116 Kellogg Insight Based on insights from Florian Zettelmeyer and Inhi Cho Suh How to Build AI that Everyone Can Trust An expert from IBM Watson discusses how to remove bias and increase transparency in machine-learning algorithms. ARTIFICIAL INTELLIGENCE IS HERE TO STAY. Machines are getting smarter, faster, and are poised to play ever-greater roles in our health - care, our education, our decision-making, our businesses, our news, and our governments. Humans stand to gain from AI in a number of ways. But AI also has the potential to replicate or exacerbate long-standing biases. As machine learning has matured beyond simpler task-based algorithms, it has come to rely more heavily on deep-learning architectures that pick up on relationships that no human could see or predict. These algorithms