MeetupAgile AI Ethics: Balancing Short Term Value with Long Term Ethical OutcomesThreads / Humans in the loop / 2021
Humans in the loop in 2021
6 sessions
MeetupProduct Management in Machine LearningClaimLaszlo Sragner says monitoring, evaluation, and labeling are tightly coupled and should happen as one continuous process for machine learning models.9:51
PodcastData Selection for Data-Centric AI: Data Quality Over QuantityPushed backCody Coleman argues against using all available data by default, because noisy data and labels increase cost and difficulty.41:11
MeetupData-Centric AI Means Centralizing Training DataPushed backAlberto Rizzoli disputes the usefulness of treating ImageNet as a fully reliable benchmark because some classes contain substantial labeling errors.13:47
PodcastThe Future of AI and ML in Process AutomationClaimSlater Victoroff says changing an OCR engine can invalidate labels when labels are stored only as positions in extracted text.23:25