Regulatory Interoperability – Why could it be the future of AI Governance?

Title

Regulatory Interoperability – Why could it be the future of AI Governance?

Lecturer

José-Miguel Bello y Villarino - Senior Research Fellow – University of Sydney Law School, jose-miguel.bellovillarino@sydney.edu.au

Content and organization

This Spring 2026 International AI Doctoral Academy (AIDA) course examines regulatory interoperability as a potential pathway for the future of AI governance. It introduces interoperability concepts and their regulatory counterparts, maps the global AI regulatory landscape across major jurisdictions, and then explores how regulatory systems diverge and can interact through approaches such as harmonisation, mutual recognition, and partial adaptation, to then explore what regulatory interoperability means in practice. Through interactive activities, participants consider whether interoperability is domain-specific and how it connects to other parts of the regulatory landscape. The course concludes by translating these ideas into practical considerations for developers, model providers, deployers, professional users, regulators, affected persons, and enforcement bodies.

 

Level

Advanced Undergraduate possible / Mainly targeting Postgraduate students considering AI governance issues.

Course Duration

5 Hours

Course Type

Short Course

Participation terms

Nominal 5 EUR/USD/GBP/AUD/SGD/CAD – 50% discount for AIDA members. Nominal fee to encourage serious registrations – in case of difficulty to pay a waiver will be offered. Both AIDA and non-AIDA students are encouraged to participate in this short course. If you are an AIDA Student* already, please: Step (a): Register in the course by following by following the Course Link ??? or alternatively by sending an email to the Course Lecturer ??? (at)??? for your registration. AND Step (b): Enroll in the same course in the AIDA course link ??? using the ‘Enroll on this course’ button therein, so that this course enters your AIDA Certificate of Course Attendance. If you are not an AIDA Student do only step (a). *AIDA Students should have been registered in the AIDA system already (they are PhD students or PostDocs that belong only to the AIDA Members listed in this page: Members)

Lecture Plan

Days/time

Schedule

July – one 5h session or 2x2.5h session over two days

Language

English

Modality (online/in person):

Online (could be delivered in person/hybrid if aligning with an AIDA meeting of 22-25 Jun 2026 Messina, Italy is possible, could also be delivered at the Sydney Law School in July with hybrid participation in one single session.

Notes

Are there exams? Details on how to successfully complete the course. No exams. Completion of the course involves completing the in-class activities.

Course Link
Host Institution
University of Sydney Law School (non-curriculum / no credit – recognition of completion through AIDA)

Other short courses

10. 12. 2025 Go

Ethics & STICs

11. 03. 2025 Go

Deep Learning

13. 02. 2025 Go

Ethics and AI

13. 02. 2025 Go

Computer Vision

19. 01. 2025 Go

Ethics & STICs

10. 04. 2024 Go

Ethics & STICs

01. 03. 2024 Go

Computer Vision

24. 11. 2023 Go

Human Rights Toolbox

21. 02. 2023 Go

Computer Vision

11. 05. 2022 Go

Geometric learning

05. 04. 2022 Go

Computer Graphics

04. 04. 2022 Go

Bayesian Learning

02. 04. 2022 Go

Computer Graphics

31. 03. 2022 Go

Web of Data

28. 03. 2022 Go

Machine Learning

27. 03. 2022 Go

Machine Learning

02. 03. 2022 Go

Player Modeling

28. 02. 2022 Go

Player Modeling

21. 02. 2022 Go

Affective Computing

21. 02. 2022 Go

Machine Listening

21. 02. 2022 Go

Computer Vision

21. 02. 2022 Go

Computer Vision

21. 02. 2022 Go

Self-Driving Cars

21. 02. 2022 Go

Deep Learning

21. 02. 2022 Go

Deep Learning 2

09. 07. 2021 Go

Self-Driving Cars

09. 07. 2021 Go

Computer Vision

09. 07. 2021 Go

Deep Learning

17. 06. 2021 Go

Deep Learning School

17. 06. 2021 Go

Memory Network

02. 06. 2021 Go

Machine Listening

02. 06. 2021 Go

Affective Computing

02. 06. 2021 Go

Deep Learning 2

01. 06. 2021 Go

Computer Vision