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Record W6950559395 · doi:10.5281/zenodo.8163789

Excentric Humanism and the Artlessness of Artificial Intelligence

2023· article· en· W6950559395 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicPostmodernism in Literature and Education
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsRealmHuman intelligenceReading (process)Embodied cognitionHumanismConformityRelevance (law)Object (grammar)

Abstract

fetched live from OpenAlex

What is the defining feature of the human capacity to think? One answer to this vexing question, the dominant one is our technological era, is to conceive this faculty as mind-centered or egocentric. Thinking here is taken fundamentally to be a mental act. The project to artificially recreate human thinking is premised on this arguably concentric reading of thinking, one in conformity with a code-dependent and calculative understanding of what constitutes intelligence. An alternative reading underscores the extent to which the human capacity for reflection is excentric, or displaced from the center that is the cogito. Jean-Francois Lyotard, Byung-Chul Han, and Jean Baudrillard are recruited as contemporary proponents of the excentric paradigm. Their analyses are marshaled as a means of underscoring the fact that despite recent advances within the realm of artificial intelligence, the project to replicate human intelligence is structurally incapable of duplicating its defining feature--an embodied and open-ended relationship to the world.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.943
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.002

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 head0.075
GPT teacher head0.260
Teacher spread0.185 · 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