As the interest in utilizing AI/machine learning in healthcare continues to grow, healthcare systems are adopting algorithms to enhance patient care, alleviate clinician burnout, and improve operational efficiency. However, while these applications may appear promising, they also carry certain risks, including the potential to automate and reinforce existing health disparities.

During this seminar, we will introduce the ABCDS Oversight framework developed at Duke Health. This comprehensive framework focuses on the governance, evaluation, and monitoring of clinical algorithms, providing participants with practical guidance to ensure the responsible implementation of AI/ML. Specifically, we will highlight how high-level principles can be translated into actionable steps for developers, allowing them to maximize patient benefit while minimizing potential risks.

Additionally, we will provide participants with our Bias Analysis and Mitigation template, a valuable tool for identifying and addressing potential sources of bias in AI/ML algorithms. This template facilitates the anticipation of associated harms and guides the implementation of strategies to mitigate or prevent biases. By utilizing this tool, developers can proactively address bias concerns and work towards equitable healthcare outcomes.

We will also address the challenges posed by large language models (LLMs) powered by generative AI, such as ChatGPT. While LLMs have the ability to generate text, their outputs must be carefully monitored and controlled to avoid unintended biases or misinformation. We will explore considerations and strategies necessary for effectively evaluating and governing LLMs within the healthcare context.

Lastly, we will discuss the competencies needed for educators working to prepare the next generation of health professionals. Universities can play a crucial role in supporting healthcare professionals to build critical competencies in AI/ML by strengthening curricula and providing opportunities for continuing professional development.

Whether you are a developer, a healthcare professional, or simply an enthusiast in the field of AI/ML, this seminar will offer valuable insights and practical tools for promoting responsible and equitable implementation of AI/ML in healthcare settings. Join us to learn how you can contribute to shaping the future of healthcare delivery through AI/ML innovation, educating next-generation health professionals, and ensuring the best possible outcomes for patients at Duke and beyond.