Quality assurance for AI systems on business contracts
Chair
Mitsunori Nanno (CEO, FiNC Technologies Inc.)
Theme /Issue
Clarifies the concept of quality assurance of AI models, and develops guides to ease communications among parties of AI development contracts. Aims to reduce possible legal issues and facilitates AI development agreements which leads to promote the utilization of AI applications
#8 Work of the study group
Date
June. 17, 2021
Contents
Discussion
Topics
The work of the study group, “Handbook for Discussing AI Quality on Business Contracts”
Presenters
–
#7 Cases of AI development project
Date
May. 13, 2021
Contents
Presentation, Discussion
Topics
Precision/performance discussion in case of AI development of visual inspection system
Presenters
Mitsuhisa Ota (BrainPad Inc.)
#6 Model Contracts /Preparation of Mock Trial
Date
Mar. 16, 2021
Contents
Presentation, Discussion
Topics
Model contracts by the government promoting open Innovation / Discussion on mock trial scenario
Presenters
Kazuhiko Komamura (Nomura Research Institute)
#5 Past cases / Preparation of Mock Trial
Date
Jan. 26, 2021
Contents
Presentation, Discussion
Topics
Past examples of AI services that generated some ethical issues / Discussion on mock trial scenario
Presenters
Naohiro Furukawa (ABEJA, Inc.) Dai Goto (Harumi Partners Law Firm)
#4 Quality definition on existing guidelines
Date
Nov. 24, 2020
Contents
Presentation, Discussion
Topics
Machine Learning Quality Management Guideline (National Institute of Advanced Industrial Science and Technology)
Presenters
Yutaka Oiwa (National Institute of Advanced Industrial Science and Technology)
#3 Quality definition from legal perspective
Date
Oct. 27, 2020
Contents
Presentation, Discussion
Topics
Past cases in practice / Lawyers’ perspectives on quality assurance
Presenters
Tetsuya Kurokawa (CHOWA GIKEN Corporation) Hiromasa Komine (BayCurrent Consulting , Inc.) Naohiro Furukawa (Abeja Inc./Vice chair of the study group)
#2 Machine learning and its quality
Date
Sep. 16, 2020
Contents
Presentation, Discussion
Topics
Quality definition and assurance on Machine Learning Systems Engineering
Presenters
Hiroshi Maruyama (Preferred Networks, Inc.)
#1 Conventional systems and its quality
Date
Aug. 3, 2020
Contents
Introduction of study groups / Presentation / Discussion
Topics
Quality definition and assurance on conventional softwares/systems
Presenters
Fuyuki Ishikawa (National Institute of Informatics)
