Beyond “Alexa, good morning”: prerequisites for a voice assistant that truly understands older adults with empathy
Bibliographic record
Abstract
Older adults show interest in technological resourcesa perception we were able to confirm through field tests conducted with 20 individuals aged between 60 and 89 in Portugal.Participants were challenged to use the virtual assistant Alexa to contact family members and perform other daily activities.A total of 6,301 interactions were recorded during the study, across different categories.The analysis of these interactions, combined with post-test interviews and the results of a loneliness scale, revealed gaps that hindered the interaction between Alexa and the participants.As a result, we were able to identify key requirements for the development of a more empathetic and age-appropriate voice assistant.In summary, the findings point to the potential of such technology to reduce loneliness and facilitate communication with family members, while also highlighting limitations related to language and command comprehension.Based on the results, we propose a set of design requirements for a virtual assistant tailored to the needs of older adults.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".