AI, you have some explaining to do

When it comes to your next-door neighbors, maybe it's better that way. As we operationalize machine learning (ML) and AI systems, end-users need to know how decisions are made and why actions are taken. What I hear often from clients looking at adopting AI or users in the field that work with AI-based decision making is that they don't trust the black box paradigm of AI. If AI is "learning" and "evolving" based on acquired data, and they can't see its logic flow, they're not comfortable with it and do not want to rely on its decisions or recommendations. I recently discussed this very issue with a client that had developed an AI to assist human teams determine bid ranges based on strategic fit, expected economic return, and competitive intelligence when bidding for oil and gas exploration leases.