Artificial intelligence (AI) tools in healthcare are not immune to bias - especially if they have been trained on data sets that do not accurately reflect the population they serve. Overcoming bias in AI and machine learning goes beyond recognizing its existence. Analyzing model performance and questioning the data will help determine what's really going on under the surface.
Actium's responsible AI approach enabled a health system to expand cardiology outreach to underserved Black and Asian populations by 23%. This required a huge amount of upfront work, questions, debates, and collaboration, but the results were worth it. Responsible AI approaches have been embedded in Actium's data science pipeline and health systems can better engage their high-risk patients, without biases.
Listen to Chris Hemphill’s discussion with healthcare leaders about how they're using data-driven approaches to better serve their patients.
