CRISPR Gene-Therapy: A Critical Review of Ethical Concerns and a Proposal for Public Decision-Making
Bibliographic record
Abstract
CRISPR is currently viewed as the central tool for future gene therapy. Yet, many prominent scientists and bioethicists have expressed ethical concerns around CRISPR gene therapy. This paper provides a critical review of concerns about CRISPR gene therapy as expressed in the mainstream academic literature, paired with replies also generally found in that literature. The expressed concerns can be categorised into three types depending on whether they stress risk/benefit ratio, autonomy and informed consent, or concerns related to various aspects of justice. In the reviewed literature, we found no intrinsic objections to CRISPR gene therapy, even though many such objections were present in discussions of gene editing in the 1990s. The paper then proposes a brief outline for a practically applicable moral framework for public decision-making about CRISPR gene therapy and suggests how such a framework might be supported. We also suggest that this framework should govern public engagement about CRISPR gene therapy in order to reduce the risk that we make decisions about CRISPR gene therapy based on misperceptions, inflated views of risk, or unreasonable moral or religious views.
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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 | 0.013 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.008 | 0.009 |
| 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".