資料２

OECD (経済協力開発機構)
技術予測フォーラム
報告
Dec. 13, 2016
総務省「AIネットワーク社会推進会議」「開発原則分科会」
中央大学 総合政策学部 教授
大学院 総合政策研究科 委員長
平野 晋

OECD Technology Foresight Forumon Artificial Intelligence
Nov. 17, 2016
@ OECD Conference Centre
2, rue André Pascal
75775 Paris Cedex 16, France1OECD-TFF紹介ページと雰囲気

Available at <http://www.oecd.org/sti/ieconomy/technology-foresight-forum-2016.htm>(last visited Dec. 6 2016).

• 会場は立ち見が出る程の盛況ぶり（通常は空席が目立つとのこと）。
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主要スピーチの要点• アンドリュー・ワイコフ氏(*1)の冒頭陳述– (*1) Director, Science, Technology and Innovation– 後述• 小職のスピーチ– 後述• クロサカ先生のスピーチ– クロサカ先生から• アン・カブラン女史(*2)の最終陳述– (*2) Head of Division on Digital Economy Policy– 後述

3議題＆発表者等（1/2）

Available at <http://www.oecd.org/sti/ieconomy/technology-foresight-forum-2016.htm>(last visited Dec. 11, 2016) (emphasis added).
4

議題＆発表者等（2/2）

Available at <http://www.oecd.org/sti/ieconomy/technology-foresight-forum-2016.htm>(last visited Dec. 11, 2016) (emphasis added).
5アンドリュー・ワイコフ氏

Available at http://www.oecd.org/sti/ieconomy/Final%20AI%20TFF%20bio%20book.pdf (last visited Dec. 11, 2016)6

A. ワイコフ氏の冒頭陳述• 高松におけるG7情報通信大臣会合にも言及しつつ、日本が意欲的に取り組んでいる旨を褒めるような調子で紹介。

7

小職の発表• 発表時間を９分40秒程に収めるようにとの指図ゆえに、コンサイスに主張を指摘。

写真は、セッション開始前の様子。
8

小職の発表概要• 総務省が有識者会議を開催して検討して来たこと。
– 「AIネットワーク」の概念・発展将来像を説明。

• 高松のG7情報通信大臣会合にて高市大臣がAI開発原則を発表し、賛成を得られていること。
• 引き続き「社会推進会議」と２つの「分科会」にて、内容を洗練化・構築中であること。
• 来年３月には東京で国際シンポを開き、世界に提示する意欲・予定であること。
• トロッコ派生問題に８原則（透明性）を当てはめて、８原則の重要性を指摘。
• まとめ： 日本が国際社会に貢献できるように望んでいることを強調。

9使用スライドは、以下のURLで公表中<http://www.oecd.org/sti/ieconomy/
Prof%20Hirano%20AI%20Foresight%2
0Forum%20Nov%202016.pdf> (lastvisited Dec. 11, 2016)

使用スライド（抄）は、次スライド以降参照。

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14

15

16

17

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まとめとして、以下を指摘：• OECDや国際社会に受容されるガイド
ラインの構築に、日本が貢献したいと望んでいること。
• 開発原則の重要性を、理解していただけたと望んでいること。
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質疑応答の概要• 会場の意見は、日本の開発８原則の提案に対し、概ね賛成の雰囲気が大勢であったと感じられた。
• 以下の諸原則に関する重要性を認識したような発言が目立つように感じられた。
– 「① 透明性の原則」、– 「⑦ 倫理の原則」、及び– 「③ 制御可能性の原則」。

23

アン・カブラン女史の最終陳述

24

アン・カブラン女史の最終陳述

Available at http://www.oecd.org/sti/ieconomy/Final%20AI%20TFF%20bio%20book.pdf (last visited Dec. 11, 2016)• 日本からのＡＩ開発に関する国際的なガイドラインの提案を踏まえつつ、来年９月又は１０月のＯＥＣＤ・日本
共催のシンポジウム、来年１１月のＣＤＥＰにおいて、各国と議論を行い、肯定的な反応が示されれば、2018年の勧告化に向けたプロセスに進みたい。
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ご清聴、有難う御座いました。

26

参考

Impacts and Risks Caused by AI Networking,and Future Challenges(From Studies on AI Networking in Japan)
November 17, 2016

Tatsuya KUROSAKA

Project Assistant Professor at Keio University
Graduate School of Media and GovernanceEvaluation of Social and Economic Impacts Caused by AI Networking“Conference on the Networking among AIs” evaluated social and economic impacts caused by
AI networking in the time series from 2020s to 2040s in each field of public, life, and industrial areas.
[Public area][Life area][Industrial area]

Public infrastructure, disaster prevention, smart cities, public administration.
Life support (personal assistance), creation of richness.
Common matters (corporate business, etc.), agriculture, forestry and fisheries,
manufacturing, transportation and logistics, wholesale and retail, finance and insurance,
medical and nursing care, education and research, service industry, construction.

[Sample 1] Manufacturing[Sample 2] Medical and nursing care

It is expected that smart manufacturing processes and supply chains will emerge around 2020,and production optimization and advanced multi-product variable production (customization)
will be realized in response to the dynamic balance of demand and supply.
In addition, digital marketing, high value-added after-sales service, and maintenance services
based on the analysis of operational data on users will be realized.
Furthermore, the automation of production beginning with the design phase of products is
expected in the second half of the 2020s, and efficiency and speed improvements indevelopment work will be realized.

The disease prediction of patients based on their vital data and the health management ofpeople based on their gene information will be realized, thus resulting in an extension of healthy
life expectancy.
It is expected that the automatic analysis of research papers will be realized in the 2030s, andmedical research and new drug development will be accelerated.

▲ Widespread use of cooperative robots that can work with people [MRI]▲ Realization of unmanned maintenance*2 (2020) [Future]▲ Improvements in product demand prediction and the efficiency of supply chains based on real-time data [I4.0]▲ Lead-time reduction through the use of demand data [I4.0]▲ Realization of smart industrial robots and machine tools for advanced multi-product variable production▲ Use of AI diagnosis support to improve diagnosis accuracy and reduce misdiagnosis [MRI]▲ Practical application of guidance robots for the visual impaired (2016) [White Paper]▲ Marketing of pushcart-type walking aids equipped with sensors [White Paper]▲ Practical application of technologies to detect abnormalities in motor functions that are not detected by body sensors, etc. (2017)[White Paper]▲ Dissemination of second opinion services using AI [MRI]▲ Dissemination of services to predict disease onset based on vital data [MRI]▲ Practical achievement of diagnostic imaging and automatic detection of lung cancer, etc. [MRI]▲ Practical achievement of health management using genetic information (2020) [Future]▲ Automatic pharmaceutical preparation [MRI]▲ Health management through ubiquitous biological information monitoring (2023) [White Paper]▲ Improvement of senior citizen QOL through the use of actuator technologies that can assist motor
functions (2023) [White Paper]▲Expansion of second careers and the senior economy through extension of healthy
life [MRI]▲Practical application of assistance network robots that help senior citizens get out of
the house (2028) [White Paper]▲ Use of sensors and actuators to support medicine, healthcare, healthmaintenance, and activities of people with disabilities* (2030) [Hirai, Member]▲ Dissemination of functions to improve dementia andstrengthen cognitive ability [MRI]▲ Dissemination of new drug development by pharmaceuticalcompanies using AI [MRI]▲ Reduction of medical costs through extension of healthy life
[MRI]

(mass customization)*1 (2020) [Future]▲ Realization of a significant reduction in construction time by on-demand manufacturing at mobile factories(2020) [Future]▲ Realization of high value-added after-sales service and maintenance service based on the analysis ofoperational data on users using the products. (2020) [Future]▲ AI robots will learn skilled workers’ intuition and knack [MRI]▲ Introduction of AI in the designing, prototyping, and testing of products for
improvements in product development efficiency and speed [MRI]▲ Improvements in product cost performance [MRI]▲ Emergence of autonomous robots that can respond to complex
environmental changes, such as production stage changes (2029) [White
Paper]▲ Realization of zero design lead time and zero inventory" (2030)[Competition]▲ Transition from standard products to tailor-made products (2030)[Competition]▲ Standardization of large companies’ unmanned plants [MRI]▲ Semi-automation and full automation of product designing [MRI]*1.
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1

Examples of Social and Economic Impacts (1/3)
FieldsExamples of Impacts

Public area (community)
Public infrastructure- The real-time collection and analysis of data on the supply and demand of public
infrastructure will enable an immediate response to sudden environmental changes.
- The automation of maintenance will achieve efficiency.

Disaster prevention- The real-time prediction of the influence of disasters will increase in sophistication, andevacuation guidance linking with the prediction will lessen the damage.

Smart cities- The utilization of street cameras and the realization of energy management will realize
comfortable, safe, and efficient cities.

Public administration- The utilization of the AI analysis result of open data on relevant policies and institutions
will benefit to level improvements in public administration.
- With the realization of forecasting utilizing information transmitted from each individualand enterprise, the planning of policies that are more precise will be possible.

Life area (people)
Life support(personal assistance)- By utilizing body and indoor sensors and robots, housework and chore support will
decrease the load of human.
- AI capable of exchanging a natural conversation with humans will appear around 2030.
- Personal fabrications will become widespread and product and service users’ own
customization will occur as common matters.

Creation of richness- Encounter support and experience sharing will be sophisticated as a result of thedevelopment of sensors and media, and a possibility of qualitative changes people’sconnections will be expected.
2

Examples of Social and Economic Impacts (2/3)
FieldsExamples of Impacts

Industrial area (work)
Common matters(corporate business, etc.)- The automation of simple tasks, such as back-office operations, customized for eachindividual (e.g., personal secretarial services) will achieve work efficiency.

Agriculture, forestry, andfisheries- Automatic cultivation, agricultural drones, intelligent farming, and other innovations will
improve production efficiency and a yield expansion.
- Smart manufacturing processes and supply chains will realize production optimization
and advanced multi-product variable production (mass customization), in response to
the dynamic balance of demand and supply.

Manufacturing- Based on the analysis of operational data on users, digital marketing, high value-added
after-sales service and maintenance service will be realized.
- The automation of production beginning with the design phase of products is expectedin the second half of the 2020s, and efficiency and speed improvements indevelopment work will be realized.

Transportation and logistics- The reduction of accidents, elimination of traffic congestion, the reduction ofenvironmental impacts, and resolution of regional “traffic refugees,” including elderly
people, will be achieved as a result of level improvements in autonomous driving.

Wholesale and retail- The utilization of the analysis results of data on customers of intelligent commerce,purchase recommendations, etc., will stimulate customers’ consumption.

Finance and insurance- The sophistication and divergence of products and services will be expected as a resultof the refinement of risk assessment.
- The automation of trading, loan screening, and credit management will become
widespread around 2030.

3

Examples of Social and Economic Impacts (3/3)
FieldsMedical and nursing care

Examples of Impacts- The disease prediction of patients based on their vital data and the health managementof people based on their gene information will be realized, thus resulting in an
extension of healthy life expectancy.
- Medical research and new drug development will be accelerated by the automatic
analysis of research papers.

Education and researchService industry- Detailed education, ranging from the learning of subjects to career development,
according to each individual will make progress.
- The tacit knowledge of excellent performers, skilled technicians, and creators will beformalized and archived, which will improve education efficiency.
- The automation of comparatively simple jobs in security service, backyard work, andresponse services at call centers will make progress.
- The automatic evaluation of the reasonable prices of real estate will facilitate realestate transaction.
- The introduction of robot technology to dangerous work and painful work will make iteasier to work on construction site for women and elderly people.

Construction- Sensors that will detect the deterioration of structures and new functional materials asa result of advanced data analysis will be developed, which will further enhance thesafety of buildings.

4

Risks Caused by AI Networking (1/2)
The conference classified social, economic, ethical, and legal risks caused by AI networking as follows*.
1. Risks Associated with Functions： Functions that are expected in the AI network system do NOT work
appropriately.
2. Risks related to Legal System, Rights, or Interests: AI network system infringes rights or interests.
* Some risks have both sides. (example: Risk of accident)

For studying the ideal state of evaluation and management of risks, examination of scenarios that imagine an
actual applications of AI network system will be needed. (I.e., Risk scenario analysis)
Type of Risks

ExamplesRisks Associated with Functions

Security-related risks

Risks related to information andcommunications network
systems.

- Hacking and cyber attack on AI network system.
- Surreptitious attack on AI network systems without attracting anyone’s attention.
- Occurrence of unintended situation caused by intermingled with various AI in information communication
network.
- Occurrence of unintended situation caused by irregular work of AI when information communication
network has some trouble.
- Data leak and data loss from clouds, and system failure.

Opacification risks- As AI algorithm becomes opacified, appropriate control of AI network system becomes difficult for human.

Risks of control loss

- As AI network system runaways, control by human becomes difficult or impossible.
5

Risks Caused by AI Networking (2/2)
Type of Risks

ExamplesRisks related to Legal Sys, Rights, or Interests
Risks of accidents

Risks of crimes- Accident by the action of an autonomous vehicle or robot on an autonomous decision basis.
- Crime by malware abusing AI network system.
- Terrorism or crime by autonomous weapon system.

Risks related to the rights andinterests of consumers, etc.

- Inappropriate application of AI network system infringes rights and interests of consumers and young
people, etc.

Risks related to theinfringement of privacy andpersonal information- As collection and application of personal information by AI network system becomes opacified, control of
personal information becomes difficult.

Risks related to human dignity
and the autonomy of eachindividual

Risks related to democracy andgovernance mechanisms- AI network systems infringe privacy by surmising people’s intentions, health, or future actions, etc.
- AI network systems infringe individual autonomy by invisible manipulation of human's decision making
processes.
- Collapse of the value system of the human-central principles by the technological singularity.
- AI network system’s bad influence on voting and people's behavior.
- As AI network system is applied to the governance of the nation, decision making processes become
opacified and the location of responsibility turns ambiguous.

6

Future Challenges
1. Formulation of Basic Principles for
Research and Development “AI R&D
Guidelines”
2. Facilitation of Cooperation toward theDevelopment of AI Networking
3. Securing of Competitive Ecosystem
4. Challenges for Promotion of Economic
Development and Innovation
5. Setting Evaluation Indices on Impact ofDevelopment of AI Networking andRichness- and Happiness-related Indices6. Protection of Users
7. Ensuring Security for the AI Networking
8. Institutional Issues relating to Privacy andPersonal Data
9. Institutional Issues relating to Content
10. Study of Basic Rules of Society

11. Creating and Sharing Risk Scenarios
12. Accelerated Advancement of Information
and Communications Infrastructure
13. Prevention of the Formation of AI Network
Divides
14. Issues related to Ideal State of Human
Existence
15. Fostering of AI Network System Literacy
16. Personnel Training for the AI Networking
17. Improvements in Working Environments
in Response to AI Networking
18. Establishment of a Safety Net
19. Contribution to Human Happiness throughthe Resolution of Global Issues
20. Approach to Governance of the AI
Network Systems

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Relationship between Future Challenges and four types Issues
Institutional
issuesEconomic
issuesSocial andethical issues

Technical
issues

1. Formulation of Basic Principles for Research and Development “AI R&D Guidelines”

◎

○

◎

◎

2. Facilitation of Cooperation toward the Development of AI Networking

○

◎

○

◎

3. Securing of Competitive Ecosystem

◎

◎

△

○

4. Challenges for Promotion of Economic Development and Innovation

○

◎

△

○

5. Setting Evaluation Indices on Impact of Development of AI Networking and Richnessand Happiness-related Indices

○

◎

◎

○

6. Protection of Users

◎

◎

◎

○

7. Ensuring Security for the AI Networking

○

○

△

◎

8. Institutional Issues relating to Privacy and Personal Data

◎

○

○

○

9. Institutional Issues relating to Content

◎

◎

○

○

10. Study of Basic Rules of Society

◎

○

○

○

11. Creating and Sharing Risk Scenarios

◎

△

○

◎

12. Accelerated Advancement of Information and Communications Infrastructure

○

○

△

◎

13. Prevention of the Formation of AI Network Divides

○

◎

○

○

14. Issues related to Ideal State of Human Existence

○

○

◎

○

15. Fostering of AI Network System Literacy

△

△

◎

◎

16. Personnel Training for the AI Networking

○

◎

○

◎

17. Improvements in Working Environments in Response to AI Networking

◎

◎

○

△

18. Establishment of a Safety Net

○

◎

○

△

19. Contribution to Human Happiness through the Resolution of Global Issues

◎

◎

◎

○

20. Approach to Governance of the AI Network Systems

◎

○

◎

○

* A strong relationship, moderate relationship, and weak relationship between each issue and region are shown by ◎, ○, and △, respectively. 8

Detail of Future Challenges (Extract)
11. Creating and Sharing Risk Scenarios•Creating scenarios of various risks assuming the scenes of the utilization andapplication of AI network systems.
•Promotion of countermeasures based on scenarios against risks.
➢ Risk assessment (Time of occurrence, occurrence probability, scale of damage etc.)➢ Risk management (risk prevention, operation stoppages and disconnection fromnetworks in response to incidents, implementation of improvements, etc.)➢ Risk communication (e.g., scenarios shared by each stakeholder in society).
•Ongoing reviews of scenarios in accordance with the development of AI networking.
•Study on the ideal state of the government’s initiatives with consideration of scenario.

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Detail of Future Challenges (Extract)
20. Approach to Governance of the AI Network System• Study on the role sharing of hard laws (e.g., administrative regulations and criminal
regulations) and soft laws (e.g., agreements between stakeholders and forum standards)
for the governance of AI network systems.
• Study on the ideal state of consensus building among stakeholders on AI network
systems.
 Study on the ideal state of the process design of consensus building among
stakeholders.
 Study on the ideal state of communication between experts and non-experts.
• Study on the ideal state of opportunities to participate in the process of internationalrulemaking on AI network systems and maintenance of the transparency of theprocess.
• Formation of opportunities for international discussions about issues concerning thegovernance of the AI network systems such as formulation of “AI R&D Guidelines”.
 Formation of opportunities for domestic discussions in preparation forinternational discussions.
 Promotion of research and study on the ideal state of the governance of AI
network systems.
10My opinion• Remember the history of the internet
 We can learn the deployment of new technology to our society.
e.g. Connectivity -> Web -> Broadband -> Mobile -> IoT
 As a result, we concern today on information security and privacy.
• Understand the difference Is AI a next step from latest migration like IoT?
 AI will become the networked system to collaborate each other.
 “Unpredictable technology” is a key to find the difference.
• Find the reasonable transparency
 Who can care about transparency?
 Reasonable transparency should be a movement and/or
framework that Users and Experts work together to clarify
the ordinary and extra-ordinary condition.

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Conclusion• First of all, “AI Network System for Humankind”
 AI Network System must be ruled by humankind as user themselves.
 “User” includes not only “individual” but “company” and/or “community.” Users expect the availability of valid, affordable, controllable,
safe and secured AI Network System.

• Never stop innovation to “AI Network System”
 AI Network System can help us to create the “user-centric” society(if we want it.) Japan prospects the potential of AI Network System due to facing
the social problems.

• Think about ecosystem What kind of ecosystem? Who takes the top?
 The ecosystem should be developed with responsibility to “user.”

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Japan would like to talk on“AI Network System” with you!

Thank you for your attention.