DATA is a moving-image meditation on the fragile state of being human inside systems of computation. It confronts three elemental questions: What does it mean to be human? What does it take to see each other as equals? When do we collapse?—but asks them within the logics of datafication, surveillance, and algorithmic control.
The work unfolds as a series of allegorical visions suspended in darkness: a boy illuminated by a projected family film—a private memory becoming a dataset under machine vision; a knight carrying an old man up a hill—the handover between legacy and update, memory and model; a house burning in isolation—an archive on fire, the loss of storage and story; a mass of bodies spiraling toward light—a social graph ranked, sorted, optimized until exhaustion. Each scene captures a threshold where identity, memory, and survival collide with capture, parsing, and prediction.
Human figures appear fused into structures like networks and circuits, bodies turning into topologies, ascending toward impossible hierarchies of ranking, dissolving into machinic pipelines, or flowering into strange algorithmic blooms. These shifting images mirror the contradictions of our condition: we are at once fragile and resilient, embodied and abstracted, deeply individual yet continuously aggregated, scored, and compared.
At its core, DATA asks how we define humanity when bodies become datasets, when identity is flattened into profiles, when inequality is encoded as weights and thresholds, and when collapse arrives as systemic failure rather than a single event. The figures are not heroes or villains but signals moving through noise—embodiments of longing, grief, hope, and judgment that expose the silent biases and brittle optimizations binding us together.
By blending mythological allegory with contemporary dystopian imagery, DATA stages a space where salvation and critique coexist, where tenderness and violence intertwine, and where every vision reflects our unresolved entanglement with the infrastructures that see, sort, and simulate us. It does not propose answers. Instead, it holds space for reflection—reminding us that to be human is to remain irreducible to metrics, to search for meaning amid collapse, and to recognize fragments of ourselves across datasets and bodies alike. Ümüt Yildiz