Basic information of the Research Area

[Trusted quality AI systems]Core technologies for trusted quality AI systems

Research Supervisor

Akiko AizawaProfessor, Digital Content and Media Sciences Research Division, National Institute of Informatics

Strategic Objective

Trusted AI

Overview

Artificial Intelligence (AI) technologies are being applied to a rapidly expanding range of applications in the world at large, and have become indispensable for the creation of new value in scientific, social and economic spheres. However as a consequence of their “black box” nature, facing built-in biases and other such limitations, “deep learning” and other machine learning technologies present a variety of reliability/safety related issues that must be addressed before widespread application.
Therefore our Research Area involves creating fundamental technologies, and constructing AI systems that incorporate these fundamental technologies, leading to the realization of trusted quality AI that humans can use widely and safely in society. In our research we also address such issues as the definition and assessment of the reliability/safety of Human-centric AI systems, the determination of requirements for such systems, and the establishment of technologies to meet those requirements.
More specifically, we direct our efforts toward the following research and development areas:
(1) Revolutionary/evolutionary AI technologies toward the realization of trusted AI.
(2) Technologies to ensure the reliability and safety of AI systems expected from a Human-centric society.
(3) Technologies to ensure data reliability and support human decision making within a Human-centric AI society.
Through these efforts we aim to open avenues to the resolution of various social issues, promote the creation of new science and value, foster a community for research into trusted AI and related fields, and heighten the presence of Japanese research within such fields.
This research area is managed as part of the AI, big data, IoT, and the cyber security integration project developed by the Ministry of Education, Culture, Sports, Science and Technology (AIP Project).

Research Area Advisors

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Schedule of Selection Process

Deadline for application
Document-based review 2021/06/19
JST will contact to the interviewees no later than 2021/06/26
Interview-based review(※)
※Interview date and time will be assigned by JST.
2021/07/10・2021/07/14

Research Supervisor's Policy

Research Supervisor's Policy of this Research Area can be downloaded from below.