. group show at Saatchi, being a UK New Artist Of The Year Award finalist at Saatchi, winning the 2023 UKNA bursary, and featuring in the “Centre of the Periphery” group exhibition at Pipeline gallery.
Website and links: www.ghalamdar.com
Project:
The Ouroboros Effect
The main theme of this research focuses on the evolving relationship between the cutting-edge technology of artificial intelligence (AI) and painting: one of humanity's oldest technologies. This interplay raises profound questions about creativity, agency, and the future of art in an increasingly digitised world. As artists, we believe the best approach to understanding this relationship is through direct and playful engagement: Painting is curious, afterall. Therefore, one idea we are proposing is to use a vast number of mass-produced oil paintings as input data to train AI models. Alongside this, we intend to conduct creative investigations in the following areas:
1. The Recursive Dilemma in AI and its Ouroboros Paradox:
AI's development has reached a recursive loop (AI cannibalism), metaphorically akin to the ouroboros - a serpent devouring its own tail. This symbolism raises the question of what happens when AI, nourished on a diet of human creativity and increasingly its own generated content, begins to learn from itself. Does this lead AI to a point of no return, losing its 'head' or intelligence, akin to a self-consuming entity with diminishing human relatability?
2. Agency in Image Making:
This research questions where the agency lies in contemporary image making, particularly in the context of AI-generated art. It explores the potential of AI as a collaborative tool rather than a threat, challenging the existential fears surrounding AI's role in the arts. The investigation extends to how AI can complement and coexist with the painter's creativity, offering new possibilities and perspectives in painting.
3. Painting's Resilience and Adaptability:
Historically, painting has demonstrated remarkable adaptability in the face of technological advancements and new media. Its inherent 'porousness' allows it to assimilate foreign elements, thereby expanding its boundaries. This research evaluates how painting can integrate AI technologies, maintaining its relevance and agency.
4. The Intersection of Human and AI Intelligence:
The study seeks to understand the interface between human creativity and AI, particularly in image generation. It considers whether this relationship is symbiotic or parasitic, given that AI relies on extensive human-generated data. The potential of AI to produce unexpected interpretations and variations in art, while still relying on human context and intention, is a key focus.
5. The Threat of Model Collapse:
A critical concern is the potential for 'model collapse' in generative AI models, where over-reliance on AI-generated content could lead to a decline in performance and originality.
6. Temporality, Embodiment, and Materiality in Art:
The research delves into how AI influences concepts like temporality and the physicality of art. It questions how AI-generated imagery can enhance or alter traditional art forms like landscape paintings, and the role of technology in reshaping our understanding of time and art creation.
7. AI, Painting, and the Construction of Reality:
Drawing on the example of Piero Della Francesca's "True Cross" paintings, the study examines how painting has historically been a primary medium for image-making, serving as a critical framework to understand AI-generated images and visual reality. It explores how crises in image-making are manifested today - inspired by historical examples e.g painting going back to abstraction when the camera was invented or responding to the Cold War and practice of soft power. Is there an impending crisis for painting and image-making today? And if so, how can we use previous challenges to painting as a means to understand this crisis?
8. The 'Frankenstein Monster' in Art Creation:
The research likens the AI-generated art to a 'Frankenstein monster', reflecting on the themes of hybridity and innovation in contemporary art practices. This analogy underscores the complexities and ethical considerations in blending human creativity with artificial intelligence.
9. Navigating the New Politics of Image Production:
Finally, the study addresses the politics of image production in the age of AI. It contemplates how AI's parasitic relationship with painting, spanning both visual and linguistic domains, affects the production and perception of art. We want to explore questions of authority, ownership and consent of image-production, whether it’s authorised by the artists or others. What are the power dynamics? Throughout history, technology has significantly altered our connection with visual art, particularly paintings, through processes like reproduction and displacement. Innovations such as photography and mass media revolutionized the way we interacted with images. Now, artificial intelligence takes this transformation a step further by engaging in a form of visual terrorism, effectively hijacking and manipulating images.