250408Data infrastructure and AI in Japan

Transcript

1. IT Promotion Agency Japan Approaches to Data Infrastructure and AI in Japan 2025-04-08 Kenji Hiramoto Digital Infrastructure Center
2.  IPA is a think tank and policy implementation organization for digital technology. IPA is a key player in the digital society Digital Architecture Center Digital Infrastructure Center Industrial Data Spaces Ouranos Ecosystem AI Safety Institute Digital Agency Ministry of Economy, Trade and Industry Cabinet Office AI safety Architecture Building Blocks Data governance Data management Software Digital Transformation
3. Japan Develop the foundation for a digital society on a global level by 2030. 3 IPA Digital Infrastructure Center Digital Infrastructure Center Digital Infrastructure Digital Transformation Software Engineering Innovation Anyone can anytime use infrastructure and resources Anyone can transform their business to the cutting edge one Anyone can realize their ideas Rule Tool Methodology Data Use Cases Courseware Security Human Resource Dev. AI Data Spaces
4. Japan • Data is the foundation of future society. Data 4
5. Japan Japan has a vision of Society 5.0 as the society of the future and has established Digital Governance Code 3.0 for companies to embody this vision. 5 Digital Governance Code 3.0 Viewpoints • Vision and Strategy • Monitoring • Culture Pillars • Definition of Vision • Strategy planning • Strategy implementation • Measure and feedback • Communication with Stakeholders Self-assessment and Certification Program for actions of digital transformation https://www.meti.go.jp/policy/it_policy/investment/dgc/dgc.html Data is an essential element of the code
6. Japan IPA will make a data maturity model until the summer of 2025. 6 Data Management/Governance/Maturity Data/AI Management Data/AI Governance Data/AI Maturity 1. Appropriate data/AI management ensures data/AI quality. 2. Appropriate data/AI governance ensures sustainable data/AI quality. 3. If quality-assured data is supplied, the use of data/AI will grow. Value
7. Japan  Raise awareness of the data-driven society to the executives • Guidebooks and seminars. Data-driven Management Playbook for Executives CDO（Chief Data Officer）Playbook Data management Playbook（Planned） Data governance Playbook Data maturity Playbook Interoperability Playbook（Planned）  We will develop training materials with the University of Tokyo and work with business associations. 7 Raising Executive Awareness https://www.ipa.go.jp/digital/data/data-spaces-academy.html
8. Japan  Rule • Expanding the types of reference models for rules, such as data usage conditions  Data models • Promotion of use • Minor adjustment  Domain data models • Education • Already standardized and deploying entity information on facilities, parson, etc. • Disaster risk management • Data items and first draft are ready and will be finalized 8 Enhance the interoperability framework Data Code Character Data （Japanese/English） Core data parts Core vocabulary Numeric data （Sensing data） Core data models Service data model［DM］ Base registry DM Date & Time Address Postal code Geo coding Phone POI code Point of contact Nursing info. Accessibilit y Person Legal entity Facility Equipment Metadata Admen. G. Land G. Legal entity G. Smart city DM (Local service) Moving object Feature Map Disaster rm, DM Support activity Status report Shelter and evacuation site Education DM Contents Student ＆ Stakeholders School Government DM Use case Evidence and Information Application Service catalogue Report and material Event Service and program Service delivery point Activity Address BR Support program BR Business location BR Legal entity BR List of school List of evacuation site List of shelter List of hospital Event BR Public Facility BR List of code Activity Afflicted people ・・・ Others Acquisition Land Building Event Combine blocks to build a data model Image data Geospatial data BR: Base registry GIF Data Models (Government Interoperability Framework) https://www.digital.go.jp/policies/data_strategy_government_interoperability_framework
9. Japan  Once the data structure and interrelationships are clear, data conversion and utilization can be done accurately. 9 Data mapping PJ for business LEI Legal Entity name Address #Emproyee ID Enterprise name Type of Enterprise HQ Address #Emproyee(full time) #Emproyee(part time) 法人番号 企業名 本店所在地 主たる事業所 常勤雇用者数 Country C Country B Country A Standard 法人番号 ID LEI id 企業名 Enterprise name Legal Entity name Legal Entity name 本店所在地 HQ address Address HQ address 主たる事業所 Business facility 常勤雇用者数 #Emproyee (full time) (#Employee) #Emproyee (full time) #Emproyee (part time) #Emproyee (part time) Cannot be exchanged because the data name and definition are different. Country A Country B Country C US NIEM EU SEMIC JP GIF JP IMI
10. Japan  Government and industry collaborated to map current data space-related initiatives.  Data mapping will also be developed 10 Building Blocks mapping project Business Common business function Data space function Data Trust function Rule
11.  Practical guidebook based on standards 11 Data Quality callenge Data dictionary Data models Tools ISO8000 Data quality ISO25024 SQueRE: Process ISO25012 SQueRE: Characteristics ISO5259 Data quality in AI ISO19157 Geographic JP GIF: Data quality guidebook And others Gov.uk: data quality guide Vic.au: data quality guide Governance UN Global Digital compact Data.EU; Data quality guide JP DA: Data governance guidebook(JP) DSA: sensor data quality guide How to use the standards? ISO38505 Governance of Data ISO8183 Data lifecycle framework
12. Japan  Development of data quality management methods essential for a data-driven society. 12 Data quality management Governance cycle view Process view (Operation) Gateway view (Characteristics) Ensure the organization has a sustainable structure. Identify actions required at each stage. Define the evaluation index. https://aisi.go.jp/effort/effort_infor mation/250331_2/
13. Process(Data Lifecycle) 13 1 2 3 4 5 6 7 8 1.Data planning 2.Data acquisition 3.Data preparation 4.Data processing 5.AI system 6.Evaluation of output 7.Deliver the result 8.Decommisioning Gate Gate Gate Gate Gate Gate Gate Gate
14. Japan 14 Image of the guidebook AISIJapan AI Safety Institute  Generate and collect the data required to achieve the objective, and if the data is not available within the organisation, acquire it from external sources. 49 Actions Data acquisition Data collection Ensure high-quality data when generating and collecting data. Find the data needed to achieve your objectives. Collect raw materials for data processing Gate External data acquisition External data Acquire High-quality external data. Validation and verifications Change management Configuration management Risk management Validation is an important process, and change management and configuration management are carried out on a continuous basis. Procedure Checkpoint Procedure and checkpoint Data acquisition 1. Finding the necessary data 2. Check the provenance information 3. Check the condition Data collection 1. Check the device (Sensor) 2. Collect/Input the data •Prevent the errors by using the ｗeb forms and APIs 3. Verify the data •Removal of out-of-range data and inappropriate data •Lack of consistency 4. Anonymise and conceal 5. Make the metadata  Are data obtained from  Are there any problem provenance informatio  Are there any restrictio of use of the data?  Are you taking steps to inappropriate data from  Do you ensure that ou entered?  In the case of sensor d  Do you check that the Do you refer DCAT for Data acquisition
15. Japan  The Smart City Reference Architecture 3.0 was published. • The SCRA has been enhanced significantly with items related to the data infrastructure. 15 Smart city project Municipalities Data models Sensor data Digital twin https://www8.cao.go.jp/cstp/society5_0/smartcity/index.html
16. Japan AI is one of the key player of data-driven society AI 16
17. Japan  AI safety is an essential requirement for an environment that encourages innovation. 17 Innovation Strategy 2024(AI part) ① AI innovation and the acceleration of innovation through AI • Strengthening R&D capabilities (including data supply) • Acceleration of the use of AI • Enhancing AI infrastructure • Human resource development and recruitment ② Realize the AI Safety • Governance and rules • AI safety • Prevention of mis/dis information • Intellectual property rights ③ International cooperation/collaboration
18.  J-AISI is an organization formed with the cooperation of 13 relevant ministries and 5 related organizations. 18 AI Safety Institute(AISI) AISI Executive director IPA Deputy executive director Council of Ministries and Agencies Consider government policies for AISI to ensure AI safety Members: Relevant ministries, agencies and institutions Secretariat: Cabinet Office (Secretariat of Science, Technology and Innovation Policy) AISI Steering Committee Deliberates on important matters related to AISI's business operations. Chair: Executive Director of AISI Members: Partnership Participating Organizations, relevant government ministries and agencies (Director level) Secretariat Strategy & planning Team: General coordination related to AISI Technology Team: Various surveys, red teaming studies Framework Team: Study of evaluation based on safety standards and guidelines Standards Team: Responding to trends in standards related to AISI Security Team: Research on AI and cybersecurity Secretary general: Director general, Digital Infrastructure Center Thematic Subcommittee Each group formed with relevant members discuss by themes Partnership Project Registering relevant projects and initiatives as the AISI. Government policy for AI safety assurance. Report on business policies, plans, results, etc. Relevant ministries, agencies and institutions Installed as needed Attendance/Participation Cabinet Office *Advisors are appointed as needed. Relevant Ministries and Agencies: • Cabinet Office (Secretariat of Science, Technology and Innovation Policy) • National Security Bureau • Cabinet Cyber Security Center • National Police Agency • Digital Agency • Ministry of Internal Affairs and Communications • Ministry of Foreign Affairs • Ministry of Education, Culture, Sports, Science and Technology • Ministry of Economy, Trade and Industry • Ministry of Defense • Ministry of Land, Infrastructure, Transport and Tourism • Ministry of Agriculture, Forestry and Fisheries • Ministry of Health, Labour and Welfare Related organizations: • IT Promotion Agency, Japan (IPA) • National Institute of Information and Communications Technology • RIKEN • National Institute of Informatics • National Institute of Advanced Industrial Science • and Technology https://aisi.go.jp/ AISI Japan AI Safety Institute
19. 19 Role and Scope of AISI  Role • AISI supports the government by conducting surveys on AI safety, examining evaluation methods, and creating standards. • As a hub for AI safety in Japan, AISI will consolidate the latest information in industry and academia, and promote collaboration among related companies and organizations. • Collaborate with AI safety-related organizations. • AISI is not an R&D organization.  Scope • Set the scope flexibly in the following AI related issues, while considering global trends. • Social Impact • governance • AI System • contents • data
20. Developer Service provider User 20 Activities and Output Guideline for Business Crosswalk between Guideline for Business(Japan) and Risk Management Framework(US) AMAIS: Activity Map on AI Safety Guide to Red Teaming Methodology on AI Safety AI Security Research Report Data Quality Management Guidebook Guide to Evaluation Perspectives on AI Safety Training materials for AI Safety Digital Skill Standard Multi Language and Multi Culture Challenge