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
Outputs Handbook on AI Quality and Development Agreements(July 21, 2021) (written in Japanese)
Past sessions #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)
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