Can Chatbots Ever Provide More Social Connection Than Humans?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Around the world, hundreds of millions of people have used social chatbots designed to provide companionship to their users. But can people reap genuine social benefits from interacting with chatbots? In Studies 1a&b (pre-registered; N=801), participants shared good news with a supportive or less supportive interaction partner whom they believed was either a chatbot or a human. Participants’ feelings following the interaction were influenced by their partner’s response style, but not by whether their partner was human. In Study 2 (pre-registered, N=201), participants derived more social connection from having a supportive conversation with ChatGPT than with a less supportive human. In a final pre-registered study (Study 3; N=401), we identified an important boundary condition, demonstrating that the relative benefits of interacting with chatbots (vs. humans) may be reduced when they claim too much humanity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 it