Minority Reports from 2054: Building Collective and Critical Forecasting Imaginaries via Afrofuturetypes and Game Jamming
Bibliographic record
Abstract
Imagined affordances reflect the imagined applications that users have for technology compared with what designers intend, including their own values and expectations that inform these imagined actions. For our purposes, imagined affordances enable black people in the diaspora to strive for affirmation within hostile environments that have accompanied slavery and its traumatic aftermath. This article presents pedagogical research in speculative black futurism, turning to our Minority Reports 2054 Game Jam, first held at California State University, East Bay in spring 2017, as a model for forecasting Afrofutures. In our forecasting pedagogy, we ask students from marginalized working-class communities to reimagine their social, media and digital spaces into the year 2054—the imagined year for the film Minority Report—thereby highlighting the “minority reports” of future visions too often ignored. We explain the forecasting processes developed for systematically imagining viable black futures by revisiting ancient black cultural rituals, such as the Brazilian adaptation of the African Kongo cosmogram. We also meld the latest methodological tools for scanning future trends to reposition them as “Afrofuturetypes” that trace past, present and future. Afrofuturetypes describe the building exercises of and outcomes via the Game Jam, whereby students create socially interactive games that aim to generate stories of 2054 with black futures in mind.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".