Ethics of Artificial Intelligence through a Cultural Anthropology Lens
Episode notes
For this episode, we are joined by Kadija Ferryman, an anthropologist who studies equity and policy in health risk prediction technologies. Dr. Ferryman is Faculty at the Berman Institute of Bioethics and Assistant Professor in the Department of Health Policy and Management at the Johns Hopkins Bloomberg School of Public Health.
Dr. Ferryman traces her path into studying technology through a cultural anthropology lens, beginning with an early curiosity about how different cultures define illness and disease. She explains how the cultural anthropology focus on beliefs, values, and power structures shapes the way she examines modern health technologies. Using examples like the sequencing of the human genome, she highlights how different scientific communities drew strikingly different conclusions from the same discovery, revealing deeper tensions about race, biology, and social meaning that continue to influence biomedical research.
Building on this foundation, Dr. Ferryman explores how bias becomes embedded in everyday health technologies, from pulse oximeters to clinical risk prediction algorithms. She describes how known inaccuracies of pulse oximeter readings for darker-skinned individuals persisted for decades and became especially visible during the COVID-19 pandemic. Extending these concerns to emerging areas like generative AI, she raises important questions about how biased data can shape both clinical care and healthcare systems more broadly. At the same time, she offers a more nuanced perspective: these flawed technologies can also serve as powerful windows into the inequities of our society and as opportunities to rethink how ethics is integrated into medicine and technological development.
Ethical Guidelines for AI:
https://healthaipartnership.org/health-equity-across-the-ai-lifecycle-heaal
Select other publications by Dr. Ferryman:
Also mentioned on the show: Joy Buolamwini Coded Bias