Compassionate Digital Innovation: A Pluralistic Perspective and Research Agenda
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 Digital innovation offers significant societal, economic and environmental benefits but is also a source of profound harms. Prior information systems (IS) research has often overlooked the ethical tensions involved, framing harms as ‘unintended consequences’ rather than symptoms of deeper systemic problems. In response, this paper presents a problematization review that critiques and revises three widely held assumptions about digital innovations: (1) that they generate net benefits that outweigh the associated harm; (2) that their ethicality can be calculated through utility and (3) that their harms can be mitigated through technological, corporate or regulatory intervention. We argue that compassion provides a pluralistic ethical foundation that integrates the strengths of consequentialism, deontology, and virtue ethics. This framework prioritises serving all stakeholders, especially the most vulnerable, while avoiding harm. It sets a research agenda focused on addressing structural dysfunctions, amplifying marginalised voices, and fostering sustainable systems. By reimagining digital innovation as a force for the common good, this paper contributes to a more just and equitable digital future for all.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.005 |
| 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