How shall a business adapt its management control systems when learning machines enter the arena? Will the control system continue to focus on humans aspects and continue to consider a learning machine to be an automation tool as any other historically programmed computer? Learning machines introduces productivity capabilities that achieve very high levels of efficiency and quality. A learning machine can sort through large amounts of data and make conclusions difficult by a human mind. However, as learning machines become even more complex systems, they introduce an uncertainty not previously considered by automation tools. The algorithms can make their own associations, and the automation engineer will no longer know exactly how a learning machine produces its outcome. What is the motive for a learning machines decision? A learning machine in this context becomes more human-like compared to the older generation of automation computers. This research concludes that most contemporary Management Control System principles are relevant when deploying machine learning, but some are not. These conclusions are based on empirical data from contemporary sources.

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Martin is a M.sc, MBA and result focused manager with broad experience in quality management, sustaining engineering from Operations, R&D and project management.