At a time when the value of data is never higher, many companies are investing in "artificial intelligence," in one or the other form, to help them transform business processes and make decisions faster and more accurate. But, despite what some purport, the fact remains that "training and learning" are still only as good as the data it uses -- and as such can be prone to all of the same cognitive biases that plague human decision-makers. These models account for most of the digital decisions AI systems make today, using information from behavioral, physiological, or any other source their creators deem relevant. Artificial intelligence has grown exponentially, but how can organizations ensure that AI doesn't make mistakes that are more costly than the technology itself? Cognitive bias is a real problem for AI developers trying to create systems that can make fair and unbiased decisions.