Closer or even farther from fairness: An assessment of whether fairness toolkits constrain practitioners with regards to algorithmic harms

To encourage ethical thinking in Machine Learning (ML) development, fairness researchers have created tools to assess and mitigate unfair outcomes. However, despite their efforts, algorithmic harms go beyond what the toolkits currently allow to measure. Through 30 semi-structured interviews, we investigated whether data scientists are...