Computers and robots can be biased too and it likely stems from the majority-focused photos used to train them. Researchers at the Massachusetts Institute of Technology are helping to pinpoint why facial recognition software is not accurate across all races -- and the issue likely stems from both recycled code and a Caucasian-dominated computer engineering field. Joichi Ito, MIT's Media Lab director, said during an artificial intelligence panel held this week at the World Economic Forum Annual Meeting that the software's apparent trouble with recognizing diversity is likely because the engineers, and the faces used to train the software, are mostly white. More: Google Photos' 'racist' error highlights facial recognition's limits The issue goes back to the basics of artificial intelligence. Machine learning programs are based on teaching a computer with a set of data.