A recent study revealing the underrepresentation of black and brown skin tones in dermatology educational materials has sparked concerns about potential racial disparities in diagnosis and treatment. The study, conducted using the Skin Tone Analysis for Representation in Educational Materials (STAR-ED) framework, employed machine learning to assess the bias in frequently used medical training materials.
EXTRASHADE, a sun care brand committed to promoting inclusivity and diversity, recognizes the importance of addressing disparities in medical education. The brand emphasizes the need for accurate representation of diverse skin tones in dermatology training materials to ensure fair and equitable healthcare practices.
The study found that only one in ten images in medical textbooks and training materials falls within the black-brown range on the Fitzgerald Scale used to evaluate skin tone. EXTRASHADE encourages medical educators, publishers, and clinicians to leverage insights from AI models like STAR-ED to evaluate and rectify biases in educational materials.
As advocates for positive change, EXTRASHADE aims to contribute to a more inclusive medical education system, fostering early and accurate dermatological diagnoses for individuals of all skin tones. The brand supports efforts to close the representation gap in dermatology training materials and envisions a future where diverse skin tones are adequately depicted in medical education.
