Questioning the questions we ask about the impact of AI on software engineering
Bibliographic record
Abstract
The recent advent and wide diffusion of generative AI has initiated a fundamental change in how software is developed. This technology is just one innovation along a long arc of disruptions in software engineering that include the internet, high-level programming languages, integrated development environments, open source, agile development, and social coding environments. Disruptive technologies such as these show the potential to augment and accelerate development activities along many socio-technical dimensions, while altering fundamental business processes and paradigms. Yet paradoxically, these innovations have the potential to eventually undermine the very advancements they seek to promote, rendering technologies and methods obsolete [1].
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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 | 0.023 | 0.085 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.063 |
| Scholarly communication | 0.014 | 0.053 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.017 | 0.020 |
| Insufficient payload (model declined to judge) | 0.014 | 0.005 |
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".