165 citations · 330 across the 8 of their papers we have counts for
4 papers · 1 filter
Yes, But Not Always. Generative AI Needs Nuanced Opt-in
Wiebke Hutiri, Morgan Scheuerman, Shruti Nagpal +2
This paper argues that a one-size-fits-all approach to specifying consent for the use of creative works in generative AI is insufficient. Real-world ownership and rights holder str…
TEDI: Trustworthy and Ethical Dataset Indicators to Analyze and Compare Dataset Documentation
Wiebke Hutiri, Mircea Cimpoi, Morgan Scheuerman +2
Dataset transparency is a key enabler of responsible AI, but insights into multimodal dataset attributes that impact trustworthy and ethical aspects of AI applications remain scarc…
Taxonomizing and Measuring Representational Harms: A Look at Image Tagging
Jared Katzman, Angelina Wang, Morgan Scheuerman +4
In this paper, we examine computational approaches for measuring the "fairness" of image tagging systems, finding that they cluster into five distinct categories, each with its own…
Bringing the People Back In: Contesting Benchmark Machine Learning Datasets
Remi Denton, Alex Hanna, Razvan Amironesei +3
In response to algorithmic unfairness embedded in sociotechnical systems, significant attention has been focused on the contents of machine learning datasets which have revealed bi…