The “silence of the chips” concept: towards an ethics(-by-design) for IoT
Bibliographic record
Abstract
In this position paper, we would like to promote the alternative approach positioned between the two extreme positions consisting in refusing any innovation or in adopting technology without questioning it. This approach proposes a reflexive and responsible innovation (von Schomberg, 2013; 2011; 2007) based on a compromise between industrial and economic potentialities and a common respect of our human rights and values. We argue that the “silence of the chips right” (Benhamou, 2012; 2009) is timely, relevant and sustainable to face ethical challenges raised by IoT such as protecting privacy, trust, social justice, autonomy or human agency. We believe this technical solution may support establishing an ethics of IoT embedded in the technology itself. Our position is not ‘technocratic’: we do not agree with discourses arguing technology can fix problems. Through the responsible research and innovation approach we promote the idea that only human agency and user empowerment constitute a valid answer to the ethical, legal and social issues raised by IoT.
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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 | 0.050 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.085 |
| Scholarly communication | 0.016 | 0.023 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.015 | 0.017 |
| Insufficient payload (model declined to judge) | 0.002 | 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".