The rights and wrongs of robotics: Ethics and robots in public organizations
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 Some electronics experts believe that robots, like present‐day computers, will be commonplace. A diverse assortment of robots, with varying purposes, capacities, forms, and sizes, is emerging with significant implications for the policy, service and regulatory responsibilities of government. This paper explores three public policy fields – aging, health care and defence – where the use of robotics is already substantial or where it is projected to grow substantially and where significant ethical issues exist or are anticipated. Applying ethical theories to the use of robotics is difficult. In the near‐term, the focus should be on the ethical standards and behaviour of those designing, manufacturing, programming and operating robots. Several key topics in contemporary public sector ethics, including personal moral responsibility, privacy and accountability, are central to the emerging field of robot ethics. This suggests developing an ethics regime for robotics and examining the need for laws and regulations governing its use.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 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