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Record W3155705451 · doi:10.24908/iqurcp.9603

Transhumanism as Lens for Economic and Social Development

2018· article· en· W3155705451 on OpenAlexvenueno aff
Callum Tomkins-Flanagan

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2018
Typearticle
Languageen
FieldNeuroscience
TopicNeuroethics, Human Enhancement, Biomedical Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsTranshumanismPaceMultinational corporationPosthumanEnvironmental ethicsPoliticsHuman enhancementDominance (genetics)SociologyPolitical sciencePolitical economyEconomicsLawComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Transhumanism is a philosophical worldview so driving that in some circles, it might almost be called a religion. Transhumanist belief holds that the rushing integration of humans and machines is inevitable and it moves to deeply alter the nature of human existence. Transhumanists believe that, properly harnessed, such integration can become a force of ultimate good. Reaching dominance in the technology sector, transhumanism's tenets and predictions have begun to drive the actions of multinational companies such as Google. If technology is left to take its current path, what are the plausible outcomes? How does the accelerating pace of technology stand to change the world's economy and the lives of average citizens? What risks (economic and ethical) are there to the fulfillment of transhumanist ideals by corporate powers, and how might they be mitigated? This dissertation makes no claim to a concrete solution, but raises the issues which are beginning to confront modern business and political leaders, and will only grow in the future. It implores such leaders to look further, and to make preparations to employ the advances to come to their best advantage, and to the best advantage of 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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.432
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.004
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.316
GPT teacher head0.441
Teacher spread0.125 · 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; both teacher heads agree on what is shown here.

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
Published2018
Admission routes1
Has abstractyes

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