This paper examines the audiovisual artwork Prosomoíosi (Simulation) to critique how successive simulation technologies overwrite cultural memory. Grounded in media-archaeological thinking, the study argues that concepts must be articulated through media whose operative logic remains visible, thereby transforming viewers from passive spectators into active witnesses of algorithmic decision-making. A transparent live diffusion pipeline serves as both method and message, enabling audiences to observe how text prompts, stochastic noise, and performer input co-evolve on screen. By tracing precedents from early interactive installations to contemporary AI-driven works, the paper positions Prosomoíosi within a lineage that challenges tool-centric spectacle and renegotiates authorship at the human-machine frontier. Medium alignment thus emerges as a transferable design heuristic for artists seeking to move beyond technological virtuosity toward works that explicitly reveal, rather than conceal, their underlying political dimensions.

"Prosomoíosi" (Simulation) is a real-time audiovisual study of how successive modeling frameworks overwrite cultural memory. Grounded in media archaeology, the work introduces ’medium alignment’, arguing that concepts must be voiced through media that expose their operative logic. A live diffusion pipeline with multi-prompt editing stages the algorithmic politics of selective remembrance, inviting audiences to renegotiate authorship and selfhood at the human–machine frontier through contemplative engagement with the transparent algorithmic process."

"Quantum est in libris" explores the intersection of the archaic and the modern. On one side, there are manuscript materials from the Estonian National Museum’s (ERM) more than century-old archive describing the life experiences of Estonian people; on the other side, there is technology that transforms these materials into a dynamic and interactive experience. Connecting technology and cultural heritage is the visitor, who turns texts into inputs for a screen sculpture.

"Quantum est in libris" explores the intersection of the archaic and the modern. On one side, there are manuscript materials from the Estonian National Museum’s more than century-old archive, describing the life experiences of Estonian people; on the other side is technology that transforms these materials into a dynamic and interactive experience. Connecting technology and cultural heritage is the visitor, who turns texts into inputs for a screen sculpture.

Innovations in digital fabrication technologies are increasingly enabling artists and designers to create data physicalizations in real time. In this paper, we discuss how we adapted a circular knitting machine to physicalize visitors at a local art gallery during the pandemic recovery year. To evaluate this year-long installation, we conducted design critiques with 15 individuals including those who worked in the building and lived alongside it for a year, as well as subject matter experts. We then iteratively worked with 11 of those individuals to gain insights for re-deploying the visualization for interpretation. Overall, this paper contributes long-term reflections and recommendations for using digital fabrication for real-time data physicalizations.

This paper discusses the artwork "Visions of Destruction", with a primary conceptual focus on the Anthropocene, which is communicated through audience interaction and generative AI as artistic research methods. Gaze-based interaction transitions the audience from mere observers to agents of landscape transformation, fostering a profound, on-the-edge engagement with pressing issues such as climate change and planetary destruction. The paper looks into early references of interactive art history that deploy eye-tracking as a method for audience interaction, and presents recent AI-aided artworks that demonstrate interactive latent space navigation.

This paper explores the potential of generative AI within interactive art, employing a practice-based research approach. It presents the interactive artwork "Visions of Destruction" as a detailed case study, highlighting its innovative use of generative AI to create a dynamic, audience-responsive experience. This artwork applies gaze-based interaction to dynamically alter digital landscapes, symbolizing the impact of human activities on the environment by generating contemporary collages created with AI, trained on data about human damage to nature, and guided by audience interaction. The transformation of pristine natural scenes into human-made and industrialized landscapes through viewer interaction serves as a stark reminder of environmental degradation. The paper thoroughly explores the technical challenges and artistic innovations involved in creating such an interactive art installation, emphasizing the potential of generative AI to revolutionize artistic expression, audience engagement, and especially the opportunities for the interactive art field. It offers insights into the conceptual framework behind the artwork, aiming to evoke a deeper understanding and reflection on the Anthropocene era and human-induced climate change. This study contributes significantly to the field of creative AI and interactive art, blending technology and environmental consciousness in a compelling, thought-provoking manner.

Psychedelic Forms is a series of case studies that explore deep learning (DL) possibilities for creating a tangible form guided by text prompt and 3D object. The selected generated digital 3D objects were manually altered and prepared for 3D printing in ceramics (Figure 1). Glazing happened by hand, often inspired by the AI-generated objects’ vertex colors. And the pouring technique used for painting, it is a metaphor of the thermodynamics of meaning spaces in the latent spaces.

Interactive NeuroKnitting: Knitting with Your Brain stems from our previous work about knitting and brain data. A self-made circular knitting machine Circular Knitic is activated on the user’s EEG data in real-time. It means that knitting happens only when a spectator wears BCI (brain-computer interface). The audience’s meditation and attention levels are translated to the knitting machine’s speed and pattern. Hence, the autonomous knitting machine is turned into a brain-data-driven mechanism that enables the audience to experience their brain activity through the knitting process, leaving the pattern in the garment behind. The growing collective brain-knitting installation is accompanied by the on-screen personal EEG data visualization overlaying AI-generated videos. A multimodal EEG data experience enables the viewers to understand their brain activity in novel and artistic ways.

We introduce the Collection Space Navigator (CSN), a browser-based visualization tool to explore, research, and curate large collections of visual digital artifacts that are associated with multidimensional data, such as vector embeddings or tables of metadata. Media objects such as images are often encoded as numerical vectors, based on metadata or using machine learning embeddings. Yet it remains a challenge to explore, analyze, and understand the resulting multidimensional spaces. Dimensionality reduction techniques such as t-SNE or UMAP often serve to project high-dimensional data into low dimensional visualizations, but require interpretation themselves given their typically abstract dimensions. The Collection Space Navigator provides a customizable interface that combines two-dimensional projections with an array of configurable multifunctional filters and navigation controls. The user is able to view and investigate collections by zooming and scaling, transforming between projections, and filtering dimensions via range sliders and text filters. Insights gained through these interactions can be used to augment original data via easy to use export capabilities. This paper comes with a functional online demo showcasing a large digitized collection of classical Western art. Users can reconfigure the interface to fit their own data and research needs, including projections and filter controls. This open source tool is intended to be applicable in a broad range of use cases, types of collections and across diverse disciplines.

Museum collection strategies are governed by a variety of factors, including topical focus, acquisition funds, availability of works in the art market, donations and specific coincidental opportunities. Yet, it remains unclear if more fundamental collection patterns emerge, exist, and are shared between museums, which could for example allow an established artist to estimate when a contemporary art museum would acquire their works. Here we collect and analyze data from 12 European contemporary art museums, taking into account artwork creation dates, collection acquisition dates, and the associated artist age at both points in time. From this simple quantitative construct we are able to reveal a striking gradient of museum profiles at the aggregate level. This lag can function to constitute a macroeconomic index of "mean museum collection lag", ranging from 3 years in the most dynamic cases (Kiasma) to 35 years in the most established institutions (Museo Reina Sofía). Meanwhile, on the granular level, plotting artist age over collection year, and using artist-age vs artwork-collection matrices, a detailed picture becomes evident, where individual museums are characterized by shared patterns and a rich heterogeneity of ideographic details. Regularities include continuous acquisitions, systematic acquisition of older materials over time, and brief bursts, where whole oeuvres of individual artists join specific collections. Hence, we are able to shed light on the detailed collection history of museums, transcending the anecdotal nature of art historical storytelling via the provision of a quantitative context. Our approach of cultural data analysis combines expertise in art, art history, computational social science, and computer science. Our joint perspective builds a bridge between and serves an audience of museum professionals, art market actors, collectors, and individual artists alike.

POSTcard Landscapes from Lanzarote I and II are two AI-generated video works accompanied by two sound pieces. The StyleGAN 2-created visuals were composed of location-based datasets, more precisely, from Flickr photos of Lanzarote – a tourists’ Mecca of Canary Islands. One video intends to represent a touristic, and the other, a local view of the place. The project draws attention to the influence of the tourist gaze on the landscape and identity formation of the Lanzarote island in Spain. Heavily dominated by the imaginative geographies that have been constantly reproduced by the visitors, create a conflict between desired touristic rituals, which one is preprogrammed to reproduce when arrived at the destination, and the reality. Better said in the words of an expert on tourist photography Jonas Larsen “[…] circulating images overpower reality: ‘reality’ becomes touristic, an item for visual consumption.” [3]

Dream Painter is an interactive robotic art installation that turns the audience's spoken dreams into a collective painting. By telling one's past dream, a participant guides the interactive robotic system in the latent space of the AI model that results in a multicolored line drawing. The artwork consists of several parts: an interaction station, a painting robot, a kinetic and animated mechanism that moves the paper roll when a drawing is finished, and the deep learning model that transforms a spoken word into a painting. All these interconnected components of hardware and software are arranged into an autonomous and interactive robotic art installation. The main aims of this project are to explore the interactive potential of AI technology and robotics, and trigger discussion over the deep learning applications in a wider sense. More precisely, this case study is primarily focused on the translation of different semiotic spaces as a trigger for creativity and audience interaction method.