Structural inequalities and chronic disease health outcomes: Impact of AI on health equity

Artificial intelligence (AI) systems play a critical role in achieving health equity through their impact on health and society via algorithms and emerging technologies. This chapter overviews ways in which AI systems may have both positive and negative impacts on healthcare, health and health equity. It provides historical context for the journey of AI as a factor of everyday life and business, highlighting the potential benefits and harms of AI within healthcare; and further documents a broad set of present-day harms that algorithmic bias has caused across different domains of social determinants of health, including health care access and quality, economic stability, education access and quality, neighborhood and built environment, and social and community context. Finally, it overviews current barriers to progress, and potential solutions for incorporating health equity into AI technology development, model training, algorithm deployment, and implementation efforts. A major risk of AI is perpetuating stereotypes through reliance on historical data and biased samples. There needs to be an intentionality to mitigate biases, engage diverse stakeholders throughout the process, and ensure results of AI are transparent and interpretable. AI can become a tool for social good, or it could become another source of structural inequities.