Sarcouncil Journal of Multidisciplinary

Abstract: This article critiques the societal implications of artificial intelligence in healthcare, proposing an "equity-by-design" framework to prevent algorithmic bias. It integrates ethical considerations throughout the AI development lifecycle rather than treating them as secondary concerns. Using Northwestern Medicine Health Care's governance model as a case study, the article examines how theoretical principles can be operationalized through institutional policies prioritizing fairness. The framework encompasses four key domains: inclusive data governance, fairness-aware algorithm development, transparent deployment processes, and participatory governance structures. These approaches are particularly effective in addressing disparities in high-impact areas such as emergency department triage systems and prior authorization workflows. The article highlights the importance of regulatory reforms, organizational policies, and industry standards in creating comprehensive governance frameworks. It concludes by emphasizing future directions for advancing healthcare AI equity, including specialized fairness tools, interdisciplinary research, shared resources, and educational reform. Throughout, the framework demonstrates how AI can be designed to ensure equitable care for all patient populations.