Speaker: Prof Patrick Mikalef, Norwegian University of Science and Technology, Norway
Artificial intelligence is becoming increasingly embedded and connected to organizational processes and decision-making tasks. At the same time, the models that underpin contemporary AI applications are becoming progressively more complex and inscrutable. This phenomenon creates a contradiction, as delegating critical tasks requires trust-building and understanding how AI applications operate and decisions are made. To this end, explainable AI has been proposed as a set of methods that can be applied to turn the “black box” into a “glass box”. Nevertheless, in information systems research, understanding what explanations are, why they are important, and how they can create differential value has remained underexplored. The talk will focus on the role of explainability in organizational contexts and the different ways it can lead to value generation.