1.4 Interpretability

Publisher: Information Technology Industry Council (ITI)

We are committed to partnering with others across government, private industry, academia, and civil society to find ways to mitigate bias, inequity, and other potential harms in automated decision making systems. Our approach to finding such solutions should be tailored to the unique risks presented by the specific context in which a particular system operates. In many contexts, we believe tools to enable greater interpretability will play an important role.