“Breaking Barriers: Addressing Algorithmic Bias for Equitable Cancer Care Access” is an initiative aimed at tackling a critical issue in healthcare: the unfairness in AI-driven cancer care. AI models, which are increasingly used in diagnosing and treating diseases, often lack data from diverse groups of people. This means that not everyone’s health needs are considered equally, especially when it comes to cancer treatment. Factors like ethnicity, gender, economic status, race, age, and religion are not always adequately represented in AI training, leading to disparities in healthcare access.
To address this, a one-day event is being proposed to delve into how biases in AI affect health systems and to find ways to make AI in healthcare more equitable. This event is spearheaded by a leading Professor of Machine Learning, who has extensive knowledge in this area and is poised to gather a wide range of experts, policymakers, and industry leaders to share insights and strategies.
Participants will present their research and solutions for creating AI algorithms that fairly represent all populations, taking into account various social, legal, and technological aspects. The goal is to ensure that AI aids in providing equal access to cancer treatments, including vaccines and clinical trials, for everyone.
The insights and outcomes from this event will be widely shared, aiming to influence future reforms in healthcare AI. This includes publishing a detailed research proposal in a prestigious journal and disseminating highlights through national newspapers and various communication platforms. By bringing together a community of experts to focus on reducing bias in AI, this initiative seeks to pave the way for more equitable healthcare access for all, particularly in the fight against cancer.