The One Thing AI Needs To Succeed

Artificial intelligence, specifically machine learning (ML), enables a new world of complex decision-making using novel relationships between data. This paradigm of a system "learning" from data instead of tedious rules-based programming on an outcome, while exciting in its possibilities, opens up a series of new challenges. Distrust, unfairness, bias and ethical ramifications of automated ML decisions are now increasingly common. The recent story about the inadvertent bias in Amazon's recruiting or face recognition software are examples of unforeseen effects of these applications of AI. They occur because, by and large, the relationships absorbed are opaque, thereby dissuading model developers in fixing it.