Applications of ML Model Datasets

10 Jun 2024


(1) TIMNIT GEBRU, Black in AI;

(2) JAMIE MORGENSTERN, University of Washington;

(3) BRIANA VECCHIONE, Cornell University;

(4) JENNIFER WORTMAN VAUGHAN, Microsoft Research;

(5) HANNA WALLACH, Microsoft Research;

(6) HAL DAUMÉ III, Microsoft Research; University of Maryland;

(7) KATE CRAWFORD, Microsoft Research.

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

3.6 Distribution

3.7 Maintenance

4 Impact and Challenges

Acknowledgments and References


3.5 Uses

The questions in this section are intended to encourage dataset creators to reflect on the tasks for which the dataset should and should not be used. By explicitly highlighting these tasks, dataset creators can help dataset consumers to make informed decisions, thereby avoiding potential risks or harms.

• Has the dataset been used for any tasks already? If so, please provide a description.

• Is there a repository that links to any or all papers or systems that use the dataset? If so, please provide a link or other access point.

• What (other) tasks could the dataset be used for?

• Is there anything about the composition of the dataset or the way it was collected and preprocessed/cleaned/labeled that might impact future uses? For example, is there anything that a dataset consumer might need to know to avoid uses that could result in unfair treatment of individuals or groups (e.g., stereotyping, quality of service issues) or other risks or harms (e.g., legal risks, financial harms)? If so, please provide a description. Is there anything a dataset consumer could do to mitigate these risks or harms?

• Are there tasks for which the dataset should not be used? If so, please provide a description.

• Any other comments?

This paper is available on arxiv under CC 4.0 license.