Students

COMP6400 – Intelligent Machines, Ethics and Law

2026 – Session 1, In person-scheduled-weekday, North Ryde

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff Convenor, Lecturer
Xiaohan Yu
xiaohan.yu@mq.edu.au
Contact via Email
Floor 3, 3IR
By Appointment
Lecturer
Regina Fabry
regina.fabry@mq.edu.au
Contact via Email
By Appointment
Lecturer
Niloufer Selvadurai
niloufer.selvadurai@mq.edu.au
Contact via Email
By Appointment
Lecturer
Rita Matulionyte
rita.matulionyte@mq.edu.au
Contact via Email
By Appointment
Credit points Credit points
10
Prerequisites Prerequisites
Corequisites Corequisites
Co-badged status Co-badged status
COMP2400
Unit description Unit description

This unit is co-designed and co-taught by experts from relevant fields. It introduces modern Artificial Intelligence (AI) technology, and evaluates the capabilities of several intelligent systems on well-known tasks such as facial recognition and the assessment of insurance claims. In the context of these systems, the unit will address fundamental societal (legal/ political/ ethical) issues  that need to be addressed when designing and deploying AI-powered computer applications towards achieving Responsible AI. The implications of such requirements on the use of AI systems will be discussed along with possible technical remedies to address them.

Learning in this unit enhances student understanding of global challenges identified by the United Nations Sustainable Development Goals (UNSDGs) Industry, Innovation and Infrastructure; Peace, Justice and Strong Institutions

Important Academic Dates

Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates

Learning Outcomes

On successful completion of this unit, you will be able to:

  • ULO1: Employ existing AI systems on benchmark business problems and evaluate the results.
  • ULO2: Demonstrate an appreciation of the ethical, legal, and other socioeconomic implications of AI.
  • ULO3: Outline sustainable remedial measures for proposed AI solutions, aligned with the ethical and legal requirements, in the business context.
  • ULO4: Effectively communicate to various stakeholders how the potential legal, ethical and social issues are addressed in the context of the solutions developed.

General Assessment Information

This unit is jointly taught by academics from Philosophy (Weeks 2 to 5), Law (Weeks 6 to 9) and Computing (Weeks 10 to 13). Correspondingly there are three assessment tasks. Should there be a need for clarification or help regarding assessment tasks, students should contact corresponding teaching staff. The convenor should be contacted only if the problem does not get resolved.

 

Requirements to Pass this Unit

To pass this unit you must:

  • Achieve a total mark equal to or greater than 50%.

Release

  • Assessment 1 - Media Presentation: To be released no later than 06/03/2026 
  • Assessment 2 - Mid-Term Exam: To be released on week 9 SGTA
  • Assessment 3 - Programming Assignment: To be released no later than 11/05/2026

Late Assessment Submission and Penaltie

Late Submission Policy - 5% penalty per day: If you submit your assessment late, 5% of the total possible marks will be deducted for each day (including weekends), up to 7 days. - Example 1 (out of 100): If you score 85/100 but submit 20 hours late, you will lose 5 marks and receive 80/100. - Example 2 (out of 30): If you score 27/30 but submit 1 day late, you will lose 1.5 marks and receive 25.5/30. - After 7 days: Submissions more than 7 days late will receive a mark of 0. - Extensions: - Automatic short extension: Some assessments are eligible for automatic short extension. You can only apply for an automatic short extension before the due date. - Special Consideration: If you need more time due to serious issues and for any assessments that are not eligible for Short Extension, you must apply for Special Consideration.

Need help? Review the Special Consideration page HERE

  • Assessment 1 - Media Presentation: YES, Standard Late Penalty applies 
  • Assessment 2 - Mid-Term Exam: YES, Standard Late Penalty applies 
  • Assessment 3 - Programming Assignment: YES, Standard Late Penalty applies 

Special Consideration

The Special Consideration Policy aims to support students who have been impacted by short-term circumstances or events that are serious, unavoidable and significantly disruptive, and which may affect their performance in assessment. If you experience circumstances or events that affect your ability to complete the assessments in this unit on time, please inform the convenor and submit a Special Consideration request through http://connect.mq.edu.au/.

Assessment Tasks

Name Weighting Hurdle Due Groupwork/Individual Short Extension AI Approach
Media Presentation Assignment 30% No Due 02/04/2026 Individual No Observed
Midterm Examination 45% No In week 9 SGTA Individual No Observed
Programming Assignment 25% No 05/06/2026 Individual Yes Open

Media Presentation Assignment

Assessment Type 1: Presentation task
Indicative Time on Task 2: 30 hours
Due: Due 02/04/2026
Weighting: 30%
Groupwork/Individual: Individual
Short extension 3: No
AI Approach: Observed

You will reflect on a relevant issue and deliver a presentation elaborating on your ideas.
On successful completion you will be able to:
  • Demonstrate an appreciation of the ethical, legal, and other socioeconomic implications of AI.
  • Outline sustainable remedial measures for proposed AI solutions, aligned with the ethical and legal requirements, in the business context.
  • Effectively communicate to various stakeholders how the potential legal, ethical and social issues are addressed in the context of the solutions developed.

Midterm Examination

Assessment Type 1: Examination
Indicative Time on Task 2: 30 hours
Due: In week 9 SGTA
Weighting: 45%
Groupwork/Individual: Individual
Short extension 3: No
AI Approach: Observed

You will sit an exam assessing your understanding of societal issues related to AI systems.
On successful completion you will be able to:
  • Demonstrate an appreciation of the ethical, legal, and other socioeconomic implications of AI.
  • Outline sustainable remedial measures for proposed AI solutions, aligned with the ethical and legal requirements, in the business context.
  • Effectively communicate to various stakeholders how the potential legal, ethical and social issues are addressed in the context of the solutions developed.

Programming Assignment

Assessment Type 1: Experiential task
Indicative Time on Task 2: 25 hours
Due: 05/06/2026
Weighting: 25%
Groupwork/Individual: Individual
Short extension 3: Yes
AI Approach: Open

You will run pre-trained AI systems on business problems and present the results of your experiments, evaluations, and analyses.
On successful completion you will be able to:
  • Employ existing AI systems on benchmark business problems and evaluate the results.
  • Demonstrate an appreciation of the ethical, legal, and other socioeconomic implications of AI.
  • Outline sustainable remedial measures for proposed AI solutions, aligned with the ethical and legal requirements, in the business context.
  • Effectively communicate to various stakeholders how the potential legal, ethical and social issues are addressed in the context of the solutions developed.

1 If you need help with your assignment, please contact:

  • the academic teaching staff in your unit for guidance in understanding or completing this type of assessment
  • Academic Success for academic skills support.

2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation.

3 An automatic short extension is available for some assessments. Apply through the Service Connect Portal.

Delivery and Resources

This unit is co-badged with COMP2400.  It is designed to be offered on a Face-to-Face format. Apart from lectures, there are practical classes (associated with the computing related lectures -- Weeks 10 onwards) and SGTAs (Weeks 2-13). Specifically, there are no SGTAs or practical classes in Week 1. Please consult the university timetable for venue and time.

There is no text book for the unit. Necessary resources will be provided by the teaching team on the iLearn page.

The assessment of this unit includes some writing tasks. Limited training in writing skills will be provided through regular learning and teaching activities. Students are also strongly encouraged to utilise the support provided by the university, via facilities such as the Writing Centre. Details are provided under "Student Support" below.

Week 1 Classes

In week 1, the lecture will cover Unit organization + Advice on writing essays/reports. The lecture will be onsite on Thursday (2.0 hrs) 10:00am-11:59am (14SCO Mason Lecture Theatre). SGTA will start from week 2.

 

Methods of Communication

We will communicate with you via your university email and through announcements on iLearn. Queries to convenors can either be placed on the iLearn discussion board or sent to the unit convenor via the contact email on iLearn.

Unit Schedule

  1. Unit organization + Advice on writing essays/reports (Week 1, Xiaohan Yu, Computing)
  2. Ethical aspects of AI (Weeks 2-5, Regina Fabry, Philosophy)
  3. Legal aspects of AI (Weeks 6-9, Rita Matulyonite and Niloufer Selvadurai, Law)
  4. Computational aspects of AI (Weeks 10-13, Xiaohan Yu, Computing) 

Policies and Procedures

Macquarie University policies and procedures are accessible from Policy Central (https://policies.mq.edu.au). Students should be aware of the following policies in particular with regard to Learning and Teaching:

Students seeking more policy resources can visit Student Policies (https://students.mq.edu.au/support/study/policies). It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.

To find other policies relating to Teaching and Learning, visit Policy Central (https://policies.mq.edu.au) and use the search tool.

Student Code of Conduct

Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/admin/other-resources/student-conduct

Results

Results published on platform other than eStudent, (eg. iLearn, Coursera etc.) or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit connect.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au

Academic Integrity

At Macquarie, we believe academic integrity – honesty, respect, trust, responsibility, fairness and courage – is at the core of learning, teaching and research. We recognise that meeting the expectations required to complete your assessments can be challenging. So, we offer you a range of resources and services to help you reach your potential, including free online writing and maths support, academic skills development and wellbeing consultations.

Student Support

Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/

Academic Success

Academic Success provides resources to develop your English language proficiency, academic writing, and communication skills.

The Library provides online and face to face support to help you find and use relevant information resources. 

Student Services and Support

Macquarie University offers a range of Student Support Services including:

Student Enquiries

Got a question? Ask us via the Service Connect Portal, or contact Service Connect.

IT Help

For help with University computer systems and technology, visit http://www.mq.edu.au/about_us/offices_and_units/information_technology/help/. 

When using the University's IT, you must adhere to the Acceptable Use of IT Resources Policy. The policy applies to all who connect to the MQ network including students.

Changes from Previous Offering

Total assessment number has decreased from 4 to 3 in order to satisfy the new 3AM policy. Assessment 2 has been changed to Exam (mid-term). The weight of three assessments have been updated as follows:

1. Assessment 1: Weight increase from 25% to 30%.

2. Assessment 2: Weight increase from 30% to 45% (exam)

3. Assessment 3: Weight decreases from 30% to 25%.

Unit information based on version 2026.04 of the Handbook