Critique of the Necropolitical Economy of The Internet of Things: Brains, Biohacking, and Social Apartheid
Bibliographic record
Abstract
Science and technology are converging with centralized political and economic interests in research fields and industries such as neurology, weapons manufacturing, AI, biosurveillance, and human augmentation. This convergence is international in scope and entails a technoscientific intensification of anti-democratic governing procedures. It therefore poses an international challenge to democracy. In this paper, I critically survey diverse applications of a key governing procedure according to which this convergence is being engineered. I also highlight apposite features of the political/libidinal economy through which it operates. To do so, I merge Achille Mbembe’s analyses of necropolitics/necropower with Deleuze and Guattari’s diagrammatic analyses of paranoic-fascisizing procedures of unconscious social production, linking both to the IoT. With the latter established as a universal infrastructure, necropower deploys global and specific (in contrast to partial and nonspecific), anti-democratic integrative procedures in both scientific R&D and geopolitics to decode the human brain, hack biosystems, and engineer social apartheid.
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.
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 | 0.002 | 0.001 |
| 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 | 0.002 | 0.001 |
| 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".