Exploitation Process for Machine Learning Systems

Satoshi Okuda and Naoshi Uchihira ()
Additional contact information
Satoshi Okuda: Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi, Ishikawa 923-1292, Japan
Naoshi Uchihira: Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi, Ishikawa 923-1292, Japan

International Journal of Innovation and Technology Management (IJITM), 2024, vol. 21, issue 06, 1-28

Abstract: 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.

Keywords: Human–machine collaboration; software engineering for machine learning systems; project management; technology and innovation management (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0219877024500482
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:ijitmx:v:21:y:2024:i:06:n:s0219877024500482

Ordering information: This journal article can be ordered from

DOI: 10.1142/S0219877024500482

Access Statistics for this article

International Journal of Innovation and Technology Management (IJITM) is currently edited by H K Tang

More articles in International Journal of Innovation and Technology Management (IJITM) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().