Science Is Open Software
- ID
- 26560
- Status
- summarized
- Published
- 19 Sep 2026, 10:21 AM
- Fetched
- 21 Sep 2026, 6:17 AM
- Provider
- Hacker News
- Category
- dev-community
- Original URL
- https://jepedersen.dk/blog/202505_research/
- Source URL
- https://hnrss.org/best
Summary
- Score
- 5.5
- Created
- 21 Sep 2026, 6:19 AM
- Tags
- Audience
- developersai_ml_learners
What happened
Jens Egholm Pedersen argues that computational science is effectively synonymous with open source software, because science requires testable, reproducible models and software is how those predictive models are encoded and shared. He frames open source not as a side activity but as the core scientific method for computational fields, challenging academia's tendency to treat code as a disposable time sink.
Why it matters
If you build or rely on computational tooling—ML models, data pipelines, research code—this is a reminder that without open, reproducible software your results are not independently verifiable. For builders shipping AI/ML systems, this argues for treating your code and data pipelines as the actual scientific artifact, not just the paper or the demo.
Discussion angle
Where's the line between 'open source as science' and the reality that most production ML code is proprietary, messy, and never reproducible—does the argument apply outside academia?