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Record W4281479350 · doi:10.32920/ifmj.v2i2.1563

Un/interactive Fish in Posthuman Ethical Design

2022· article· en· W4281479350 on OpenAlexvenueno aff
Yueh-Jung Lee

Bibliographic record

VenueInteractive Film and Media Journal · 2022
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsnot available
Fundersnot available
KeywordsPosthumanPosthumanismFish <Actinopterygii>SociologyEmbodied cognitionCritical designComputer scienceFisherySocial scienceArtificial intelligence

Abstract

fetched live from OpenAlex

In the posthuman era, what counts as ethical has dispersed and re-distributed to a nonhuman-centered network that includes nonhuman species and nonliving matter. This hybrid study consists of research and project-based speculative design that aims to recalibrate human relationships with others, in this case, digital fish. The overarching question in this research is: How a human-nonhuman relationship could look like through the lens of Taoist-posthumanism and how to design such a relationship? More specifically, how to design a mutually beneficial interactive system with limited human-initiated interaction? Firstly, I draw on Posthumanism, Taoism, and Contractualism as theoretical frameworks to form the arguments regarding the human-fish relationship. Second, I analyze the theories and transcribe them into the public interactive project Not-my-fish in terms of un-interactive interaction and human experience. Third, I apply the concept of flow as design guidelines and feature four aspects of the flow in the human-fish interaction: ecological flow, sensory flow, social flow, and data flow. Fourth, I discuss how the participating parties mutually benefit from this partnership. Not-my-fish rearticulates the relationship between humans and fish as well as humans and computers and sees the human-fish relationships from posthuman and Taoist perspectives. In short, although the transition from human-centered to posthuman interactive media creates some challenges for human partners and design aspects, the project demonstrates a practical way for humans to develop a posthuman design in public interactives and serve the public good at the same time.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.350
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.005
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.022
GPT teacher head0.288
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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