In Progress
Please note that this Unit Profile is still in progress. The content below is subject to change.Overview
This unit is designed for students who want to develop knowledge and skills in the automation of the practice of law. This unit incorporates theory, research and the practical application of legal project management, process improvement and innovation frameworks, expert systems, document and process automation, data analytics, machine learning and blockchain. Students will examine software systems that empower consumers including lawyerless internet-based systems that vend interactive documents and intelligent legal assistance. Intelligent systems designed for lawyers to produce inexpensive transactional outcomes will be considered. The challenges, threats, opportunities and ethical considerations associated with these developments will be explored. Consideration will also be given as to how governments, pro bono and community legal centres may directly benefit from automation. Through engagement with legal knowledge engineering, students will develop a legal App. No programming experience or other technical knowledge is required.
Details
Pre-requisites or Co-requisites
Co-requisites: LAWS11057 and LAWS11059, or LAWS11030
Important note: Students enrolled in a subsequent unit who failed their pre-requisite unit, should drop the subsequent unit before the census date or within 10 working days of Fail grade notification. Students who do not drop the unit in this timeframe cannot later drop the unit without academic and financial liability. See details in the Assessment Policy and Procedure (Higher Education Coursework).
Offerings For Term 1 - 2026
Attendance Requirements
All on-campus students are expected to attend scheduled classes - in some units, these classes are identified as a mandatory (pass/fail) component and attendance is compulsory. International students, on a student visa, must maintain a full time study load and meet both attendance and academic progress requirements in each study period (satisfactory attendance for International students is defined as maintaining at least an 80% attendance record).
Recommended Student Time Commitment
Each 6-credit Undergraduate unit at CQUniversity requires an overall time commitment of an average of 12.5 hours of study per week, making a total of 150 hours for the unit.
Class Timetable
Assessment Overview
Assessment Grading
This is a graded unit: your overall grade will be calculated from the marks or grades for each assessment task, based on the relative weightings shown in the table above. You must obtain an overall mark for the unit of at least 50%, or an overall grade of 'pass' in order to pass the unit. If any 'pass/fail' tasks are shown in the table above they must also be completed successfully ('pass' grade). You must also meet any minimum mark requirements specified for a particular assessment task, as detailed in the 'assessment task' section (note that in some instances, the minimum mark for a task may be greater than 50%). Consult the University's Grades and Results Policy for more details of interim results and final grades.
All University policies are available on the CQUniversity Policy site.
You may wish to view these policies:
- Grades and Results Policy
- Assessment Policy and Procedure (Higher Education Coursework)
- Review of Grade Procedure
- Student Academic Integrity Policy and Procedure
- Monitoring Academic Progress (MAP) Policy and Procedure - Domestic Students
- Monitoring Academic Progress (MAP) Policy and Procedure - International Students
- Student Refund and Credit Balance Policy and Procedure
- Student Feedback - Compliments and Complaints Policy and Procedure
- Information and Communications Technology Acceptable Use Policy and Procedure
This list is not an exhaustive list of all University policies. The full list of University policies are available on the CQUniversity Policy site.
Feedback, Recommendations and Responses
Every unit is reviewed for enhancement each year. At the most recent review, the following staff and student feedback items were identified and recommendations were made.
Feedback from Students request: Clarification of assessment requirements in response to assessment feedback
Clarify ‘assessment requirements’
The Unit Coordinator will review marking rubrics prior to the next offering to ensure clarity, fairness, and consistent performance differentiation.
Feedback from Reviewer comment
Unit coordinator to specify plan for promotion and visibility of LAWS13019
It is proposed that the unit should be promoted more broadly within the School of Business and Law. This can occur through presentation at the next School of Business and Law meeting which should aim to raise awareness of the availability of LAWS13019 as an elective unit and for other Unit Coordinators to recommend/endorse same to their students, if possible.
Feedback from Reviewer Comments
Clarify how LAWS13019 is linked to professional employment outcomes
It is also proposed that for the next 2026 offering, LAWS13019 learning outcomes should explicitly map to the Bachelor of Laws degree structure. This could include mapping between LAWS13019 assessment tasks to key legal industry skills being made visible in the Week 1 orientation session for new students. This will help students recognise the relevance of artificial intelligence in the legal profession to their degree and employability.
Feedback from End of term feedback from students: Requested clearer explanations of unit learning outcomes
Clarify key ‘take-aways’ in Unit Profile for LAWS13019
The unit profile will be refreshed prior to the 2026 offering to highlight key take-aways from the LAWS13019 unit, such as hands-on building and operation of artificial intelligence tools, automation, legal tech, and the ability to critically evaluate the risks in using artificial intelligence products within contemporary legal practice.
Feedback from Reviewer Comments
Add competitor relevance note
Unit Profile to include statement that comparable units exist elsewhere in other Australian University offerings and that retaining LAWS13019 sustains CQU competitiveness. It should be noted on the unit profile that this unit provides greater breadth and depth into the use of artificial intelligence within the Australian Legal Profession, notably by offering a build-your-own AI solution assessment structure.
Feedback from Student feedback
Clearer explanation of assessment rubrics
Removed complex rubric descriptors and referenced proposed coordinated review process. It is proposed that rubric and assessment alignment should be reviewed by the Unit Coordinator and their direct supervisor. This should occur prior to the next offering to ensure continued rigor and transparency for the unit.
- Apply process improvement and innovation frameworks to the delivery of legal work
- Identify aspects of legal work and new forms of service delivery that can be automated
- Classify what ethical and regulatory issues are presented by lawyering using intelligent machines
- Construct a software application using teamwork that can model legal knowledge and reasoning to perform useful legal work for non lawyers as a form of social innovation.
This is not an accredited unit.
Alignment of Assessment Tasks to Learning Outcomes
| Assessment Tasks | Learning Outcomes | |||
|---|---|---|---|---|
| 1 | 2 | 3 | 4 | |
| 1 - Practical Assessment - 80% | ||||
| 2 - Group Work - 20% | ||||
Alignment of Graduate Attributes to Learning Outcomes
| Graduate Attributes | Learning Outcomes | |||
|---|---|---|---|---|
| 1 | 2 | 3 | 4 | |
| 1 - Communication | ||||
| 2 - Problem Solving | ||||
| 3 - Critical Thinking | ||||
| 4 - Information Literacy | ||||
| 5 - Team Work | ||||
| 6 - Information Technology Competence | ||||
| 7 - Cross Cultural Competence | ||||
| 8 - Ethical practice | ||||
| 9 - Social Innovation | ||||
| 10 - Aboriginal and Torres Strait Islander Cultures | ||||