Steps to Evaluate Fairness in Machine Learning Models
May 15, 2024 · 2 min read · Businesses prioritize metrics that impact their bottom line, while data scientists often focus on accuracy. However, bias in a model can lead to allocative harms (unequal distribution of benefits) and representation harms (downplaying certain groups)...
Join discussion












