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Record W4295955091 · doi:10.1145/3543829.3543841

Does Alexa Live Up to the Hype? Contrasting Expectations from Mass Media Narratives and Older Adults' Hands-on Experiences of Voice Interfaces

2022· article· en· W4295955091 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
FieldComputer Science
TopicAI in Service Interactions
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNarrativeSoftware deploymentPerceptionPsychologyEcho (communications protocol)Amazon rainforestRelation (database)Internet privacyComputer scienceComputer security

Abstract

fetched live from OpenAlex

Voice user interfaces (VUIs) are advertised as easy to use and beneficial to older adults (OAs). Disparities between expectations and OAs’ hands-on experiences with VUIs may discourage OAs’ further use of VUIs and widen digital divides. To understand such disparities, we conducted two-week in-home field deployments of the Amazon Echo Dot with OAs. We interviewed participants before and after deployment on their perceptions of VUIs in relation to prevailing media-derived expectations about VUIs. Our analysis revealed mismatches between expectation and hands-on experiences with VUIs; namely, VUIs were found to be more primitive than expected, there were more limitations to VUIs than expected, more prerequisites were required to fully make use of VUIs, and the sources that VUIs drew from fell short in earning trust. Our findings contribute aspects to be considered to close the gap between expectations and experiences related to VUIs for older adults.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.590

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.252
Teacher spread0.240 · 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

Citations19
Published2022
Admission routes1
Has abstractyes

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