1.
子供のプライバシー対策に必要なもの
Protecting Privacy of Children
Privacy by Design Conference 2023
- Dixon Siu, MyData Global Board Member 2020 & 2021
- Keiko Tanaka, Assistant Professor at KCG.edu
- Velislava Tchakarova-Hillman, Founder of EDDS, Visiting Researcher at London School of Economics
- Kohei Kurihara, Chief Executive Officer at Privacy by Design Lab
CC-BY-SA 4.0

2.
Dixon Siu
Fujitsu Limited
● Software Engineer
● SDG 9 Community Enabler
● Global Responsible Business Incubator
● Personium Chief Evangelist
MyData Global
● Board Member (2021 & 2022)
● Board Member at Greater Bay Area (Hong Kong) Hub
● MyData4Children Co-Founder / Co-Leader
Board member or personal data empowerment incubator for the
following organizations:
● Open Development Cambodia
● Afroleadership
● aNewGovernance

3.
UNICEF’s Manifesto for Better Governance of Children’s Data
In year 2021, UNICEF released the manifesto for better
governance of Children’s Data.
MyData4Children was grateful to provide comments to
the final draft.
Ten (10) important points are summarized here.
Three (3) of them can be done right away by the
Government and ICT companies.

4.
Age-appropriate Design
出典：Final Draftof Cambodian Child Online Protection Guidlines for The Digital Technology Industry

5.
Child ‘Well-Being’ (in the Digital Age)
● Children’s right to
culture, leisure and
play
● Protect children from
harmful and illegal
online content,
conduct, contact and
consumer risks
出典：ASEAN ICT Forum on Child Online Safety (Disrupting Harm)

6.
Prioritize children’s best interests in all decisions about children’s data
Governments and companies should give priority to children’s rights in
their data collection, and processing and storage practices
MyData Operators - MyData.org

7.
COLLABORATE with children and their communities
in policy building and management of their data
● when you take photo of the children
you don't have their consent to
post it online (some parents said that
the child actually felt upset)
● children are digital natives, the
parents have to catch up with the
technologies to protect them
● individuals do not trust the
government and companies. Data
literacy involving all stakeholders!
MyData4Children Workshop | Cambodia ICT Camp
Digital Security for Children is Key | Kiripost

8.
PROVIDE adequate resources to implement
child-inclusive data governance frameworks
Please perform Child Rights Impact Assessment!
Data protection authorities and technology companies must employ staff who
understand children’s rights, and governments should allocate funding for
regulatory oversight.
出典：MO-CRIA: Child Rights Impact Self-Assessment Tool for Mobile Operators.pdf (unicef.org)

9.
Contextualizing the need for data goveranace in education
from English literature review
教育データ、プライバシーに関して英語圏の資料レビュ
ーに基づくガバナンスへの論点の紹介
京都情報大学院大学 田中恵子

10.
教育データ利活用のロードマップ （2022/3）
Digital Agency. (2022). Roadmap on the utilization of data in education. https://www.digital.go.jp/assets/contents/node/basic_page/field_ref_resources/0f321c23-517f-439e-9076-
5804f0a24b59/20220307_en_education_outline_01.pdf

11.
子どものプライバシー対策に必要なのは？
スパムは届いてないから、
きっと安全に使えてると思うけど…
正直、学校がプライバシー保護
しているか、判断しようが無い
● データのプライバシーを最優先する
● 不必要な追跡と監視を最小限に抑える
● 生徒のデータを使って何が行われているのかについてもっと
オープンにする
● 生徒が自分のプロフィールをある程度制御できるようにする
● 学生の学習を支援するためにデータをさらに活用する
学校に求められているのは…
Source: “Data in Schools – What Students Say” – research
findings poster. (2022, October 17). Enhancing the Use of
Digital Data in Secondary Schools; enhancing the use of
digital data in secondary schools. https://data-smart-
schools.net/2022/10/18/data-in-schools-what-
students-say-research-findings-poster/

12.
● 新たな評価 New forms of Assessment : ペーパーテストの出来栄えでは測れない
、より広く深い認知範囲と複雑で高次の思考を測るアセスメントにより、学習プ
ロセスに貢献する
● 新たな学修成果証明 New forms of Credentialing: 課外活動やMOOCなど多様な
、学びの成果を、他者に示すことでモビリティを高めるデジタルな成果証明
教育テクノロジー（Edtech)とデータの可能性
ココに関心！

13.
教育テクノロジー（Edtech)とデータに関する主要な批評
● ポストデジタル: 前例のないレベルの日常のデジタル化とコンピュータ化の存在が特徴
● 教育のデジタルトランスフォーメーション:前例のない量のデータ化 (Selwyn et al.)
× 教育テクノロジーは単なるデジタルツール
◎ 教育セクターのダイナミクスを再構築する可能性を秘める
前代未聞であることが常態化する "normalized unprecedentedness" (Atwater, 2021)
十分な知識に基づいた選択を行うために必要な経験/専門知識/情報の欠如
「技術的夢遊病」のリスク：人間の存在条件を再構築する過程を進んで眠ったまま歩くこと
デジタル教育プラットフォームの急速な拡大と普及にもかかわらず、そのようなプラットフォームに対
して批判的な立場をとる教育研究は驚くほど稀である (Decuypere et al., 2021, p.1)。
「サイバー委譲 」”Cyberdelegation” が起きている (Williamson et al., 2022)
政府および公共機関が、技術的専門知識不足のため、ガバナンスを目的としたデータの収集または分析のタスクを
民間のテクノロジー組織に外部委託するプロセス。例： 福祉の割り当て、医療サービス、犯罪の検出と予測、国家安全保障、防衛、教育
民営化の特徴と共通点:
①公的資金、民間経営、②監督の欠如、③学力テスト＝教育成功の指標、④エビデンスがない、⑤利害関係者の偏り

14.
Privacy by design:
Governance and
oversight of a
growing EdTech
industry
Dr Velislava Hillman
Founder, EDDS Education Data | Digital
Safeguards
Visiting Fellow, London School of Economics &
Political Science

15.
MONITOR EDTECH
SECTOR
AUDIT TO VALIDATE STANDARDS UPDATES
STAKEHOLDER
ENGAGEMENT

16.
Setting a course for ethical innovation
and better EdTech
benchmark
against
framework
trust but verify
continuously
evaluate
ethical race to
the top

17.
CONNECT
VELISLAVA HILLMAN
Twitter
@velislava777
Web
edds-education.org
Email
veli@edds-education.org

18.
車には、スクールゾーンのような規制がある

19.
Examples of Data Harm データ「害」に至ったケース
1. Algorithmic manipulation: algorithmic systems that manipulate the content or level of difficulty in a biased/unjust way. A good example
is with the adaptive Learning Market Acceleration Program (ALMAP), described in this paper: https://peer.asee.org/adaptive-learning-the-
premise-promise-and-pitfalls.pdf
2. Data abuse: edtechs that were recommended to schools by governments during the Covid pandemic, were sharing or selling data to third
parties: https://www.hrw.org/report/2022/05/25/how-dare-they-peep-my-private-life/childrens-rights-violations-governments
3. Normalising surveillance - apps tracking children's toilet breaks https://www.washingtonpost.com/technology/2019/10/29/school-apps-
track-students-classroom-bathroom-parents-are-struggling-keep-up/
4. Algorithmic discrimination: schools are beginning to use algorithmic decision-making systems for assigning students to schools,
preventing dropout, and keeping students safe. However, there has been discrimination against certain marginalised groups (according to
race and socio-economic status) https://cdt.org/wp-content/uploads/2019/08/2019-08-08-Digital-Decision-making-Brief-FINAL.pdf
5. Risks emanating from data breaches and cyber insecurities: Lots of sensitive and personal data of children as well as former students
can be leaked and sold to black markets etc.etc. https://www.edsurge.com/news/2022-08-29-after-recent-high-profile-data-breaches-
illuminate-education-quietly-gets-acquired
教育におけるテクノロジ・データ利活用が、意図せず害をもたらした例の報告があり、
いわゆるデータ害（data harm)としてどのようなプライバシーリスクがあるか事例を認識し、
対策をとってイノベーティブな活用が求められる

20.
Current Scope of Education Data (for audience in Japan)
Digital Agency. (2022). Roadmap on the utilization of data in education. https://www.digital.go.jp/assets/contents/node/basic_page/field_ref_resources/0f321c23-517f-439e-9076-
5804f0a24b59/20220307_en_education_outline_01.pdf
In Japan, the Digital Agency, released a document dubbed "Roadmap on the Utilization of Data in Education" on January 20, 2022.
The document presents the architecture of education data (Figs. 1 and 2). However, the document soon came under criticism, mostly due to the lack of
a common understanding among the public of the definition of education data, how it would be used, and who would have access to it. When the
document stipulated that the government set out to standardize education data, many mistakenly feared the near-future establishment of an
Orwellian, single point of control over education databases maintained by the government, when in reality, the roadmap was only intended to
standardize data models. Some other concerns may be legit because, in terms of consent and control, Japan does not have the regulatory equivalent of
the U.S.‘s Family Educational Rights and Privacy Act (FERPA) but rather Personal Information Protection Act stipulates that the prior consent of the data
subject to a transfer of its personal data (including sensitive information) is not required if the transfer is necessary for promoting the sound
upbringing of children.

21.
Education technologies and Data
● Post-digital : marked by an unprecedented level of everyday digital and computerization
presence
● Digital transformation of education: unprecedented amount of datafication (Selwyn et
al.)
Education technologies are not just digital tools, but has the potential to reshape the dynamics of educational sector
"normalized unprecedentedness" (Atwater, 2021)
the lack of experience / expertise /information required for making an educated choice
Risk of “technological somnambulism"
willingly sleepwalk through the process of reconstituting the conditions of human existence
despite the rapid expansion and prevalence of digital education platforms, educational research that takes a
critical stance toward such platforms remains surprisingly rare (Decuypere et al., 2021, p.1)

22.
● New forms of Assessment : insead of high-stakes summative assessment, measure
a broader and deeper cognitive range and complex, higher-order thinking through
embedded assessments that contribute in an incremental way to the learning
process
● New forms of Credentialing: recognize students with partial degrees, validate extra-
curricular learning
Potentials of Education technologies and Data
My primary interest!

23.
1. public funding, private management
2. lack of oversight
3. standardized assessment as a measure of educational success
4. lack of evidence
5. impartial stakeholders
“Cyberdelegation” similarity with privatization of education
Cyberdelegation is the process where government and public-sector institutions outsource the tasks of gathering or analyzing
data for purposes of governance to private technology organizations, due to a lack of technical expertise on the part of the
public sector, as seen in cases such as social welfare allocation, healthcare services, crime detection and prediction, national
security, intelligence and defense, and education (Williamson et al., 2022)
Shares the same 5 characteristics of privatization of education in cyberdelegation
The previous version of significant education reform in the 90s US, relied on data from a standardized test and introduced a free market mechanism of
privatization without scientific ground that contests the narrative that privatization improves education, ultimately enlarging disparities in race and
class (Barkan, 2018). The process of privatization had little oversight and went without adequate vetting or ongoing oversight.