“You bet she can fuck” – Trends in Female AI Narratives within Mainstream Cinema: Ex Machina and Her
Bibliographic record
Abstract
In today's digital age, we are becoming more like machines and machines are becoming more like us. Donna Haraway's seminal essay, "A Cyborg Manifesto," proposes the cyborg as a transgressive figure capable of subverting oppressive power structures. While there is no denying this powerful imagery, what are the common trends in female AI narratives in mainstream cinema? This paper examines the films Ex Machina (2015) and Her (2013), which both feature male human protagonists and female AIs (Ava, a feminized robot in Ex Machina and Samantha, a female operating system in Her). Ava's and Samantha's highly sexual yet innocent characterizations and similar desires for freedom are reflective of societal anxieties surrounding male control over female agency. As gendered AIs continue to populate our media, one can only hope that we can live up to Haraway's vision of the cyborg, and expand the scope of our questions and concepts past male pleasure and women as research-fetish objects.
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How this classification was reachedexpand
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 | 0.001 | 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) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".