Yingfei Wang (pictured), an assistant professor of Information Systems at the University of Washington’s Foster School of Business, envisions a healthcare system that combines human intuition and algorithmic precision. Her research currently focuses on developing reinforcement learning (RL) models to crunch patient’s data and generate personalized care plans. RL models differ from other algorithms by learning from how patients respond to past treatment and incorporating these insights into future care plans. Wang envisions these models working especially effectively for chronic disease treatment, as the AI can help clinicians quickly alter treatment plans based on any changes to a patient’s health.
Throughout her work, Wang maintains a high level of vigilance when it comes to ethics and accountability. She emphasizes to her Masters of Science in Information Systems students the risk biased data sets pose to the application of artificial intelligence, especially in healthcare. She explains that diverse, inclusive data sets are far more effective and successful than biased ones. Wang also emphasizes the importance of transparency in AI, as physicians must understand how the data sets operate in order to form a mutually beneficial partnership with the algorithms.