Bibliographic record
Abstract
Many problems in the ethics of technology arise because our ethical conventions take time to adapt to our technology. Workplace surveillance is a good example. This chapter develops some of the ethical issues raised by surveillance technology in the workplace, using a framework of informal game theory. One leading approach to workplace surveillance, following Foucault’s Panopticon metaphor, emphasizes the power of employers over employees; another looks at unexpected consequences from a managerial perspective. Our analysis shows that both of these approaches have more structure than is often noticed, yielding new alternatives for ethical policy recommendation. On the one hand, even those under surveillance by the more powerful have options, and the equilibrium includes outcomes not preferred by the more powerful player. On the other, most surveillance systems have at least two equilibria. Here, ethics has an important role in helping agents choose and maintain socially better equilibria. A number of policy recommendations follow from this approach. This chapter deploys a framework of informal game theory to elucidate some of the ethical issues raised by surveillance technology in the workplace. We do not use “games” in our title to diminish the importance of the issues we discuss, but rather to highlight their interactive, strategic, and dynamic aspects. This chapter focuses on how alternatives are structured by new electronic workplace surveillance technologies, yielding new opportunities for ethics. This chapter extends the approach of Danielson (2002b) to support recommendations for policy in the workplace.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".