Contextualizing Technological Stewardship: Origins and Implications of an Approach to Responsible Tech Development
Bibliographic record
Abstract
The Multiplicity of "Stewardship" Technological stewardship, or "tech stewardship," is a concept used by some engineering educators as part of strategies to encourage responsible technological development.In the context of Canadian engineering education, the most prominent use of this term is in the Tech Stewardship Practice Program (TSPP), an online course in which several thousand participants -largely undergraduate engineering students at Canadian universitieshave enrolled since 2021 [1].The TSPP positions the term "tech stewardship" as "professional identity, orientation, and practice" with the goal of "bend[ing] the arc of technology towards good," [2].Although the program differentiates the term from other approaches to responsible technological development, understandings of, and approaches to technological stewardship are not the same across all contexts.Other engineering education programs and scholars present technological stewardship in close relation to concepts like social responsibility [3] or responsible innovation [4], or use the term to describe a process of pedagogical design for the engineering classroom, rather than a practice for engineers to engage in [5].Within the TSPP itself, 'tech stewardship' is defined in relation to a set of behaviors.Different parts of the program and related publications describe tech stewardship as a mindset, a practice, and a contributor to cultural change within engineering [6].However, the theoretical grounding of the concept, and its relationship to other ways of teaching and practicing engineering ethics or design, is not discussed within the TSPP itself, nor in its related materials.The authors of this paper are members of a cross-institutional research team studying the effects of the TSPP on students' understandings of engineering responsibility [1].As we began our project in January 2023, the multiple meanings of "tech stewardship"and of "stewardship" itselfbecame apparent.We noticed the word "stewardship" in diverse contexts, including in scholarly literature, on the news, and on our garbage and recycling bins.We spent team meetings discussing the relationship between the "tech stewardship" of the TSPP and notions of stewardship in other contexts: religious, environmental, Indigenous, policy-based, and design-focused.How did the "tech stewardship" of the TSPP position engineers?What was its relationship to the engineering culture that the TSPP founders sought to change?Was it challenging the status quo, or reinforcing it?After two team members stumbled across a book produced by the National Council of the Churches of Christ in the United States, titled, Teaching and Preaching Stewardship [7], we decided that deeper inquiry into the concept of stewardship was a necessary part of our research.Language, as Williams argues [8], is not a neutral medium for communication.Instead, words are powerful tools that change over time and carry cultural and historical meaning, shaping our practices, thinking, and interactions with the world.When navigating concepts such as technological stewardship, clear definitions enable us to critically engage with them
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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 | 0.025 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.013 | 0.052 |
| Scholarly communication | 0.020 | 0.023 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".