Course Title: Legal Considerations of Artificial Intelligence, Big Data and Blockchain

Part A: Course Overview

Course Title: Legal Considerations of Artificial Intelligence, Big Data and Blockchain

Credit Points: 12.00


Course Code




Learning Mode

Teaching Period(s)


City Campus


660H Graduate School of Business and Law


Sem 1 2023

Course Coordinator: Cathryn Nolan

Course Coordinator Phone: +61411 073 838

Course Coordinator Email:

Course Coordinator Location: Off Campus

Course Coordinator Availability: By appointment via email, MS Teams or phone

Pre-requisite Courses and Assumed Knowledge and Capabilities


Course Description

This course provides you with the opportunity to engage with and analyse current legal issues in frontier digital business environments and apply these learnings in contemporary organisational contexts. This course embeds a case-study pedagogy to explore AI, Big Data and Blockchain technology (including cryptocurrencies and other crypto assets), and the applications of these technologies. The case studies will prompt you to identify, analyse and critique legal and ethical considerations for blockchain-enabled businesses including in the areas of cyber security, intellectual property, privacy, corporate and organisational structures, and dispute resolution. The course content draws on Australian and international comparative materials where appropriate.

Objectives/Learning Outcomes/Capability Development


On successful completion of this course you should be able to:

CL01 Identify and analyse the legal considerations relating to the use of AI and Big Data for digital business.

CL02 Identify and analyse the legal considerations relating to the use of Blockchain technology for digital business.

CL03 Conduct research into emerging legal, regulatory, and ethical issues that arise in digital business environments.

CL04 Analyse issues and apply judgement to create solutions for a specific organisational context.

CL05 Communicate effectively with clients and stakeholders.

Overview of Learning Activities

This course is delivered as a blend of face-to-face activities (such as: workshops, seminars, lectures, tutorials, and group tasks) and online learning. Learning will be focused around a series of case studies. Learning activities may also include: project development activities; guest speakers/expert commentators; prescribed readings; researching and analysing specific information; solving problems; producing artefacts; proposing solutions; seeking and providing peer feedback; and reflective praxis.

Overview of Learning Resources

Various learning resources are available online through MyRMIT Studies/Canvas. Class activities, recordings, notes and outcomes are posted on Canvas.

Resources are also available online through RMIT Library databases and other facilities. Visit the RMIT library website for further details. Assistance is available online via our chat and email services, face to face at our campus libraries or via the telephone on (03) 9925 2020.

Additional resources and/or sources to assist your learning will be identified by your course coordinator and will be made available to you as required during the teaching period.



Overview of Assessment

The assessment tasks, their weighting and the course learning outcomes to which they are aligned are as follows.

Assessment Task 1: 15%;  Linked CLOs: 1, 4   Assessment Task 2: 35%;  Linked CLOs: 1, 2, 3, 4, 5   Assessment Task 3: 50%;  Linked CLOs: 1, 2, 3, 4, 5

Feedback will be provided throughout the semester in class and/or in online forums through individual and group feedback on progress, milestones and approaches, and by individual consultation.