“I Don’t Want To Shoot The Android”: Players Translate Real-Life Moral Intuitions to In-Game Decisions in Detroit: Become Human
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
In interactive story games, players make decisions that advance and modify the unfolding story. In many cases, these decisions have a moral component. Examining decision-making in these games illuminates whether players mobilize their real-life morality to make in-game decisions and what impact this has in both the game world and real life. Using mixed-methods consisting of semi-structured interviews and the Moral Foundations Questionnaire (MFQ30), we collected data from 19 participants who played the game Detroit: Become Human. We analyzed how participants applied their real-life morals toward in-game decisions using thematic analysis and statistical analysis of the MFQ30 results. Qualitative findings indicate that participants mobilize their moral intuitions to make in-game decisions and how much participants cared about their game characters influenced their choices. We contribute a better understanding of how players react to moral dilemmas in interactive story games for game designers to help them improve player experience.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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