Position: Unlabeled IS NOT Equal to No Human Supervision in Visual Learning
This episode examines the paper "Position: Unlabeled IS NOT Equal to No Human Supervision in Visual Learning. Hosts discuss how modern AI models, despite being labeled "unsupervised," rely heavily on specific human choices and foundational infrastructure. The discussion concludes that making these implicit dependencies explicit is crucial for scientific integrity and building robust systems.