The symbiogenic experience: towards a framework for understanding humanmachine coupling in the interactive arts
Bibliographic record
Abstract
This article outlines a research agenda that addresses the question of how contemporary interactive arts practice can evolve new strategies or ways of facilitating the development and representation of subjective experiences that induce an embodied felt sense of the humanmachine co-evolution. To help answer this question, the term symbiogenic has been created as a shorthand or umbrella term to better discuss these types of experiences and the concepts they introduce. The term symbiogenic is taken from symbiogenesis, the evolutionary theory introduced in 1909 by Russian biologist Konstantin Mereschkowsky and expanded in the modern era by Dr. Lynn Margulis (1993, 1981). This theory emphasizes cooperation and other more complex interactions between organisms that go beyond mere competition. The research starts from the conception that there currently exists a range of interactive artworks that examine and engage with the increasing cooperation and co-evolution that humans are experiencing with their technological environment. However, what is proposed is that interactive or technological art can go further and provoke a bodily felt sense of this dynamic and thus bring into greater consciousness the co-dependent and co-evolutionary path of our relationship with technology. It is believed that these experiences can be both developed and identified within an artistic context but they lack a cohesive conceptual framework from which to study and analyse them.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.027 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".