This course examines algorithms as social and cultural objects—products of human labor, politics, and imagination, as much as of mathematics and computation. Drawing on interdisciplinary perspectives from Science and Technology Studies (STS), media studies, and critical data studies, students will explore how algorithms shape and are shaped by social values, institutions, and practices. Topics include algorithmic bias and discrimination, automation and labor, surveillance and governance, platform infrastructures, and the cultural imaginaries of artificial intelligence. Through case studies ranging from social media feeds to predictive policing and generative AI, the course asks: What does it mean to live in a world increasingly governed by algorithms? How do we study, critique, and intervene in algorithmic systems?
Learning Outcomes
Upon successful completion, students will have the knowledge and skills to:
- explain how algorithms and digital platforms reflect and shape social life;
- identify the contributions of STS, media studies, and critical data studies to understanding changes in everyday life;
- describe the ways algorithmic systems affect various social groups, focusing on issues of equity and power.
- compare and contrast major theoretical debates about AI from sociology and digital humanities; and
- apply theories and case studies to develop written analysis of AI-related controversies.
Indicative Assessment
- Short essay (2000 words) (30) [LO 1,2,3]
- Seminar presentation (5 mins) (10) [LO 1,2]
- Class participation (minute papers) (5) [LO 3,4]
- Independent Research Project Report (3000 words) (55) [LO 1,2,3,4,5]
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) 30 hours of contact made up of lectures and tutorial activities
b) 100 hours of independent student research, reading and writing.
Requisite and Incompatibility
Prescribed Texts
Not applicable.
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 |
|---|---|
| 2026 | $4500 |
- International fee paying students
| Year | Fee |
|---|---|
| 2026 | $5820 |
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.
Second Semester
| Class number | Class start date | Last day to enrol | Census date | Class end date | Mode Of Delivery | Class Summary |
|---|---|---|---|---|---|---|
| 7972 | 27 Jul 2026 | 03 Aug 2026 | 31 Aug 2026 | 30 Oct 2026 | In Person | N/A |