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Record W3082637199 · doi:10.3991/ijai.v2i2.16759

Fearing the Robot Apocalypse: Correlates of AI Anxiety

2020· article· en· W3082637199 on OpenAlexaff
David John Lemay, Ram B. Basnet, Tenzin Doleck

Bibliographic record

VenueInternational Journal of Learning Analytics and Artificial Intelligence for Education (iJAI) · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicEthics and Social Impacts of AI
Canadian institutionsMcGill University
Fundersnot available
KeywordsFunctional illiteracyAnxietyPsychologyApplied psychologyClinical psychologyDevelopmental psychologyPolitical sciencePsychiatry

Abstract

fetched live from OpenAlex

This study examines the relationship between individuals’ beliefs about AI (Artificial Intelligence) and levels of anxiety with respect to their technology readiness level. In this cross-sectional study, we surveyed 65 students at a southwestern US college. Using partial least squares analysis, we found that technology readiness contributors were significantly and positively related to only one AI anxiety factor: socio-technical illiteracy. In contrast, all four links between technology readiness inhibitors and AI anxiety factors were significant with medium effect sizes. Technology readiness inhibitors are positively related to learning, fears of job replacement, socio-technical illiteracy, and particular AI configurations. Thus, we conclude that AI anxiety runs through a spectrum. It is influenced by real, practical consequences of immediate effects of increased automatization but also by popular representations and discussions of the negative consequences of artificial general intelligence and killer robots and addressing technology readiness is unlikely to mitigate effects of AI anxiety.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.545
Threshold uncertainty score0.488

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.089
GPT teacher head0.420
Teacher spread0.331 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations43
Published2020
Admission routes1
Has abstractyes

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