The Artist Using AI to Reconstruct Lost Stories
- Almagul Menlibayeva is using AI to reconstruct stories lost to censorship
- Her latest installation, Posthuman Matter: The Map of Nomadizing Reimaginings #3, combines craft and code
- Menlibayeva’s approach to AI is rooted in a deeper reckoning with history, loss, and power
- She critiques the lingering impacts of Soviet rule in Central Asia, from ecological degradation to cultural erasure
- Menlibayeva’s work revives Indigenous and nomadic histories long overwritten by empire
Introduction to Almagul Menlibayeva’s Work
Almagul Menlibayeva’s latest installation, Posthuman Matter: The Map of Nomadizing Reimaginings #3, is a large-scale work that combines craft and code to imagine an alternative cartography of Central Asia. The installation features a handwoven textile map, crafted by artisans in Kazakhstan, suspended above video screens that loop footage of salt lakes, steppe villages, and decaying nuclear test sites.
Menlibayeva’s approach to artificial intelligence is rooted in a deeper reckoning with history, loss, and the systems that shape how stories are remembered or erased. She engages with AI not as a neutral tool, but as a terrain of power, ideology, and potential transformation.
Menlibayeva’s Background and Inspiration
Born in Kazakhstan and educated in the Soviet art system, Menlibayeva’s early training in folk textiles and Russian futurism is evident in her layered, hybrid works. Her interest in artificial intelligence is rooted in the traumatic history of Kazakh nomads and the Soviet-era collectivization that dismantled her ancestors’ way of life.
Menlibayeva’s work critiques the lingering impacts of Soviet rule in Central Asia, from ecological degradation to cultural erasure, while reviving Indigenous and nomadic histories long overwritten by empire. With AI, she’s found a way to confront and reanimate these stories.
AI Realism: Qantar 2022
AI Realism: Qantar 2022 was Menlibayeva’s first project to incorporate AI. Created in response to the Bloody January protests in Kazakhstan, the project constructs a synthetic memoryscape from collective trauma. Menlibayeva collected protest-related stories from friends and social media, extracting key phrases in Kazakh and Russian, as well as voice messages sent via landlines and mobile networks.
These fragments of real speech became the raw material for AI Realism: Qantar 2022. Menlibayeva worked with text-to-image and voice-to-image models via Google Colab to assemble a series of AI-generated images from those crowdsourced stories. The resulting artwork is nonlinear and emotionally charged, confronting the erasure of the events from memory.