Lessons Learned from Kaggle's Fisheries Competition: Emphasizing Responsible AI Governance
Exploring the implications of a data competition, this article highlights the importance of responsible AI governance in the fisheries domain. By focusing on the role of trustworthy AI and safe data practices, we demonstrate how Project Cerebellum's AI incident database can aid harm prevention efforts. Ready to join our mission? JOIN US This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM).
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
We use weekly snapshots of the AIID for stable reference. For the official suggested citation of a specific incident, use the “Cite this incident” link on each incident page.