Articulating AI futures for Brazil: on different regimes of technological solutionism
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 study of expectations in innovation policy has gained prominence over the past decade . A key concern has been the belief that complex social problems can ultimately be resolved through technological innovation, a perspective termed technological solutionism. However, the existing literature mainly focuses on North America and Europe, offering a homogeneous understanding of technological solutionism and a normative view of how these expectations affect the Global South . This paper employs critical discourse analysis, in dialogue with the sociology of expectations, and Latin American science and technology studies, to examine technological solutionism in connection with two recent Brazilian policy documents: the Brazilian Strategy of Artificial Intelligence (EBIA) and the Fapesp Call for Applied AI Research Centers. It argues that, in Brazil, technological solutionism is linked to a very specific concern: the one of dependency. Thus, adopting technosolutionist imperatives would be seen as the best remedy against ‘underdevelopment’, impeling Brazil to ‘leapfrog’ and catch-up advanced nations. The paper calls for critical approaches to regimes of technological solutionism whose consolidation and hegemony are tied to the role Global South countries have in global capitalism and international policy.
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 | 0.006 |
| 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 | 0.001 |
| 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