Comfort and Data Sharing With Artificial Companion Robots Among an Online Cohort
Bibliographic record
Abstract
Abstract Results from a June 2020 survey on comfort with two forms of artificial companion (AC) robots in normal compared with pandemic times will be presented. 1,082 adults age 21-92 (mean 64) completed the online survey for a response rate of 45%. Significantly greater comfort is reported with small AC robots relative to larger human-shaped robots in both normal and pandemic times. In bivariate and adjusted models, younger age and male gender were most commonly associated with greater comfort with AC robots. Most participants (68.7%) did not think an AC robot would make them feel less lonely. About half (52.8 %) of the participants reported that they probably or definitely would want their facial expressions to be read, while a minority (15.0%) were at least somewhat comfortable with AC robots recording their conversations. The most common person participants wanted these data types shared with is themselves, a spouse/partner, and medical provider.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".