From Public Data to Responsible A.I.

Abstract

In recent years advances in big data and algorithms have given rise to a world in which it is finally possible to include algorithmic decision making in the decision pipelines of governments and businesses. But how should governments and companies organize and communicate their data? How and when should they include A.I. in their decision making process? And how will their employees and customers react to the inclusion of A.I. in their organizations? In this presentation I will discuss recent advances in the creation of data integration, distribution, and visualization tools designed to augment the decision-making pipelines of organizations. These tools include A.I. concepts and techniques that have become relevant for our understanding of economic development, and have open the door to new techniques to collect and distribute public data. I show how these tools are paving the way for A.I. to become an integral part of an organization, and conclude by showing empirical work documenting differences on how people judge human and A.I. actions.