Evitable Conflicts, Inevitable Technologies? The Science and Fiction of Robotic Warfare and IHL
Bibliographic record
Abstract
This article contributes to a special symposium on science fiction and international law, examining the blurry lines between science and fiction in the policy discussions concerning the military use of lethal autonomous robots. In response to projects that attempt to build military robots that comport with international humanitarian law [IHL], we investigate whether and how the introduction of lethal autonomous robots might skew international humanitarian norms. Although IHL purports to be a technologically-neutral approach to calculating a proportionate, discriminate, and militarily necessary response, we contend that it permits a deterministic mode of thinking, expanding the scope of that which is perceived of as “necessary” once the technology is adopted. Consequently, we argue, even if lethal autonomous robots comport with IHL, they will operate as a force multiplier of military necessity, thus skewing the proportionality metric and amplifying new forms of destructive, lethal force.
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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 | 0.001 |
| 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 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".