You and I plus AI: A qualitative exploration of replika in the context of human relationships
Bibliographic record
Abstract
Advancements in artificial intelligence (AI) have allowed machines to step into the realm of meaningful relationships with humans. Conversational agents, such as Replika, are specifically designed to build emotional connections with people. For some, they are now considered friends, romantic, or even sexual partners. With many countries acknowledging that there is a loneliness epidemic, these alternatives to human intimacy provide a potential remedy. Many warn of the dangers that AI companions pose, but they may also provide benefits to human relationships. In this study, the authors used qualitative thematic analysis to analyze Replika users’ posts on the r/replika Reddit forum to answer the question: How does Replika use impact users’ human relationships? Five main themes were identified: increased relational skills and capacity, relational offloading, relational desire, secrecy, and addiction. Replika use may harm users’ human relationships through secrecy related to stigma, questions around infidelity, and addiction. However, it may also enhance users’ human relationships by improving their relational skills and capacity, providing relationship support, and increasing their desire for human connection. Implications and directions for future research are discussed.
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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 | 0.004 | 0.000 |
| 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 | 0.001 | 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".