Comparative Designs Reveal Preferences for Human-Generated Rather Than AI-Generated art
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
The evaluation of AI-generated art has seen increased interest after widespread access to AI-generated art (e.g., DALL-E or Stable Diffusion). While previous studies have suggested that there are preferences for human-generated art, the research remains far from robust with numerous contradictory findings. One potential reason for this discrepancy is differing experimental designs employing comparative or non-comparative methods. To shed light on this problem, two experiments were conducted: one using a Likert scale (N = 250) and another using a 2-alternative forced choice design (N = 102). Our conflicting results between the two designs suggest that traditional Likert-based art appraisals in non-comparative formats may not be sensitive enough to reliably detect preferences that a forced-choice task can reveal. While AI-generated art continues to become more mainstream, people tend to prefer human art in terms of their liking and valuation appraisals when measured in comparative designs that better approximate real-world interaction with art.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 it