This interactive immersive installation explores the invisible processes through which artificial intelligence observes, records, and transforms human behaviour into data. By placing the participant at the centre of the experience, the project visualises the journey from a physical presence to a machine-readable profile, revealing how AI systems perceive people as collections of measurable information.
The experience begins with a simple act of person detection. As the participant enters the space, the system identifies their presence and establishes them as a subject within its field of observation. This minimal interface reflects the first stage of computer vision, where an individual is recognised not as a person but as an object to be tracked.
The second stage introduces real-time line graphs generated through hand and pose tracking. Every movement is translated into numerical values and live visualisations, exposing how gestures and body language become quantifiable parameters that can be measured and stored. Next, a heatmap and motion feedback system accumulates the participant’s movements over time. Rather than representing a single action, the visualisation builds a behavioural footprint, revealing patterns and frequencies that are invisible to the human eye but valuable to machine
learning systems.
The final processing stage shifts from data collection to computation. The immersive space fills with floating numbers, calculations, and fragmented datasets that surround the participant, visualising the hidden analytical processes performed by AI. This stage represents the organisation and processing of collected information before it is transformed into a usable model.
Once the computation is complete, the interface displays “100% Complete”, followed by “Subject Categorized.” After an extensive process of observation and analysis, the participant is reduced to a simplified numerical identity and assigned a predefined category.
Rather than criticising artificial intelligence itself, the project invites audiences to reflect on the mechanisms of contemporary data-driven technologies. It questions how everyday interactions are continuously converted into datasets for machine learning and training, and how these systems inevitably reshape human experience by treating people as collections of measurable variables rather than complex individuals.
Charlotte Juliens – Ekin Ayca Demirli – Inioluwa Adeyiga