Physical Robot or Virtual Agent? Humans’ Preferences in Human-AI Intimate Relationships
Bibliographic record
Abstract
Artificial intelligence (AI) is transforming the way humans engage in intimate relationships, taking on roles such as friends, romantic partners, pets, and therapists. However, little is known about humans’ preferences between physical robots and virtual agents in these relationships. This pilot study found variations in the roles envisioned (86% of participants envisioned AI as a friend, 75% as a therapist and 72% as a mentor, 17% as a romantic or sexual partner; caregiver and pet roles stood in the middle, with greater willingness to have an AI care for an older parent or oneself than a child). Individuals strongly preferred physical robots over virtual agents in all except therapeutic and mentoring relationships. Different factors drove these preferences, such as lifelike interaction and functional utility for physical robots and accessibility and cost effectiveness for virtual agents. These findings deepen our understanding of human-AI interactions and guide the development of human-centered AI.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".