Fairness in
Dermatological AI
The EquiDerm Project advances equitable and ethical AI for skin health and has been recognized at the United Nations’ AI for Good Global Summit. The project contributes to SDG 3 (Good Health and Well-Being) and SDG 10 (Reduced Inequalities).
Equity by Design
Advancing fairness in dermatological AI by addressing systemic underrepresentation and mitigating bias across diverse skin tones.
Responsible AI
Establishing rigorous, ethics-driven evaluation practices to support transparent, accountable, and clinically responsible medical AI.
Research Impact
Contributing recognized research to global AI governance and health equity discussions through United Nations–affiliated platforms.
Inside the Project
Many dermatological AI systems are trained on limited and unbalanced datasets, leading to reduced diagnostic accuracy and reliability for underrepresented skin tones. This creates disparities in clinical outcomes and limits trust in AI-assisted skin health tools.
The EquiDerm Project applies inclusive dataset design, fairness-aware evaluation metrics, and interdisciplinary collaboration across AI, dermatology, and ethics. The methodology emphasizes transparency, reproducibility, and global relevance.
The EquiDerm Project addresses racial bias in dermatology by identifying limitations in existing AI tools and datasets affecting underrepresented skin tones, and advancing equity-aware evaluation practices. The work was recognized at the United Nations’ AI for Good Global Summit, conducted by the International Telecommunication Union (ITU).
Conference Paper
Published in the AI for Good Innovate for Impact 2025 Report, highlighting the project’s contribution to equitable and responsible dermatological AI.
AI for Good Innovate for Impact 2025 Report
Building Ethical AI for Every Skin Tone
The EquiDerm Project contributes to global conversations on inclusive, transparent, and trustworthy AI.