Artificial intelligence and the future of nationalism
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
Abstract Artificial intelligence (AI) is spreading through all walks of life, promising social and economic disruptions that prompt comparisons with the Industrial Revolution. While there is growing interest in AI ethics and its implications for humanity, there has been surprisingly little consideration of its implications for national identities and nationalism. This paper argues that the transformation of citizens into population data is driving changes to state sovereignty and that the simultaneous competition between (and within) states and global corporations on a structural level and expansion of algorithmic population management on a quotidian level may crystallize in ways that are likely to produce nationalist responses. It concludes by proposing a number of causal mechanisms and hypotheses regarding the emergence and spread of “AI nationalism.” Scholars in nationalism studies can benefit substantially from embracing the study and applications of AI, though they ignore its development and spread at their peril.
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 | 0.001 | 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 | 0.000 |
| 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