Data Collection for ML Models: Strategies and Protocols for Ensuring Dataset Integrity

Explore the intricate process of data collection: from acquisition methods to ethical considerations.

Authors: TIMNIT GEBRU, Black in AI; JAMIE MORGENSTERN, University of Washington; BRIANA VECCHIONE, Cornell University; JENNIFER WORTMAN VAUGHAN, Microsoft Research; HANNA WALLACH, Microsoft Research; HAL DAUMÉ III, Microsoft Research; University of Maryland; KATE CRAWFORD, Microsoft Research. Table of Links 1 Introduction 1.1 Objectives 2 Development Process 3 Questions and Workflow 3.1 Motivation 3.2 Composition 3.3 Collection Process 3.4 Preprocessing/cleaning/labeling 3.5 Uses 3.

1 Motivation 3.1 Motivation 3.2 Composition 3.2 Composition 3.3 Collection Process 3.3 Collection Process 3.4 Preprocessing/cleaning/labeling 3.4 Preprocessing/cleaning/labeling 3.5 Uses 3.5 Uses 3.6 Distribution 3.6 Distribution 3.7 Maintenance 3.7 Maintenance 4 Impact and Challenges 4 Impact and Challenges Acknowledgments and References Acknowledgments and References Appendix Appendix 3.

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