10 citations · 12 across the 3 of their papers we have counts for
3 papers
"Trust Junk" Leads to Unjustified Support for Highly Discriminatory Predictive Models
Michael Correll, Lucy Havens, Mahsan Nourani
The persuasive power of data visualizations can go awry: for instance, in an explainable AI (XAI) context, visualizations can produce over-trust of predictive models. In this paper…
Investigating the Capabilities and Limitations of Machine Learning for Identifying Bias in English Language Data with Information and Heritage Professionals
Lucy Havens, Benjamin Bach, Melissa Terras +1
Despite numerous efforts to mitigate their biases, ML systems continue to harm already-marginalized people. While predominant ML approaches assume bias can be removed and fair mode…
Situated Data, Situated Systems: A Methodology to Engage with Power Relations in Natural Language Processing Research
Lucy Havens, Melissa Terras, Benjamin Bach +1
We propose a bias-aware methodology to engage with power relations in natural language processing (NLP) research. NLP research rarely engages with bias in social contexts, limiting…