Individual differences in anthropomorphism help explain social connection to AI companions
Bibliographic record
Abstract
People increasingly use conversational AI for support and companionship. Yet, current discourse on AI companions reveals a stark divide: some scholars argue that feeling connected to AI is impossible due to AI's inability to experience emotions, while others contend that AI's ability to provide the illusion of emotions is enough. Across two experiments (one pre-registered; Total N = 1274), we investigated whether accounting for individual differences in anthropomorphism could help bridge these two perspectives. Participants completed a measure of anthropomorphism and were then randomly assigned to discuss their past month through a conversation with a chatbot (chatbot condition) or by journaling (control condition) and then completed a measure of social connection. Our results suggest that for some individuals, AI's artificial nature may pose an insurmountable barrier to meaningful connection; for others, however, this artificiality may be a minor obstacle, easily overcome by a tendency to anthropomorphize.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".