66 citations · 130 across the 7 of their papers we have counts for
7 papers
From experimentation to engagement: on the paradox of participatory AI and power in contexts of forced displacement and humanitarian crises
Stella Suge, Sarah W. Spencer, Nyalleng Moorosi +3
Across the Global North, calls for participatory artificial intelligence (AI) to improve the responsible, safe, and ethical use of AI have increased, particularly efforts that enga…
Length of Stay prediction for Hospital Management using Domain Adaptation
Lyse Naomi Wamba Momo, Nyalleng Moorosi, Elaine O. Nsoesie +2
Inpatient length of stay (LoS) is an important managerial metric which if known in advance can be used to efficiently plan admissions, allocate resources and improve care. Using hi…
Healthsheet: Development of a Transparency Artifact for Health Datasets
Negar Rostamzadeh, Diana Mincu, Subhrajit Roy +7
Machine learning (ML) approaches have demonstrated promising results in a wide range of healthcare applications. Data plays a crucial role in developing ML-based healthcare systems…
Fair Wrapping for Black-box Predictions
Alexander Soen, Ibrahim Alabdulmohsin, Sanmi Koyejo +5
We introduce a new family of techniques to post-process ("wrap") a black-box classifier in order to reduce its bias. Our technique builds on the recent analysis of improper loss fu…
Fairness Preferences, Actual and Hypothetical: A Study of Crowdworker Incentives
Angie Peng, Jeff Naecker, Ben Hutchinson +2
How should we decide which fairness criteria or definitions to adopt in machine learning systems? To answer this question, we must study the fairness preferences of actual users of…
Characterising Bias in Compressed Models
Sara Hooker, Nyalleng Moorosi, Gregory Clark +2
The popularity and widespread use of pruning and quantization is driven by the severe resource constraints of deploying deep neural networks to environments with strict latency, me…
Diversity and Inclusion Metrics in Subset Selection
Margaret Mitchell, Dylan Baker, Nyalleng Moorosi +5
The ethical concept of fairness has recently been applied in machine learning (ML) settings to describe a wide range of constraints and objectives. When considering the relevance o…