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Our philosophy and the concept of Machine Realism
AI´s vision on realism
Our work aims through a philosophical lense of Machine Realism (Heikkilä, 2021) underscore the importance of shared experiences in fostering curiosity, AI creativity, and a sense of community. By engaging with the narratives of others, we gain new perspectives, affirm our own uncertainties, and find inspiration for change. We wish our human-AI-human art serves as both a reflection of and a catalyst for this ongoing process of transformation, uniting scientific inquiry, technological innovation, and artistic expression in a single, coherent vision.
At its heart, the human-AI-human art is a celebration of the transformative power of stories. The festival narratives that serve as the foundation of this work are not just isolated experiences but collective expressions of humanity's desire to connect, understand, and evolve. These stories, when analyzed and visualized by AI, reveal underlying themes of interconnectedness, transformation, and discovery—themes that are then brought to life in the final paintings. The data is available for anyone interested in our AI platform and the data has been also used in sound art by Mikko Heikinpoika in Love & Acceptance made from a Borderland 2019 love story and Viljami Lehtonen Köppö [INSERT PIECE ONCE FINAL]
Machine Realism
AI hallucinating new philosophy based on research by Graham St John (2019)
Machine realism refers not to a dystopian or utopian view of AI, but rather a realistic approach to integrating AI's analytical capabilities with human creativity to produce artwork that both reflects and deepens our understanding of reality. By leveraging AI's ability to recognize patterns, analyze narratives, and visualize data, its our heroic (D'Inverno & McCormack, 2015) team member with whom we aim to create works that transcend traditional artistic boundaries. The resulting pieces reflect a fusion of machine precision and human emotional depth, creating a new artistic vocabulary that speaks to the evolving relationship between technology and humanity (Heikkilä, 2021).
In our experimental works, machine realism manifests through the visualization of festival narratives. AI models processing the underlying emotions, themes, and transformations shared by participants, transform the abstract ideas into visual forms. The resulting artwork serves as a bridge between raw data and human experience, offering viewers not only a reflection of their own stories but also a window into the collective consciousness of transformative festivals.
Machine realism in our art is more than a technique in the following creative process; it is an ongoing exploration of how technology can enhance, rather than replace, human creativity, fostering a deeper connection to the shared experiences that define us.
Heikkilä, J-P (2021) Myytistä konerealismiin? Katsaus tekoälyn ja taiteen yhteiseen tulevaisuuteen. Futura, 2021(1).
D'Inverno, M., & McCormack, J. (2015). Heroic versus collaborative AI for the arts. In Proceedings of the 24th International Conference on Artificial Intelligence (pp. 2438-2444).
Summarized steps of our creative process
Step 1
Field research has been conducted by Dr. Jukka-Pekka Heikkilä by collecting narratives from transformative festivals (2018-2024) such as Burning Man Black Rock City and regional events, BOOM, Ozora and Mo:dem, employs a scientifically unique data collection, where a person can share a transformative in situ story to the Story Sharing Device. The initial community wisdoms narrative data of 490 narratives has been transcribed to text and the data set has been supplemented with an indexed research database of 290 research articles and 60 podcasts of core Burning Man community. The ongoing data is a part of Open Strategy research project in Aalto University and University of Oxford.
Step II
The dataset has been rendered and AI-arted by AI specialist Kiana Kiser. Data was structured for analysis, employing Natural Language Processing (NLP) techniques for summarization. Dimensionality reduction via Uniform Manifold Approximation and Projection (UMAP) and clustering through Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) facilitate the organization of data into coherent, thematic clusters. This process was augmented by Term Frequency-Inverse Document Frequency (TF-IDF) analysis to highlight key terms, and Large Language Models (LLMs) to generate descriptive labels for each cluster, encapsulating the predominant themes. Each story and research summary was then sent to OpenAI's generative AI engine «DALL-E», resulting in generating an AI-Art piece for each data point within the set.
Step III
Visionary artist Luca Delcado has painted over the AI art created from the data with traditional oil painting methods. As a result, the piece transcends the physical world, originating from the realms of the metaphysical, spiritual, and imaginative collective human-AI wisdoms. The symbolic elements and surreal approach aims especially to evoke profound emotional and intellectual responses on how science-based AI rendered data can be used in traditional art.