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Much Ado About Gender: Current Practices and Future Recommendations for Appropriate Gender-Aware Information Access
Information access research (and development) sometimes makes use of gender, whether to report on the demographics of participants in a user study, as inputs to personalized results or recommendations, or to make systems gender-fair, amongst other purposes.
Reduced, Reused and Recycled: The Life of a Dataset in Machine Learning Research
Despite the foundational role of benchmarking practices in this field, relatively little attention has been paid to the dynamics of benchmark dataset use and reuse, within or across machine learning subcommunities.
AI and the Everything in the Whole Wide World Benchmark
There is a tendency across different subfields in AI to valorize a small collection of influential benchmarks.
Do Datasets Have Politics? Disciplinary Values in Computer Vision Dataset Development
Specifically, we examine what dataset documentation communicates about the underlying values of vision data and the larger practices and goals of computer vision as a field.
Data and its (dis)contents: A survey of dataset development and use in machine learning research
Datasets have played a foundational role in the advancement of machine learning research.
Towards Accountability for Machine Learning Datasets: Practices from Software Engineering and Infrastructure
In this paper, we introduce a rigorous framework for dataset development transparency which supports decision-making and accountability.
Diversity and Inclusion Metrics in Subset Selection
The ethical concept of fairness has recently been applied in machine learning (ML) settings to describe a wide range of constraints and objectives.
