most citedExplanatory Debiasing: Involving Domain Experts in the Data Generation Process to Mitigate Representation Bias in AI Systems

6 citations · 6 across the 1 of their papers we have counts for

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cs.HC2026

Spotting (and Missing) Algorithmic Bias: Investigating User Understanding in a Fairness Assessment Tool

Anna Verheyden, Yizhe Zhang, Robin De Croon +2

Fairness metric selection is typically left to data scientists, but which biases are problematic and which metric captures them best depends on stakeholders' experience and domain…

cs.HC2025★ 6 cited

Explanatory Debiasing: Involving Domain Experts in the Data Generation Process to Mitigate Representation Bias in AI Systems

Aditya Bhattacharya, Simone Stumpf, Robin De Croon +1

Representation bias is one of the most common types of biases in artificial intelligence (AI) systems, causing AI models to perform poorly on underrepresented data segments. Althou…