• Class Number 6700
  • Term Code 3050
  • Class Info
  • Unit Value 6 units
  • Mode of Delivery Online
    • Dilan Thampapillai
    • Dr Philippa Ryan
    • Dilan Thampapillai
    • Dr Philippa Ryan
  • Class Dates
  • Class Start Date 24/08/2020
  • Class End Date 16/10/2020
  • Census Date 04/09/2020
  • Last Date to Enrol 25/08/2020
SELT Survey Results

Advances in Artificial Intelligence (AI) will be among the primary catalysts of social, economic, scientific, political and legal change in the 21st century. Discussions of AI regulation have gathered force in the wake of notable performance leaps in Machine Learning (ML) — a family of statistical techniques enabling an algorithm to ‘learn’ over time and optimise performance at a task. These advances have yielded marked improvements in related research areas such as computer vision, natural language processing (NLP) and data analytics. Given the transformative potential of AI and other features of the so-called ‘Fourth Industrial Revolution’ there are concerns about how far the law can, and should, adapt to the profound technological changes upon us, and those that lie ahead. If legal adaptation is too slow, these changes can threaten rights, stifle innovation, or catalyse public, environmental and existential risks. If technological change is too fast or ill-conceived, it might be ineffectual, disrupt societal expectations, and undermine the rule of law or public trust essential to a data-driven government. However, if the attainment of non-biological intelligence will be as consequential an event in human history as some suggest, and humanity will only have one shot at ‘getting it right’ the first time, how the law manages this transition—or whether it can—becomes a matter of existential consequence.

In the nearer term, the current wave of AI-hype and investment is fueling the ambitions of developers to apply computation to more aspects of the law and legal processes. This is, however, not the first time this has been attempted, and there are sound reasons for skepticism and temperance. Nonetheless, concurrent breakthroughs have seen the emergence of the so-called ‘Legal Technology’ (LegalTech) industry and development of various tools for use in legal practice, administration, and adjudication. A number of algorithmic decision-making (ADM) systems using ML to simulate aspects of human reasoning are also used in both public and private-sector contexts. From medicine to finance and immigration to criminal justice, ADM systems have proliferated at a remarkable pace—albeit with sometimes lamentable results. While their totalisation is framed as inevitable once various issues around bias, transparency, and fairness are resolved, this comes at the expense of a more fundamental question: should we be building them in the first place?

Despite apparent advantages, the spectre of a ‘rule by algorithm’ is understandably raising alarm. The use of proprietary algorithmic systems to automate legal processes and make consequential—and increasingly sensitive—decisions in both private and public sector contexts does not just raise privacy and due process concerns; it implies a loss of autonomy and control over self-government. How do we assess the benefits and drawbacks of an increasingly algorithmically intermediated society? Is it inevitable, or can we shape the nature and quality of our future with deliberative, evidence-based policy and regulatory interventions? What are the consequences of the ‘black boxing’ of the legal system? Should robots and other artificial agents have rights? What does ‘rule by algorithm’ mean for the autonomy of the legal system and future of liberal democracy and a discursive public sphere? Are we entering a post-human era? Will the future need lawyers?

Artificial Intelligence, Law, & Society (AILS) is an expansive and interdisciplinary module that takes a deep dive into these questions and helps students understand the societal impact of ubiquitous AI, robotics, and automation. While law-led, the module draws insights across the sciences and humanities, and ideas from religion, popular culture, video games, philosophy and literature to help students develop a 3-dimensional understanding of the societal impact of AI and the role of law in mediating its potential harms, and actualising its benefits.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

  1. Articulate and distinguish the theoretical and philosophical underpinnings of artificial intelligence and its role as a primary catalyst of social, economic, scientific, political and legal change in the 21st century.
  2. Construct and defend rationales for the use of ‘Legal Technology’ in legal practice, administration, and adjudication, including software applications leveraging Big Data and related techniques to assess litigation risk, recidivism, and 'predict' the outcome of legal cases.
  3. Evaluate the use of proprietary algorithmic systems to automate legal processes and decision-making in private and public sector contexts.
  4. Critically analyse the ways that AI is shaping and changing life, work and leisure in the 21st century.
  5. Plan and conduct a project to research and critically analyse the societal impact of AI and the role of law in mediating its potential harms, and actualising its benefits.

Required Resources

A reading list will be available on the course Wattle site.

Staff Feedback

Students will be given feedback in the following forms in this course:

  • written comments
  • verbal comments
  • feedback to whole class, groups, individuals, focus group etc

Student Feedback

ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). The feedback given in these surveys is anonymous and provides the Colleges, University Education Committee and Academic Board with opportunities to recognise excellent teaching, and opportunities for improvement. The Surveys and Evaluation website provides more information on student surveys at ANU and reports on the feedback provided on ANU courses.

Other Information

Task submission times refer to Canberra time (AEST/AEDT).

Extensions, late submission and penalties: https://law.anu.edu.au/current-students/policies-procedures/extensions-late-submission-and-penalties

Deferred examination: http://www.anu.edu.au/students/program-administration/assessments-exams/deferred-examinations

Special consideration: http://www.anu.edu.au/students/program-administration/assessments-exams/special-assessment-consideration

Word length and excess word penalties: https://law.anu.edu.au/current-students/policies-procedures/word-length-and-excess-word-penalties

Further information about the course: is available from the course WATTLE page. Students are required to access the WATTLE site regularly throughout the course for any announcements relating to the course.

Class Schedule

Week/Session Summary of Activities Assessment
1 Introduction to Artificial Intelligence (AI)
2 AI in the 20th Century: A social phenomenon
3 Three AI Paradoxes and the Law
4 The Role of AI in Social Relationships of Trust
5 AI & Ethics
6 AI & Applied Areas of Law
7 AI & the Future of Law
8 Future Direction and Reflections on AI

Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
In-class participation 10 % * 12/10/2020 1, 2, 3, 4
Quiz 30 % 14/09/2020 * 1, 2, 3, 4, 5
Research essay 60 % 12/10/2020 30/10/2020 1, 2, 3, 4, 5

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details


ANU has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Misconduct Rule before the commencement of their course. Other key policies and guidelines include:

Assessment Requirements

The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the Academic Integrity . In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.

Moderation of Assessment

Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.


For all courses taught in intensive mode, the ANU College of Law considers participation in the classes offered to be an important part of the educational experience of the graduate program and students are required to attend ALL classes (and all of each class).

In exceptional circumstances, a student may be granted permission by the Course Convenor, in consultation with the Stream Convenor or Director, LLM Program, to miss some classes, provided:

a.      it does not exceed a maximum of 25% of the classes;

b.      permission is requested in advance; and

c.      the request is supported, where appropriate, by adequate documentation.

Failure to comply with this policy may result in a student receiving the grade of NCN (non-complete fail). The normal pressures of work or planned personal trips do not constitute exceptional circumstances to justify an exemption from full compliance of this policy.

Assessment Task 1

Value: 10 %
Return of Assessment: 12/10/2020
Learning Outcomes: 1, 2, 3, 4

In-class participation

Brief description:  Effective participation in this course requires around 6-8 hours of reading each week. 

Preparation and participation in the live classes and online discussion forums is a critical element of the learning required in the course. To enhance your learning further in this course, you will also need to access regularly the course Wattle site. Live classes and online discussion forums will provide opportunities to share reflections and to collaborate in small groups, so that students can receive immediate feedback, as well as seek further clarification to improve their understanding in preparation for assessment tasks 2 and 3.

Nature of Task: Compulsory and non-redeemable. Failure to complete this task will result in a mark of 0. 

Assessment Criteria:  In class and online discussion should demonstrate an understanding of the course content. 

Assessment Task 2

Value: 30 %
Due Date: 14/09/2020
Learning Outcomes: 1, 2, 3, 4, 5


Details of Task: Students must answer 30 multiple choice questions to be completed within 90 minutes. The questions will focus on knowledge of the terminology, process and rules arising from Topics 1, 2, 3 and 4 of the course. 

Nature of the task: Compulsory. Failure to participate will result in 0 marks for this task. If you experience unavoidable and extenuating circumstances and cannot sit the quiz at the due date and time, you should apply for an extension to the College of Law student admin team here:




The College will give you one opportunity to sit the quiz, at the same time one week later. This will be your final opportunity to sit the quiz. 

Release: Monday 14 September 2020, 2pm via WATTLE. Students will have four hours to sit this test, which should take just 90 minutes to complete.

Due: Monday 14 September 2020, 6pm via WATTLE. Submissions after the due date will not be accepted.

Estimated return date: Automated via WATTLE on submission.

Assessment Criteria: N/A

Assessment Task 3

Value: 60 %
Due Date: 12/10/2020
Return of Assessment: 30/10/2020
Learning Outcomes: 1, 2, 3, 4, 5

Research essay

Details of Task: The research essay will require students to conduct independent research that investigates a theme, issue or policy underlying the impact of Artificial Intelligence on law and society. Original research will be required. Essays must include a bibliography, which is excluded from the word count. 

Nature of Task: The research essay is compulsory. Non-completion of this task will result in a 0 for this assessment task. 

Word Limit: 3,600 words 

Release: Students may choose a topic from a list that will be made available by 4 pm Monday 24 August 2020 on Wattle. 

Due Date: Monday 12 October 2020, at 5pm via Turnitin. Students must submit the essay electronically via the Wattle and Turnitin dropboxes on the course Wattle site. Late submissions (without an extension) are permitted, although late penalties will apply. 

Estimated Return Date: Within approximately three weeks of the submission date. 

Assessment Criteria:

a) Understanding of the Issues

  • addresses the question and covers all the important points
  • evidence of close consideration of the question and the research materials drawn on
  • issues raised by the topic are clearly and concisely identified
  • material chosen relates clearly to the topic and is analysed not just summarised or quoted extensively

b) Communication & Development of Argument

  • clear theme or argument
  • arguments logical and well-organised
  • ideas/paragraphs linked coherently

c) Argument/Analysis

  • originality of ideas and critical analysis of the material
  • complexity and insight in dealing with theory/ideas
  • suggestions for change where appropriate
  • interdisciplinary perspective where appropriate
  • addressing opposing arguments
  • well-reasoned conclusions

d) Research

  • research covering primary and secondary materials
  • good organisation of sources and ability to synthesise all the research materials used
  • use of theoretical material where appropriate
  • range of research sources
  • integration of material from research resources into the essay

e) Presentation, style and referencing

  • good use of structure, section headings and paragraphs
  • clarity and conciseness of expression, interesting and engaging of reader
  • use of appropriate terminology and correct grammar, syntax and spelling
  • full and accurate footnotes together with a bibliography
  • style according to Australian Guide to Legal Citation
  • adherence to word limit

Academic Integrity

Academic integrity is a core part of the ANU culture as a community of scholars. At its heart, academic integrity is about behaving ethically, committing to honest and responsible scholarly practice and upholding these values with respect and fairness.

The ANU commits to assisting all members of our community to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. The ANU expects staff and students to be familiar with the academic integrity principle and Academic Misconduct Rule, uphold high standards of academic integrity and act ethically and honestly, to ensure the quality and value of the qualification that you will graduate with.

The Academic Misconduct Rule is in place to promote academic integrity and manage academic misconduct. Very minor breaches of the academic integrity principle may result in a reduction of marks of up to 10% of the total marks available for the assessment. The ANU offers a number of online and in person services to assist students with their assignments, examinations, and other learning activities. Visit the Academic Skills website for more information about academic integrity, your responsibilities and for assistance with your assignments, writing skills and study.

Online Submission

You will be required to electronically sign a declaration as part of the submission of your assignment. Please keep a copy of the assignment for your records. Unless an exemption has been approved by the Associate Dean (Education) submission must be through Turnitin.

Hardcopy Submission

For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.

Late Submission

Individual assessment tasks may or may not allow for late submission. Policy regarding late submission is detailed below:

  • Late submission not permitted. If submission of assessment tasks without an extension after the due date is not permitted, a mark of 0 will be awarded.
  • Late submission permitted. Late submission of assessment tasks without an extension are penalised at the rate of 5% of the possible marks available per working day or part thereof. Late submission of assessment tasks is not accepted after 10 working days after the due date, or on or after the date specified in the course outline for the return of the assessment item. Late submission is not accepted for take-home examinations.

Referencing Requirements

Accepted academic practice for referencing sources that you use in presentations can be found via the links on the Wattle site, under the file named “ANU and College Policies, Program Information, Student Support Services and Assessment”. Alternatively, you can seek help through the Students Learning Development website.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information.
In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service – including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy.
If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

Distribution of grades policy

Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.

Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.

Support for students

The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).

Dilan Thampapillai

Research Interests

Dilan Thampapillai

Dr Philippa Ryan

Research Interests

The lecturers in this course are experts in this field and their teaching is led by their scholarship and research into AI and the impact of new technologies on society and the law.

Dr Philippa Ryan

By Appointment
Dilan Thampapillai
+61 2 6125 3483

Research Interests

Dilan Thampapillai

Dr Philippa Ryan
+61 2 6125 3483

Research Interests

Dr Philippa Ryan

By Appointment

Responsible Officer: Registrar, Student Administration / Page Contact: Website Administrator / Frequently Asked Questions