Bibliographic record
Abstract
Most computers during the Second World War, such as the British code-breaking Colussus machine, had been developed for military use. The effects on law and order and war and peace of computerization, worldwide telecommunications, social media, artificial intelligence (AI), and robotics is the topic of Chapter 6. As in Chapter 5, the most compelling visions of the potential opportunities and dangers have been in science fiction and in film; we begin the chapter by reviewing some memorable examples. We then discuss how technology is used by the police, such as the use of video evidence to sometimes exonerate the police against false accusations of needless brutality. We also examine how citizens are using social media to protect themselves and alert others to what they believe is unwarranted violence or unjust actions by law enforcement. We expand upon Section 5.7’s discussion of citizen mobilization by social media with the goal of regime change. In this context, we discuss how the government (especially police and security services) gains leverage via the surveillance of the digital information and communications of citizens. This surveillance has significantly increased due to security concerns post-9/11. We will examine these developments in the USA, Canada, and the UK, as well as in other parts of the world. We shall also discuss cases of organizations trying to subvert societies that repress and forbid access to the internet, with the goal of enabling its citizens to access the internet freely. Next, we consider ways in which tools of digital disruption are used by a country or government or a set of individuals against others. The timely and current case study explored is on governmental use of hacking and other aggressive digital means to interfere with the electoral processes of another country, or even to disrupt or destabilize the other country. At the extreme, governments engage in cyberterrorism or even cyberwarfare. We shall discuss several recent examples of this and argue that weapons of cyberwarfare could be as catastrophic as nuclear or biological weapons. The technology of warfare has also evolved.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.039 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".