Implicit bias and health inequities can easily get baked into Artificial Intelligence (AI) and predictive tools. To prevent this, we need an intentional approach to development that specifically addresses these issues. In this white paper, you’ll learn three important strategies for reducing implicit bias and improving the equity and diversity of your predictive outputs, while still optimizing performance against your organizational and financial objectives.
Download the complimentary white paper to learn how to:
- Define affected populations with rich, longitudinal data coverage
- Select model outcomes that are universally accessible and applicable or unavoidable
- Apply a critical eye to algorithmic outputs