Human Improvised Theatre Augmented with Artificial Intelligence
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
Improvisational theatre (improv) has been proposed as a grand challenge for general artificial intelligence (AI)~\citemartin2016improvisational. Current state-of-the-art conversational intelligence models lack proper grounding, language understanding, and generate meaningless meandering responses~\citedziri2018augmenting. Utilizing them as improvised comedy partners (improvisors) is doomed to fail - curiously, this limitation makes their use particularly appealing. Improv theatre celebrates risk taking and failure by inviting performers to express themselves without hesitation or fear of being judged~\citejohnstone1979impro. Our installation is an interactive improv workshop for a group of interested participants, culminating in a live public performance. Attendees are invited to observe and interact with AI-based improvisational theatre technology. The workshop is facilitated by two improv theatre professionals with a combined 30 years of experience in teaching, training, and touring. The performance features various AI tools for augmented creativity.
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 | 0.000 |
| 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) | 0.001 | 0.002 |
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