I conduct my research on the human and machine [learning] interaction in managerial decision making. It is a promising and rapidly developing field with a great unexplored academic and large societal impact potential in the future. The AI field has been growing fast, especially in recent years, due to its several applications, techniques, and tools. Language processing, machine vision, and machine learning have made machines more powerful, even more than humans in some contexts. There were always stories about replacing humans with machines in the near future. But there is a school of thought that humans and machines are complementary. Machines facilitate complex processing, and human knowledge and experience add contextual and relational factors that help to make the best decision. Although machines like Google AlphaGo defeated the best human in Go’s board game, the real world is not as simple as a board game for machines. The unlimited space of uncertainties demands human thinking and intuition. These arguments signal a gap for studying questions such as: should the machine oversee the human? What about an inverted side? How should their collaboration be organized? How can the human help the machine improve the performance? Some leading scholars in Information and Supply Chain Management work on these types of questions, but there is still a lack of cohesive research to answer them. In the ISCM track, such a study can be done in inventory management, supply chain planning, online commerce, and so on.