On the Readiness of Scientific Data Papers for a Fair and Transparent Use in Machine Learning
Abstract To ensure the fairness and trustworthiness of machine learning (ML) systems, recent legislative initiatives and relevant research in the ML community have pointed out the need to document the data used to train ML models. Besides, data-sharing practices in many scientific domains have evolv...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-01-01
|
| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-04402-4 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|