Quality assurance for AI systems on business contracts

ChairMitsunori 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

DateJune. 17, 2021
ContentsDiscussion
TopicsThe work of the study group, “Handbook for Discussing AI Quality on Business Contracts”
Presenters

#7 Cases of AI development project

DateMay. 13, 2021
ContentsPresentation, Discussion
TopicsPrecision/performance discussion in case of AI development of visual inspection system
PresentersMitsuhisa Ota (BrainPad Inc.)

#6 Model Contracts /Preparation of Mock Trial

DateMar. 16, 2021
ContentsPresentation, Discussion
TopicsModel contracts by the government promoting open Innovation / Discussion on mock trial scenario
PresentersKazuhiko Komamura (Nomura Research Institute)

#5 Past cases / Preparation of Mock Trial

DateJan. 26, 2021
ContentsPresentation, Discussion
TopicsPast examples of AI services that generated some ethical issues / Discussion on mock trial scenario
PresentersNaohiro Furukawa (ABEJA, Inc.)
Dai Goto (Harumi Partners Law Firm)

#4 Quality definition on existing guidelines

DateNov. 24, 2020
ContentsPresentation, Discussion
TopicsMachine Learning Quality Management Guideline (National Institute of Advanced Industrial Science and Technology)
PresentersYutaka Oiwa (National Institute of Advanced Industrial Science and Technology)

#3 Quality definition from legal perspective

DateOct. 27, 2020
ContentsPresentation, Discussion
TopicsPast cases in practice / Lawyers’ perspectives on quality assurance
PresentersTetsuya 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

DateSep. 16, 2020
ContentsPresentation, Discussion
TopicsQuality definition and assurance on Machine Learning Systems Engineering
PresentersHiroshi Maruyama (Preferred Networks, Inc.)

#1 Conventional systems and its quality

DateAug. 3, 2020
ContentsIntroduction of study groups / Presentation / Discussion
TopicsQuality definition and assurance on conventional softwares/systems
PresentersFuyuki Ishikawa (National Institute of Informatics)

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