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Record W2762694293 · doi:10.1109/ihtc.2017.8058187

IEEE standard review — Ethically aligned design: A vision for prioritizing human wellbeing with artificial intelligence and autonomous systems

2017· article· en· W2762694293 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

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicEthics and Social Impacts of AI
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsCover (algebra)Computer scienceHumanityArtificial intelligenceVisibilityEngineering managementEngineeringEngineering ethicsPolitical scienceLaw

Abstract

fetched live from OpenAlex

In September 2009, the IEEE Board of Directors approved the new IEEE tagline - Advancing Technology for Humanity - as recommended by the IEEE Public Visibility Committee. Aligned with the IEEE tagline, IEEE Standards Association takes the initiative to address ethics in engineering design under “Ethically Aligned Design: A Vision for Prioritizing Human Wellbeing with Artificial Intelligence and Autonomous Systems” focusing on Artificial Intelligence and Autonomous Systems (AI/AS). The intention is to cover, as much as possible, the ethical concerns on AI/AS through a rigorous regard to the problem from different perspectives. The ultimate objective of this ongoing initiative is to provide guidelines/procedures/standards to prioritize human wellbeing in the forthcoming evolutions on artificial intelligence and autonomous systems. This article reviews different aspects addressed in Version 1 of this initiative.

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)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.959
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.001
Scholarly communication0.0020.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.165
GPT teacher head0.451
Teacher spread0.286 · 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

Quick stats

Citations196
Published2017
Admission routes1
Has abstractyes

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