The document discusses Australia's approach to international cooperation on research related to privacy, data protection, and artificial intelligence. It outlines CSIRO's Data61 organization, which conducts research in these areas. It notes trends like increased data sharing and large language models that raise privacy concerns. It also discusses balancing innovation with regulatory requirements. The document proposes connecting different risks, closing gaps between principles and algorithms, and forming an international research alliance to coordinate standards and enable cross-border data sharing with privacy protections.

1. Australia’s National Science Agency
International
Cooperation for
Research on
Privacy and Data
Protection
Australia’s Approach
Liming Zhu
Research Director, CSIRO’s Data61
Chair, Blockchain & Distributed Ledger
Technology, Standards Australia
ISO/IEC JTC 1/SC 42/WG 3 - Artificial intelligence –
Trustworthiness

2. CSIRO’s Data61: Australia’s Largest Data & Digital
Innovation R&D Organisation
1000+
talented people
(including
affiliates/students)
Home of
Australia’s
National AI
Centre
Data61
Generated
18+ Spin-outs
130+ Patent
groups
200+
Gov &
Corporate
partners
Facilities
Mixed-Reality Lab
Robotics Inno. Centre
AI4Cyber HPC Enclave
300+
PhD students
30+
University collaborators
Responsible
Tech/AI
Privacy & RegTech
Engineering & Design of
AI Systems
Resilient &
Recovery Tech
Cybersecurity
Digital Twin
Spark (bushfire) toolkit
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3. § More sources & types from public & partners
§ Inter-governmental/cross-border data flow
§ Access and use of sensitive data from another
organisation/country
§ Data analytics over encrypted data -
”sharing/use without access”
§ Foundation models and LLMs
§ Privacy and data security concerns
Trend: Value Arises from Data Sharing & Joint Analytics
Data sharing, Large-Language Models, Foundation Models
3 |
Sensitive Data

4. Trend: Regulation/Ethic Overlay
Data Economy: Balancing Innovation & Regulation Burden
Legislations and Standards
• Global: GDPR, EU AI Act, NIST AI RMF, ISO AI Standards
• Australia
• AU Privacy Act Review
• Security of Critical Infrastructure Act (SOCI) Amendments
• Consumer Data Right (CDR): Open Banking, Energy, Telcom
International Dynamics
• Data, Software and AI Supply Chains
• Data used in AI, Trustworthy data and AI
• Responsible AI – Trust Data/AI-powered Service
- Tradeoffs between Fairness/Transparency vs. Privacy/Security
- Right to be forgotten
4 |

5. • Human, societal and environmental wellbeing
• Human-centred values
• Fairness
• Privacy protection and security
• AU Privacy Act
• Data Breach Notification
• SOCI Amendments
• Reliability and safety
• Transparency and explainability
• Contestability
• Accountability
Australian AI Ethics Principles
Privacy and Data Protection is part of it
5 |

6. • Risk silos competing for resources
• Board risk committees: financial, legal, reputation
– + HSE + privacy + security + ethics + AI + ….
• Different stakeholder interests & complex landscape of risk
assessment
• Limited connections between risks assessed separately
• Risk mgt perceived as a barrier – a separate thing dreaded doing
• Preventing research collaboration
Industry Challenge: Competing risk silos
6 |

7. • Connecting risks with concrete trade-offs/mitigations
– Privacy + Data Protection + AI Risks + other risks
• Closing the Gaps between privacy/protection principles & algorithms
– Algorithm-level approaches (like DP) are good starts
– System-level views and engineering practices are next
• Forming an international research alliance
– National-level research connections
– Coordinate on (de-facto) standards contribution
– Regulation-aware and harmonisation
– Data-sharing across borders with advanced tech
Solution Principles
7 |

8. Examples from Australia
8 |

9. • Connect multiple technical risks when possible
• Vis responsible AI risks assessment (including privacy and data security)
• Focus on mitigations that help address multiple risks first
Connecting Risks via Integrated AI/Privacy/Data Risk Assessment
9 | https://research.csiro.au/ai4m/operationalising-responsible-ai/
https://research.csiro.au/isp/research/privacy/r4/

10. Closing the Gap via Engineering Practices
10 | https://research.csiro.au/ss/science/projects/responsible-ai-pattern-catalogue/

11. International Research Alliance in Responsible AI
• National Level Research Collaboration
• Germany/Fraunhofer, France/Confiance.AI, Canada/CIRFA, US NSF/NIST..
• System-level assessment and measurement focused
• Standards Contribution
• Cross-border data sharing for security and privacy research
• With secure enclave and privacy-preserving technologies
• With domains: Agrifood export, Hydrogen supply chain, ESG…
11 |
https://www.csiro.au/en/about/challenges-
missions/trusted-agrifood-exports
https://research.csiro.au/ss/science/projects/h
ydrogen-esg-certification/

12. • Connecting risks with concrete trade-offs/mitigations
– Privacy + Data Protection + AI Risks + Other risks
– Foundation model and LLM risks?
• Closing the gaps between privacy/protection principles & algorithms
– System-level views and engineering practices?
• Forming an international research alliance
– National-level research connections
– Coordinate on (de-facto) standards contribution?
– Regulation-aware and harmonisation?
– Data-sharing across borders with advanced tech?
Ways forward – How?
12 |