Ethical Tech Pedagogy for Public Good: A Review of Educational Initiatives and Approaches
Bibliographic record
Abstract
Our research team is conducting a scoping literature review of scholarly and popular publications that address the role of ethics and ethical thinking in relation to engineering education curriculum, professional engineering practices more broadly, and their integration in the tech sector at large. This paper reports on the preliminary results of that review, which so far covers current approaches (i.e. from the last ten years) to cultivating and scaling these principles in academia and industry, and also examines local initiatives that implement some of these ideas in the classroom. We (a) identify recent knowledge and gaps on effective approaches to embedding ethics in engineering curriculum, including pedagogies that mobilize novel collaborative instruments and technologies for engaging the public; and (b) describe current academic approaches to centering ethics and ethical thinking as core elements of training and professional practice at the University of Waterloo (Ontario, Canada). In keeping with the 2021 ISTAS “Public Interest Technology” theme, the paper emphasizes efforts underway to train professional and aspiring engineers in North America with the integrated critical thinking skills they need to ethically assess the social and cultural impacts of the technologies they design, develop, and deploy.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".