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:
- 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.
- 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.
- Evaluate the use of proprietary algorithmic systems to automate legal processes and decision-making in private and public sector contexts.
- Critically analyse the ways that AI is shaping and changing life, work and leisure in the 21st century.
- 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.
Indicative Assessment
- In-class participation (10) [LO 1,2,3,4]
- Reflective journal (30) [LO 1,2,3,4,5]
- Research essay (60) [LO 1,2,3,4,5]
In response to COVID-19: Please note that Semester 2 Class Summary information (available under the classes tab) is as up to date as possible. Changes to Class Summaries not captured by this publication will be available to enrolled students via Wattle.
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Workload
Classes offered in non-standard sessions will be taught on an intensive base with compulsory contact hours (approximately 26 hours of face to face teaching). The course will also require advanced preparation through assigned readings. In total, it is anticipated that the hours required for completion of this course (class preparation, teaching and completion of assessment) will not exceed 120 hours. Classes offered during semester periods are expected to have 3 contact hours per week.
Click here for the LLM Masters Program timetable.
Inherent Requirements
Not applicable
Requisite and Incompatibility
Prescribed Texts
Students must rely on the approved Class Summary which will be posted to the Programs and Courses site approximately 2 weeks prior to the commencement of the course.
Fees
Tuition fees are for the academic year indicated at the top of the page.
If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.
- Student Contribution Band:
- 3
- Unit value:
- 6 units
If you are an undergraduate student and have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). You can find your student contribution amount for each course at Fees. Where there is a unit range displayed for this course, not all unit options below may be available.
Units | EFTSL |
---|---|
6.00 | 0.12500 |
Course fees
- Domestic fee paying students
Year | Fee |
---|---|
2020 | $4320 |
- International fee paying students
Year | Fee |
---|---|
2020 | $5760 |
Offerings, Dates and Class Summary Links
ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
Winter Session
Class number | Class start date | Last day to enrol | Census date | Class end date | Mode Of Delivery | Class Summary |
---|---|---|---|---|---|---|
6700 | 24 Aug 2020 | 25 Aug 2020 | 04 Sep 2020 | 16 Oct 2020 | Online | View |