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Management Journal Article
Building an Artificial Intelligence Explanation Capability
Companies must establish an Artificial Intelligence Explanation (AIX) capability for their AI initiatives to thrive.
Abstract
Though companies are building artificial intelligence (AI) systems and integrating them into business operations, executives are concerned about AI’s distinctive challenges (e.g., opacity) and seeking to develop new capabilities in response. We describe a new AIX explanation capability that companies must establish before their AI initiatives can thrive. This capability has four dimensions: decision tracing, bias remediation, boundary setting and value formulation. Together, these dimensions help organizations to address the challenges of model opacity, model drift, acting mindlessly and the unproven nature of AI.
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About the Authors
Ida A. Someh, Senior Lecturer in Business Information Systems, University of Queensland and Academic Research Fellow, MIT CISR
Barbara H. Wixom, Principal Research Scientist, MIT Center for Information Systems Research (CISR)
Cynthia M. Beath, Professor Emerita, University of Texas and Research Collaborator, MIT CISR
Angela Zutavern, Managing Director, AlixPartners
MIT CENTER FOR INFORMATION SYSTEMS RESEARCH (CISR)
Founded in 1974 and grounded in MIT's tradition of combining academic knowledge and practical purpose, MIT CISR helps executives meet the challenge of leading increasingly digital and data-driven organizations. We work directly with digital leaders, executives, and boards to develop our insights. Our consortium forms a global community that comprises more than seventy-five organizations.
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