Hallucinations
2023
When AI large language models generate false information, it’s called hallucination. The same term applies to the inflated promises the tech industry makes about these systems’ transformative potential. Hallucinations channels this parallel through a process of deliberate artistic intervention, where AI-generated images become raw material for personal expression rather than autonomous creation.
Working with Generative Adversarial Networks trained on minimal datasets, the initial images expose the digital artifacts and failed attempts at coherence that emerge when systems operate beyond their training. But the work begins where the machine stops: each image is then individually manipulated through custom code, with parameters and algorithms adjusted to amplify my responses to the tech industry’s mythology. These interventions become gestures that search for patterns the machine perceives but cannot articulate — making visible the gap between computational process and human interpretation.
The manipulation process transforms computational artifacts into expressive statements. Rather than accepting what the algorithm produces, the work creates conditions where human intervention, critique, and emotional response become visible within the computational framework. The titles, quotes from tech leaders about revolutionary promises, accompany images that emerge from the tension between technological capability and industry claims, inviting viewers to consider the relationships between promise, process, and outcome.
Press
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