SHARE Understanding how an artificial intelligence system generates its predictions is crucial for avoidance of bias, says a startup that has been developing what it calls “explainability in AI.” A person’s application for a loan, for example, being rejected or approved by AI needs to be analyzed for fairness. “You can actually create a dystopian world where some people get really great decisions from your systems and where some people are left out,” said Krishna Gade (pictured), co-founder and chief executive officer of Fiddler Labs Inc. Modeling data can be old or sourced incorrectly. That, among other things, causes problems. Gade believes that the black-box nature of an AI or machine learning engine, where one can’t simply open up the code and read it like you can traditional software, needs special tools.