Users, Tasks, and Conversational Agents: A Personality Study
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
Conversational Agents (CA) have become one of the common user interfaces in many online domains. In this paper, we ask whether users have a preference about the personality of CAs, and whether this preference changes depending on the length and type of the tasks CAs are used for. In an online study (N = 410), we investigated three different CA personalities (introvert, extrovert, and non-personified) in four different tasks with different natures and lengths (teaching, booking, todo, and weather). Most of the participants preferred to interact with a conversational agent (introvert or extrovert) as opposed to a non-personified interface, regardless of their own personality. Results suggested that this preference may be task dependent: when CA’s goal was to provide information, participants preferred an extrovert agent. We did not observe a difference between the preference for introvert and extrovert agents when the task’s goal was to complete an assignment.
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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 | 0.000 |
| 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) | 0.001 | 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 it