The question "Is it art?" has permeated various levels of discussion, to the point where it has almost become a meme. A 1993 TV show with the same name bluntly questioned whether contemporary artists were truly producing art, reflecting the public’s scepticism towards works beyond traditional painting or sculpture.

Digital art, in particular, has often been seen as an outsider even within the art world. Major national art critics dismissed digital artworks as mere screensavers or extremely intelligent lava lamps as recently as 2023, so this predisposition remains alive and well.

However, asking "What is art?" is essential for redefining art itself. This is especially true for media art, a field that is constantly expanding. Digital art is difficult to pin down, as it evolves rapidly alongside technological advancements and encompasses a wide range of artistic practices. As Christiane Paul notes, digital art is "digital‐born, computable art that is created, stored, and distributed via digital technologies." It leverages unique features such as interactivity, generativity, and participation while addressing broader social, political, and aesthetic questions.

Building on these discussions, the exhibition focuses on the question, "What is media art right now?" Through the lens of video, it surveys the landscape of digital art in 2024, showcasing diverse techniques that reflect the medium's current trends, challenges, and potential. By bringing together twelve artists—many of whom have backgrounds in science, design, games, music, and even ballet—Load provides a snapshot of this ever-evolving field. 

As a nod to Barcelona's leading position in the video art scene, all works on view are in video format. However, only some artists used cameras for filming, making their work classify as video art. These are juxtaposed with artists who generate their art on the computer. The focus of the show is on the variety of methods—generative art, data visualisation, filming, and AI-powered deep learning—that artists could use to produce video, emphasising both the creative journey and the final result. 

The most traditional way to create a video, and the first that comes to mind, has been filming—using cameras to capture real-life scenes. Video art, a form of artistic expression that relies on video technology as its primary medium, branched out of the cinema in the 1960s as a more experimental field, often manipulating time, motion, and sound to convey the artist's vision. 

In contrast, a radically different approach involves creating artwork on a computer, "outsourcing" part of the creative process to algorithms, as generative and AI artists do. 

Generative art is an artistic practice that employs autonomous systems to introduce chance into the art creation. Instead of directly "making" the work, an artist sets up a system with specific rules and parameters, allowing it to generate unpredictable and unique outputs, often through algorithms and computational processes. Distinguished by its emphasis on the creative process and system over the final product, generative art often incorporates randomisation and iteration, so that artworks can evolve in real time or in response to viewer interaction.

In response to the rise of “big data”—massive data sets that traditional data analysis methods struggle to interpret—artists have developed data visualisation as an artistic practice, replacing lines and graphs with media objects like images and video. Usually, such works contain dynamic graphic elements on screens, created with interactive software, and can change at any moment. By choosing specific data sets and novel visualisation techniques, artists comment on the world, history, societies, and humanity, turning artistic data visualisations into the modern equivalents of portraits, landscapes, and genre scenes in traditional art, depicting the world through data presentation instead of visible forms.

Another approach to reinterpretation of big data is AI art, where artists use machine learning algorithms, such as deep learning, to analyse visual data. The process usually involves training an algorithm on a selected dataset, for example, oriental freehand ink paintings found online. The processed data is then converted into dynamic visual representations, often employing 3D modelling, simulation, and generative design techniques to create these visualisations. This approach reveals the hidden patterns and structures within the data, transforming it into visually compelling and emotionally resonant experiences. 

The boundaries between techniques are blurred; an artist can use a range of tools and techniques in one project. For instance, they might train an AI and then create a generative artwork based on the outcome, while many photographers and filmmakers use digital post-production to add generative elements or CGI.