AI Governance for Businesses
  Artificial Intelligence (AI) governance regulates the exercise of authority
and control over the management of AI. It aims at leveraging AI through
effective use of data and minimization of AI-related cost and risk. While
topics such as AI governance and AI ethics are thoroughly discussed on a
theoretical, philosophical, societal and regulatory level, there is limited
work on AI governance targeted to companies and corporations. This work views
AI products as systems, where key functionality is delivered by machine
learning (ML) models leveraging (training) data. We derive a conceptual
framework by synthesizing literature on AI and related fields such as ML. Our
framework decomposes AI governance into governance of data, (ML) models and
(AI) systems along four dimensions. It relates to existing IT and data
governance frameworks and practices. It can be adopted by practitioners and
academics alike. For practitioners the synthesis of mainly research papers, but
also practitioner publications and publications of regulatory bodies provides a
valuable starting point to implement AI governance, while for academics the
paper highlights a number of areas of AI governance that deserve more
attention.
