LIVING WITH A ROBOT AT HOME: THE COMPLEXITY OF LIVING WITH ASSISTIVE ROBOTS LABRADOR AND DOUBLE IN EVERYDAY LIFE
Bibliographic record
Abstract
Abstract The potential for assistive robots to support older adults’ independence and social connections requires careful consideration of their implications in everyday use. This study investigates the use of two assistive robots, Labrador and Double, in older adults, guided by Actor-Network Theory (ANT). Labrador (a delivery robot) assists with medication management, meals, laundry, house cleaning to support independence, while Double (a teleprence robot) enables virtual social visits. ANT offers a way to understand how the robots interact with different actors, such as older adults, family members, staff, and the environment in which they operate. We applied a qualitative approach to explore how users construct meanings, use, and make sense of the robots in their everyday contexts. Semi-structured interviews and ethnographic fieldwork were conducted with participants to generate data. Reflexive thematic analysis was performed, and three themes emerged: (1) the human-robot relationship, (2) the robot’s agency, and (3) ethical implications. The findings suggest that having the robots in everyday life is a process of constant negotiation with the people, practice, and the robot. The study highlights the challenges and opportunities associated with the implementation of robots to improve quality of life in senior care. While there is a fear that assistive robots will dehumanize caring practices, our study shows that they have the potential to foster innovative user-technology relationships, which requires further research.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| 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".