Exploitation Process for Machine Learning Systems

In recent years, many companies have been involved in the development of machine learning systems. However, developing machine learning systems presents unique challenges compared with the traditional IT system development. In software engineering, research has been conducted on software development methodologies for machine learning systems, but most of these studies focused on the development process of individual machine learning systems, and limited research has investigated the exploitation process of continuously enhancing machine learning systems after their development and deployment. Thus, this paper focuses on the exploitation process, in which the collaboration between the machine learning systems and humans evolves gradually. Specifically, four stages of the exploitation process are proposed: visualization for machine learning, human-centered machine learning assistance, machine learning-centered human assistance, and autonomy without human involvement. Then, the characteristics and challenges of each stage are clarified. In addition, this paper examines the important aspect of trust in this context. The findings of this study are expected to provide guidelines for advancing machine learning systems incrementally in collaboration with humans from the perspective of the exploitation process rather than focusing on the development process.