From our smartphones to our welfare states, we are increasingly dependent on systems that deploy some form or other of artificial intelligence. But despite the central role that AI now plays in our lives, philosophers have been slow to shape our understanding of where we are now, and where we should go next. In this course, we will explore the novel philosophical questions raised by data and AI, drawing on moral and political philosophy, but also philosophy of science and epistemology, and throughout remaining closely engaged with the technical and empirical realities of data and AI. Our goal will be not only to navigate the normative uncertainties we face as we engage with new technologies, but also to demonstrate the exciting prospects for further study in the field of Philosophy, AI and Society (PAIS).
Learning Outcomes
Upon successful completion, students will have the knowledge and skills to:
- understand and articulate the key philosophical issues relating to the role of AI in society;
- engage in philosophical discussion and debate on the various issues relating to the role of AI in society;
- critically assess arguments about the appropriate place of AI in society; and
- clearly articulate their own position with respect to contemporary real world debates about AI in society.
Indicative Assessment
- Tutorial Contributions (in-class participation or written responses to readings) (10) [LO 1,2]
- Problem Sets (20) [LO 1,3,4]
- Essay 1 (1000 Words) (35) [LO 1,3,4]
- Essay 2 (1000 Words) (35) [LO 1,3,4]
The ANU uses 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. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.
Workload
130 hours of total student learning time made up from:
a) 36 hours of contact over 12 weeks: 24 hours of lectures, 12 hours of tutorials, plus up to 12 hours optional workshop-like activities.
b) 94 hours of independent student research, reading and writing.
Inherent Requirements
Not applicable
Requisite and Incompatibility
Prescribed Texts
Not applicable
Preliminary Reading
Selbst and Barocas, ‘Big Data’s Disparate Impact’
Corbett-Davies and Goel ‘The Measure and Mismeasure of Fairness’
Kleinberg, Mullainathan et al. ‘Discrimination in the Age of Algorithms’
Selbst and Barocas, ‘The Intuitive Appeal of Explainable Machines’
Barocas and Nissenbaum, "Big Data's End-Run around Anonymity and Consent'
Assumed Knowledge
No knowledge of AI will be assumed.
Fees
Tuition fees are for the academic year indicated at the top of the page.
Commonwealth Support (CSP) Students
If you 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). More information about your student contribution amount for each course at Fees.
- Student Contribution Band:
- 14
- Unit value:
- 6 units
If you are a domestic graduate coursework student with a Domestic Tuition Fee (DTF) place or international student you will be required to pay course tuition fees (see below). Course tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found 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 |
|---|---|
| 2024 | $4080 |
- International fee paying students
| Year | Fee |
|---|---|
| 2024 | $5280 |
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.
First Semester
| Class number | Class start date | Last day to enrol | Census date | Class end date | Mode Of Delivery | Class Summary |
|---|---|---|---|---|---|---|
| 3920 | 19 Feb 2024 | 26 Feb 2024 | 05 Apr 2024 | 24 May 2024 | In Person | View |
