By definition, Artificial intelligence is a set of computer systems that perform tasks that normally require human intelligence. On one hand, some leaders are enthusiastic about using AI systems in healthcare to improve healthcare operations and enhancing care delivery outcomes. On the other hand, some leaders are still skeptical of using AI in healthcare due to various concerns such as staffing, privacy & ethics, and lack of effective leadership for guiding the transformation journey. This panel discusses the challenges and opportunities of leading organizations in the era of Artificial intelligence and highlights lessons learned from the panelists’ experience.
Artificial Intelligence has a huge potential to analyze vast amounts of clinical and operational data to generate the needed clinical evidence for informing patient treatment. For example, cognitive intelligence agents and large language models can nowadays review patient charts and generate recommended comprehensive care plans for doctors and patients. However, many in the healthcare community are still questioning the readiness of AI systems for informing real-world clinical decisions. Several studies nowadays confirm that poorly designed AI systems can lead to unintended consequences that negatively affect patient treatment, well-being, and rights. In this panel, experts will highlight the best practices for building AI systems, including generalization, safety, transparency, fairness, biases, privacy, and many other factors, etc.
