Overcoming data imbalance and bias mitigation in the AI era
25 Jun 2025
Data Quality
- Are we building models that truly work for everyone, or just for the majority? What are the hidden risks of ignoring rare diseases or underrepresented populations?
- What tools and strategies help mitigate bias without sacrificing performance? How can we trust AI decisions when they’re trained on biased or imbalanced data?
- Whose data is powering our AI models—and who’s being left out?
