A Game to Assess Human Decision Making with AI Support

When using decision-support systems that are based on artificial intelligence (AI), humans often make poor choices. The failure of these systems to reward expectations about their utility have led to several such systems being abandoned. Although preliminary research indicates that the inability to communicate model output understandably to the humans who use the systems may contribute to this problem, it is currently unknown what specific changes in the way that AI systems communicate with users would be most likely to increase their success. In this blog post, I describe SEI research that is collecting data on actual human decision making to determine the most effective designs for AI-system interfaces within a chosen domain.