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As interaction with corporate artificial intelligence increasingly becomes a precondition for contemporary life, artists need to see beyond Generative AI (GenAI) technology as a discrete tool that makes generic products. Instead, they can imagine combinatorial approaches and conceptual frameworks for AI-enabled artworks. Through my practice-based research, the act of prompting multimodal GenAI models has been informed by comprehending an assemblage as a “framework of instruction” held together through poetic alliances, within which the output from one component feeds the process of another. Practical experiments explored an interrelation of body, text, and predictive technology, where an algorithmic prediction of human action conjured “biometric poetry” that was used to stimulate a language model. Working with archival film footage and digital puppets animated with motion-capture files gave rise to the idea of a camera’s field of view – with its bounded contents acting like a key – eliciting value from a language model in a novel form of story making. Potential erroneous inferences were perceived as a new form of chance operation and a characteristic of algorithmic remix as defined by Steve F. Anderson. This method has been further developed in a project that combines performance, waste material, object recognition, and a language model to explore how the manipulation of garbage can be rationalised by a machine to produce poetic texts as a commentary to action portrayed on a screen.

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  • contents
    • Contents
    • 01 Introduction
    • 02 Legacy Systems
    • 03 The Creative Act
    • 04 Summary of Project Method
    • 05 Precursors
    • 06 Exhausted Data Bodies
    • 07 More Mimicry in Human-Action Datasets
    • 08 HAR Misclassifications
    • 09 Distilling Literary Corpora
    • 10 Synset_Gloss
    • 11 No_m_oN
    • 12 Idling-in-the-Unreal
    • 13 Fluid Narratives
    • 14 Ritual Paradox
    • 15 Poetics of Garbage
    • 16 Summing Up
    • 17 References
    • 18 Figures and Videos
    • bruce gilchrist
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  • abstract
    As interaction with corporate artificial intelligence increasingly becomes a precondition for contemporary life, artists need to see beyond Generative AI (GenAI) technology as a discrete tool that makes generic products. Instead, they can imagine combinatorial approaches and conceptual frameworks for AI-enabled artworks. Through my practice-based research, the act of prompting multimodal GenAI models has been informed by comprehending an assemblage as a “framework of instruction” held together through poetic alliances, within which the output from one component feeds the process of another. Practical experiments explored an interrelation of body, text, and predictive technology, where an algorithmic prediction of human action conjured “biometric poetry” that was used to stimulate a language model. Working with archival film footage and digital puppets animated with motion-capture files gave rise to the idea of a camera’s field of view – with its bounded contents acting like a key – eliciting value from a language model in a novel form of story making. Potential erroneous inferences were perceived as a new form of chance operation and a characteristic of algorithmic remix as defined by Steve F. Anderson. This method has been further developed in a project that combines performance, waste material, object recognition, and a language model to explore how the manipulation of garbage can be rationalised by a machine to produce poetic texts as a commentary to action portrayed on a screen.
  • bruce gilchrist - Demolish Monsters on the Rocks: Prompting Through an Ensemble - 2026
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01 Introduction


02 Legacy Systems


03 The Creative Act


04 Summary of Project Method


05 Precursors


06 Exhausted Data Bodies


07 More Mimicry in Human-Action Datasets


08 HAR Misclassifications


09 Distilling Literary Corpora


 

10 Synset_Gloss


11 No_m_oN 

12 Idling-in-the-Unreal
 

13 Fluid Narratives


14 Ritual Paradox


15 Poetics of Garbage 

16 Summing Up

17 References

18 Figures and Videos