Responsible AI for Health Symposium Panel: Metrics for Responsible AI
At the Inaugural Responsible AI for Health Symposium, this panel centered on the discussion of metrics that can be used to measure the fairness, risk, and trustworthiness of AI models. Panelists noted the unanswered questions regarding the governing body that will ultimately be responsible for selecting, deploying, and integrating fairness metrics. Dr. Anjana Susarla elaborated on the risks of AI, stating that they are primarily derived from “us ignoring this interplay between the way we develop all these AI systems and [their] use.”
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In the U.S., almost three-quarters of patients utilize five-star scale web ratings of physicians to guide them. But how much should you trust these online ratings?
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CGM-LSM improves near-future glucose prediction with high accuracy and robustness, advancing diabetes management through large-scale sensor data analysis.
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This panel at the Inaugural Responsible AI for Health Symposium focused on the integration of AI into clinical settings and electronic health record systems. The experts discussed key considerations for using AI tools in medical decision-making and highlighted the challenges involved in building the infrastructure needed for successful implementation.