Overfitting in AI Models Discouraged in Data Science Competition: A Case Study on Kaggle's The Nature Conservancy Fisheries Monitoring
May 1, 2017
In the 'The Nature Conservancy Fisheries Monitoring' competition on data science platform Kaggle, competitors overfit their image classifier models to an unrepresentative validation dataset. This incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). To prevent similar incidents and promote trustworthy AI, join us.JOIN US
- Alleged deployer
- individual-kaggle-competitors
- Alleged developer
- individual-kaggle-competitors
- Alleged harmed parties
- individual-kaggle-competitors
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/61
Data source
Incident data is from the AI Incident Database (AIID).
When citing the database as a whole, please use:
McGregor, S. (2021) Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database. In Proceedings of the Thirty-Third Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-21). Virtual Conference.
Pre-print on arXiv · Database snapshots & citation guide
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