Intersectionality, AI, and Medical Equity: Challenges for Inclusive Education Policy
Schlagwörter:
Intersectionality, artificial intelligence, medical equity, inclusive education, healthcare disparities, bias in AI, social justice, healthcare policy, AI literacy, diversity in medical education.Abstract
The intersection of artificial intelligence (AI), medical equity, and inclusive education policy presents complex challenges and opportunities in addressing disparities within healthcare systems. AI is increasingly being utilized in healthcare to enhance diagnostic accuracy, improve patient outcomes, and optimize treatment plans. However, as these technologies become more integrated, the risks of perpetuating existing social inequities—particularly concerning race, gender, and socioeconomic status—also grow. AI systems trained on biased data can lead to unequal access to care and outcomes, deepening the disparities in medical treatment for marginalized communities. This issue is compounded by the lack of inclusivity in the development of AI algorithms and the underrepresentation of diverse populations in medical research.
