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Global trends in AI
regulation and associated
technology standards
Dr. Ansgar Koene
Global AI Ethics and Regulatory Leader, EY
4 September 2023
Development of policy debate on AI (deliberative approach)
 Fact finding and expert consultation
 AI Principles
 National AI Strategies
 Legislative gap analysis
 New or amended legislation to regulate AI
Overview of National AI-Strategies (2020)
53 Nations
Source: OECD (Organization for Economic Cooperation and Development)
https://www.aisoma.de/useful-resources-on-artificial-intelligence/
Page 2
Reactive policy development
• (Perceived) abuse of power through the use of AI
triggers reactive policy responses
• E.g. Due to protest over bias in accuracy and
deployment various US cities and states have
moved to ban the use of Face Recognition AI by
police or public sector
• IBM, Microsoft and Amazon prompted to back away
from selling facial recognition tech to law
enforcement
Page 3
Multi-national initiatives (illustrative examples)
OECD: Actively developing regulatory guidelines,
thought leadership and tracking tools through multi-
lateral dialogue to support coordinated approaches to
responsible use of AI.
OECD also acts as secretariate for other multi-national
initiatives like the Global Partnership on AI (GPAI).
G7: Under Japan’s chairmanship the G7 has
established the “Hiroshima Process” for international
discussion and harmonization of rules for the use
and development of AI.
Council of Europe: Developing a Framework
Convention on AI, Human Rights, Democracy
and the Rule of Law.
UN: UNESCO developed the Recommendation
on the Ethics of AI which was adopted by all
193 member states. This will be a contributing
part to the UN Global Digital Compact that is
being drafted for ratification 2024.
ASEAN: Is currently in the process of assessing
a set of AI Principles and Guideline for the
region.
Possible AI Governance Initiatives
Page 5
Organisation and application
Prepare the workforce and increase
awareness
Create AI Governance framework
Funding of Innovation/research
Set up AI Principles and
Governance programs
Create a Trusted AI Framework
Manage AI Risks and Implement
Appropriate Controls
Monitor and Keep Humans in-the-Loop
Promote R&D programs
Society
Proportionality and Do
No Harm
Safety and Security
Right to Privacy and
Data Protection
Multi-stakeholder and
Adaptive Governance &
Collaboration
Responsibility and
Accountability
Transparency and
Explainability
Human Oversight and
Determination
Sustainability
Awareness & Literacy Fairness and Non-
Discrimination
G20/OECD UNESCO
Inter-Governmental Principles for the Use and Development of AI
Page 6
Principles of AI Governance reflected in proposed regulation & guidance
Page 7
Transparency
Responsible disclosure
regarding AI systems and
stakeholders should be informed
if AI systems are used
Fairness
Avoidance of unfair bias,
accessibility and universal
design, and stakeholder
participation
Security and Safety
AI systems should be secure
and function appropriately, such
that they do not pose
unreasonable safety risk
Accountability
Owners, developers, providers
and users of AI systems should
be responsible for the proper
functioning of the systems
Privacy and Data Governance
Respect for privacy, quality and
integrity of data, and access to
data
Regulatory approaches to AI
United States: Emphasis on applying pre-existing laws
(e.g. Anti-Discrimination laws) and sector specific
regulations (e.g. Medical Devices), paired with voluntary
guidelines (e.g. NIST AI Risk Management framework) and
public commitments from industry.
China: Combines general guidelines with focused
regulation to address specific areas of concern. Passed new
legislation specifically requiring AI generated media content
(text, video and audio) to be labelled as synthetic, and
requiring providers to ensure that training data and content is
“true and accurate”.
EU: Focus on harmonizing regulator approaches to AI
across the 27 member states by proposing overarching
legislation to ensure that ‘high-risk’ AI applications don’t
violate the safety, security and fundamental rights of
persons (the EU AI Act).
Canada: Seeking to establish comprehensive
legislation for AI through the AI and Data Act, which
builds on existing legislation mandating Algorithmic
Impact Assessment on federal AI tools expanding the
scope to include private sector and risk mitigation
and management obligations for high-impact uses
of AI (C-27 AIDA).
UK: Proposing a framework of responsible AI
principles for existing domain-specific regulators
to apply when assessing uses of AI in the context of
their domain of competence.
Japan, South Korea, Singapore and many other
technologically developed states: Currently focused on
voluntary guidelines.
Page 8
General positioning of regulatory approaches taken by 8 key jurisdictions
Page 9
Five regulatory trends for AI
Page 10
1. Regulation and guidance is consistent with the G20/OECD AI Principles
2. Proportionality of regulatory obligations based on risk/impact of the AI
application
3. Combination of sector-specific and sector agnostic requirements to meet the
broad application domains of AI
4. AI-related policy are developed in the context of other digital policy priorities
5. Use of regulatory sandboxes and similar tools for agile learning and refining
of policy implementation
The EU Digital Strategy: 4 Pillars, and potentially global implications
Page 11
AI is a core piece of the EU’s digital strategy and regulatory tapestry
AI
Act
(draft)
GDPR
DMA
Updated
product liability
DSA
Data
Act
AI Liability
Directive
(draft)
…
…
…
Page 12
AI - EU Policy drivers
• Balancing between:
Ecosystem of Trust &
Ecosystem of Excellence
• AI Risk Assessment
• Access to Data without sacrificing Rights
• Coherent regulation across EU27.
Challenges
And..
• Correct previous Digital Economy ‘failures’
• Continue to champion Fundamental Rights (e.g.
GDPR)
• Where possible, increase regulatory convergence
with ‘partner countries’ (US and TTC process
• Develop global alliances (e.g. Canada, Japan).
To establish a legal framework for AI across Europe’s
which will set some requirements for high-risk
applications of AI: from making sure that they use high-
quality data, to ensuring human oversight.
EU’s Aim EU desired ‘Geopolitical Positioning’
China
US
EU
Focus on
‘Human-
Centred,
Trustworthy AI’
Page 13
EU: A risk-based approach to regulation
Risk assessment on the basis of risk to safety, security and fundamental rights of
natural person posed by intended use of AI
No risk or minimal risk
PERMITTED with no restrictions
Non high risk
PERMITTED but subject to
information/transparency obligations (i.e.
impersonation –bots-)
High risk
PERMITTED SUBJECT TO COMPLIANCE with
AI requirements and ex ante conformity
assessment (i.e. recruitment, medical devices)
Unacceptable risk
PROHIBITED (i.e. social scoring)
Page 14
Page 15
ASEAN Digital Masterplan – the need for an ecosystem of trust for AI
• “As ASEAN moves towards developing its digital economy, a trusted ecosystem is key - one
where businesses can benefit from digital innovations while consumers are confident to use AI.”
- ASEAN Digital Masterplan 2025
Key commonalities in current AI initiatives within ASEAN
Page 16
Strategic Initiatives
AI talent and manpower
Developing and building a pool of
skilled workers to support AI
development
Innovation and Research
Encouraging investments in AI-
related research and innovation
Governance
Implementing legal and regulatory
frameworks for the development and
application of AI systems
Infrastructure
Setting up ICT infrastructure and
systems to support data sharing and the
development of AI systems
Priority Areas
Healthcare
Many of the AI Governance guidelines identify
priority areas for the development and
deployment of AI solutions.
Some common priority areas are:
Education Smart Cities
Finance Manufacturing/Logistics Public Service
5 major areas of concern for AI system
Page 17
From the landscape study conducted, it was noted that many of the existing frameworks based on international AI ethics
principles seek to address 5 major areas of concern for AI system.
1 2
3 4 5
KNOW WHEN ONE
IS USING AI AND AI
SYSTEMS
UNDERSTAND HOW
AN AI MODEL
MAKES A DECISION
ENSURE AI
SYSTEMS ARE
RELIABLE AND
SAFE
LEAD TO FAIR
DECISION / NO
UNINTENDED BIAS
DEFINE OVERSIGHT
FOR AI SYSTEMS
Areas of Concern
Draft ASEAN AI Principles
Transparency and Explainability
Fairness and Equity
Security and Safety
Human-centric
Privacy and Data Governance
Accountability and Integrity
Robustness and Reliability
Page 18
Further considerations for policymakers
Page 19
Other factors to consider in AI policy development include:
1. Ensuring regulators have access to sufficient subject matter expertise to successfully
implement, monitor and enforce these policies.
2. Ensuring clarity, if the intent is to regulate risks arising from the technology itself or
from the way it is used or both;
3. The extent to which risk management policies and procedures, as well as the
responsibility for compliance, should apply to third-party vendors supplying AI-related
products and services.
4. The importance of multi-lateral processes to make AI rules interoperable and
comparable.
Standards and Regulation
• Standards establish technical detail, allowing legislation to
concentrate on policy objectives
• Standards can be one way to establish regulatory compliance
Page 20
P70xx “Ethics AI Standards”
IEEE P2863 - Recommended Practice for
Organizational Governance of AI
…
[national standards body]
Page 21
ISO/IEC JTC 1/SC 42 Artificial Intelligence
Page 22
IEEE 7000-2021: Model Process for Addressing Ethical Concerns During System Design
IEEE P7001: Transparency of Autonomous Systems
IEEE P7002: Data Privacy Process
IEEE P7003: Algorithmic Bias Considerations
IEEE P7004: Child and Student Data Governance
IEEE P7005: Employer Data Governance
IEEE P7006: Personal Data AI Agent Working Group
IEEE P7007: Ontological Standard for Ethically Driven Robotics and Automation Systems
IEEE P7008: Ethically Driven Nudging for Robotic, Intelligent and Autonomous Systems
IEEE P7009: Fail-Safe Design of Autonomous and Semi-Autonomous Systems
IEEE 7010-2020: Recommended Practice for Assessing the Impact of Autonomous and Intelligent
Systems on Human Well-being
IEEE P7011: Process of Identifying and Rating the Trustworthiness of News Sources
IEEE P7013: Benchmarking of Automated Facial Analysis Technology
Page 23
EY | Building a better working world
EY exists to build a better working world, helping to
helping to create long-term value for clients, people and
people and society and build trust in the capital markets.
markets.
Enabled by data and technology, diverse EY teams in over
teams in over 150 countries provide trust through
through assurance and help clients grow, transform and
transform and operate.
Working across assurance, consulting, law, strategy, tax
strategy, tax and transactions, EY teams ask better
better questions to find new answers for the complex
complex issues facing our world today.
EY refers to the global organization, and may refer to one or more, of the
member firms of Ernst & Young Global Limited, each of which is a
separate legal entity. Ernst & Young Global Limited, a UK company
limited by guarantee, does not provide services to clients. Information
about how EY collects and uses personal data and a description of the
rights individuals have under data protection legislation are available via
ey.com/privacy. EY member firms do not practice law where prohibited
by local laws. For more information about our organization, please visit
ey.com.
[Optional sector or service line descriptor — refer to The Branding Zone]
© 2021 Ernst & Young LLP.
All Rights Reserved.
XXXXX-XXXGbl
ED MMYY
[Optional environmental statement — refer to The Branding Zone]
[Required legal disclaimer — refer to The Branding Zone]
ey.com
Dr. Ansgar Koene
Global AI Ethics and Regulatory Leader
EY Global Public Policy
Ernst & Young LLP
Rue Belliard 40, Brussels 1040, Belgium
Mobile: +32 47 177 6378 | ansgar.koene1@be.ey.com
Website: https://www.ey.com/en_gl/people/ansgar-koene
EU Transparency Register:04458109373-91

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Tendencias globales en la regulación de la IA y estándares tecnológicos asociados

  • 1. Global trends in AI regulation and associated technology standards Dr. Ansgar Koene Global AI Ethics and Regulatory Leader, EY 4 September 2023
  • 2. Development of policy debate on AI (deliberative approach)  Fact finding and expert consultation  AI Principles  National AI Strategies  Legislative gap analysis  New or amended legislation to regulate AI Overview of National AI-Strategies (2020) 53 Nations Source: OECD (Organization for Economic Cooperation and Development) https://www.aisoma.de/useful-resources-on-artificial-intelligence/ Page 2
  • 3. Reactive policy development • (Perceived) abuse of power through the use of AI triggers reactive policy responses • E.g. Due to protest over bias in accuracy and deployment various US cities and states have moved to ban the use of Face Recognition AI by police or public sector • IBM, Microsoft and Amazon prompted to back away from selling facial recognition tech to law enforcement Page 3
  • 4. Multi-national initiatives (illustrative examples) OECD: Actively developing regulatory guidelines, thought leadership and tracking tools through multi- lateral dialogue to support coordinated approaches to responsible use of AI. OECD also acts as secretariate for other multi-national initiatives like the Global Partnership on AI (GPAI). G7: Under Japan’s chairmanship the G7 has established the “Hiroshima Process” for international discussion and harmonization of rules for the use and development of AI. Council of Europe: Developing a Framework Convention on AI, Human Rights, Democracy and the Rule of Law. UN: UNESCO developed the Recommendation on the Ethics of AI which was adopted by all 193 member states. This will be a contributing part to the UN Global Digital Compact that is being drafted for ratification 2024. ASEAN: Is currently in the process of assessing a set of AI Principles and Guideline for the region.
  • 5. Possible AI Governance Initiatives Page 5 Organisation and application Prepare the workforce and increase awareness Create AI Governance framework Funding of Innovation/research Set up AI Principles and Governance programs Create a Trusted AI Framework Manage AI Risks and Implement Appropriate Controls Monitor and Keep Humans in-the-Loop Promote R&D programs Society
  • 6. Proportionality and Do No Harm Safety and Security Right to Privacy and Data Protection Multi-stakeholder and Adaptive Governance & Collaboration Responsibility and Accountability Transparency and Explainability Human Oversight and Determination Sustainability Awareness & Literacy Fairness and Non- Discrimination G20/OECD UNESCO Inter-Governmental Principles for the Use and Development of AI Page 6
  • 7. Principles of AI Governance reflected in proposed regulation & guidance Page 7 Transparency Responsible disclosure regarding AI systems and stakeholders should be informed if AI systems are used Fairness Avoidance of unfair bias, accessibility and universal design, and stakeholder participation Security and Safety AI systems should be secure and function appropriately, such that they do not pose unreasonable safety risk Accountability Owners, developers, providers and users of AI systems should be responsible for the proper functioning of the systems Privacy and Data Governance Respect for privacy, quality and integrity of data, and access to data
  • 8. Regulatory approaches to AI United States: Emphasis on applying pre-existing laws (e.g. Anti-Discrimination laws) and sector specific regulations (e.g. Medical Devices), paired with voluntary guidelines (e.g. NIST AI Risk Management framework) and public commitments from industry. China: Combines general guidelines with focused regulation to address specific areas of concern. Passed new legislation specifically requiring AI generated media content (text, video and audio) to be labelled as synthetic, and requiring providers to ensure that training data and content is “true and accurate”. EU: Focus on harmonizing regulator approaches to AI across the 27 member states by proposing overarching legislation to ensure that ‘high-risk’ AI applications don’t violate the safety, security and fundamental rights of persons (the EU AI Act). Canada: Seeking to establish comprehensive legislation for AI through the AI and Data Act, which builds on existing legislation mandating Algorithmic Impact Assessment on federal AI tools expanding the scope to include private sector and risk mitigation and management obligations for high-impact uses of AI (C-27 AIDA). UK: Proposing a framework of responsible AI principles for existing domain-specific regulators to apply when assessing uses of AI in the context of their domain of competence. Japan, South Korea, Singapore and many other technologically developed states: Currently focused on voluntary guidelines. Page 8
  • 9. General positioning of regulatory approaches taken by 8 key jurisdictions Page 9
  • 10. Five regulatory trends for AI Page 10 1. Regulation and guidance is consistent with the G20/OECD AI Principles 2. Proportionality of regulatory obligations based on risk/impact of the AI application 3. Combination of sector-specific and sector agnostic requirements to meet the broad application domains of AI 4. AI-related policy are developed in the context of other digital policy priorities 5. Use of regulatory sandboxes and similar tools for agile learning and refining of policy implementation
  • 11. The EU Digital Strategy: 4 Pillars, and potentially global implications Page 11
  • 12. AI is a core piece of the EU’s digital strategy and regulatory tapestry AI Act (draft) GDPR DMA Updated product liability DSA Data Act AI Liability Directive (draft) … … … Page 12
  • 13. AI - EU Policy drivers • Balancing between: Ecosystem of Trust & Ecosystem of Excellence • AI Risk Assessment • Access to Data without sacrificing Rights • Coherent regulation across EU27. Challenges And.. • Correct previous Digital Economy ‘failures’ • Continue to champion Fundamental Rights (e.g. GDPR) • Where possible, increase regulatory convergence with ‘partner countries’ (US and TTC process • Develop global alliances (e.g. Canada, Japan). To establish a legal framework for AI across Europe’s which will set some requirements for high-risk applications of AI: from making sure that they use high- quality data, to ensuring human oversight. EU’s Aim EU desired ‘Geopolitical Positioning’ China US EU Focus on ‘Human- Centred, Trustworthy AI’ Page 13
  • 14. EU: A risk-based approach to regulation Risk assessment on the basis of risk to safety, security and fundamental rights of natural person posed by intended use of AI No risk or minimal risk PERMITTED with no restrictions Non high risk PERMITTED but subject to information/transparency obligations (i.e. impersonation –bots-) High risk PERMITTED SUBJECT TO COMPLIANCE with AI requirements and ex ante conformity assessment (i.e. recruitment, medical devices) Unacceptable risk PROHIBITED (i.e. social scoring) Page 14
  • 15. Page 15 ASEAN Digital Masterplan – the need for an ecosystem of trust for AI • “As ASEAN moves towards developing its digital economy, a trusted ecosystem is key - one where businesses can benefit from digital innovations while consumers are confident to use AI.” - ASEAN Digital Masterplan 2025
  • 16. Key commonalities in current AI initiatives within ASEAN Page 16 Strategic Initiatives AI talent and manpower Developing and building a pool of skilled workers to support AI development Innovation and Research Encouraging investments in AI- related research and innovation Governance Implementing legal and regulatory frameworks for the development and application of AI systems Infrastructure Setting up ICT infrastructure and systems to support data sharing and the development of AI systems Priority Areas Healthcare Many of the AI Governance guidelines identify priority areas for the development and deployment of AI solutions. Some common priority areas are: Education Smart Cities Finance Manufacturing/Logistics Public Service
  • 17. 5 major areas of concern for AI system Page 17 From the landscape study conducted, it was noted that many of the existing frameworks based on international AI ethics principles seek to address 5 major areas of concern for AI system. 1 2 3 4 5 KNOW WHEN ONE IS USING AI AND AI SYSTEMS UNDERSTAND HOW AN AI MODEL MAKES A DECISION ENSURE AI SYSTEMS ARE RELIABLE AND SAFE LEAD TO FAIR DECISION / NO UNINTENDED BIAS DEFINE OVERSIGHT FOR AI SYSTEMS Areas of Concern
  • 18. Draft ASEAN AI Principles Transparency and Explainability Fairness and Equity Security and Safety Human-centric Privacy and Data Governance Accountability and Integrity Robustness and Reliability Page 18
  • 19. Further considerations for policymakers Page 19 Other factors to consider in AI policy development include: 1. Ensuring regulators have access to sufficient subject matter expertise to successfully implement, monitor and enforce these policies. 2. Ensuring clarity, if the intent is to regulate risks arising from the technology itself or from the way it is used or both; 3. The extent to which risk management policies and procedures, as well as the responsibility for compliance, should apply to third-party vendors supplying AI-related products and services. 4. The importance of multi-lateral processes to make AI rules interoperable and comparable.
  • 20. Standards and Regulation • Standards establish technical detail, allowing legislation to concentrate on policy objectives • Standards can be one way to establish regulatory compliance Page 20
  • 21. P70xx “Ethics AI Standards” IEEE P2863 - Recommended Practice for Organizational Governance of AI … [national standards body] Page 21
  • 22. ISO/IEC JTC 1/SC 42 Artificial Intelligence Page 22
  • 23. IEEE 7000-2021: Model Process for Addressing Ethical Concerns During System Design IEEE P7001: Transparency of Autonomous Systems IEEE P7002: Data Privacy Process IEEE P7003: Algorithmic Bias Considerations IEEE P7004: Child and Student Data Governance IEEE P7005: Employer Data Governance IEEE P7006: Personal Data AI Agent Working Group IEEE P7007: Ontological Standard for Ethically Driven Robotics and Automation Systems IEEE P7008: Ethically Driven Nudging for Robotic, Intelligent and Autonomous Systems IEEE P7009: Fail-Safe Design of Autonomous and Semi-Autonomous Systems IEEE 7010-2020: Recommended Practice for Assessing the Impact of Autonomous and Intelligent Systems on Human Well-being IEEE P7011: Process of Identifying and Rating the Trustworthiness of News Sources IEEE P7013: Benchmarking of Automated Facial Analysis Technology Page 23
  • 24. EY | Building a better working world EY exists to build a better working world, helping to helping to create long-term value for clients, people and people and society and build trust in the capital markets. markets. Enabled by data and technology, diverse EY teams in over teams in over 150 countries provide trust through through assurance and help clients grow, transform and transform and operate. Working across assurance, consulting, law, strategy, tax strategy, tax and transactions, EY teams ask better better questions to find new answers for the complex complex issues facing our world today. EY refers to the global organization, and may refer to one or more, of the member firms of Ernst & Young Global Limited, each of which is a separate legal entity. Ernst & Young Global Limited, a UK company limited by guarantee, does not provide services to clients. Information about how EY collects and uses personal data and a description of the rights individuals have under data protection legislation are available via ey.com/privacy. EY member firms do not practice law where prohibited by local laws. For more information about our organization, please visit ey.com. [Optional sector or service line descriptor — refer to The Branding Zone] © 2021 Ernst & Young LLP. All Rights Reserved. XXXXX-XXXGbl ED MMYY [Optional environmental statement — refer to The Branding Zone] [Required legal disclaimer — refer to The Branding Zone] ey.com Dr. Ansgar Koene Global AI Ethics and Regulatory Leader EY Global Public Policy Ernst & Young LLP Rue Belliard 40, Brussels 1040, Belgium Mobile: +32 47 177 6378 | ansgar.koene1@be.ey.com Website: https://www.ey.com/en_gl/people/ansgar-koene EU Transparency Register:04458109373-91

Editor's Notes

  1. Legislation that is already in place GDPR Article 22 on right to recourse in case of automated decision making with significant impact on individuals DSA obligations on recommender systems and (automated) content moderation DMA obligations on automated systems for product recommendations Machinery Directive Medical Devices New legislation that will touch on AI (other than the AI Act) Data Act AI Liability directive Cyber Resilience Act