Course coordinator
Dr Sungyong Ahn
Student consultation available via zoom or in-person; please email to make an appointment
Course overview
- Study period
- Semester 2, 2024 (22/07/2024 - 18/11/2024)
- Study level
- Undergraduate
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Communication & Arts School
The scale and scope of automation is an increasingly persistent feature of our everyday lives. In this course, students will engage with the deeper context of our faith in algorithms, and the aspirations, anxieties, ambitions and fantasies that have brought them to life. Course content will explore the science, ethics, politics and sensory experience of automation, from its historical inception to its technocratic and popular applications in contemporary life and the spaces we inhabit. Students will develop a grounded knowledge of the value systems shaping automated systems in the modern world, before progressing to a critical evaluation of the automated future that is central to the ambitions of contemporary digital cultures.
Course contact
Course staff
Lecturer
Dr Sungyong Ahn
Timetable
The timetable for this course is available on the UQ Public Timetable.
Additional timetable information
Whilst every effort is made to place students in their preferred activity, it is not always possible for a student to be enrolled in their tutorial of choice. If you require assistance, please ensure that you email timetabling.commarts@enquire.uq.edu.au from your UQ student email with:
- Your name
- Your student ID
- The course code
- A list of three tutorial preferences (in order of preference)
- Reason for the change – e.g. timetable clash, elite athlete status, SAP
Teaching staff do not have access to change tutorials or help with timetables; all timetabling changes must be processed through the Timetabling Team.
Aims and outcomes
In this course, you will examine and engage with the aspirations, anxieties, ambitions and fantasies that have characterised our understanding of, and experiences with, automation. You will explore the science, ethics, politics and sensory experience of automations, from its historical inception to its technocratic and popular applications in contemporary life, focusing especially on the rise of algorithmic culture and artificial intelligence. This course provides a grounded knowledge of the value systems shaping automated systems in the modern world, before progressing to a critical evaluation of the automated future that is centra to the ambitions of contemporary digital cultures.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Critically investigate and evaluate the history and contemporary cultural impact of automation
LO2.
Analyse automation from a variety of historical, philosophical, aesthetic, sociological, technological and political perspectives
LO3.
Communicate effectively about the key debates and scholarship in the study of automation
LO4.
Think and write critically about the cultural impact of automation on everyday life, drawing on key debates and scholarship
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Participation/ Student contribution |
Weekly Tutorial Workshops
|
20% |
Week 2 - Week 13
These workshops will be completed during your tutorials. |
| Presentation, Reflection |
Discussion Leader + Critical Reflection
|
20% |
You will be allocated a week in which to lead a class discussion in your Week 2 tutorial. You must submit a written reflection by Friday 4pm before the tutorial you are allocated as a discussion leader. |
| Paper/ Report/ Annotation | Field Research | 25% |
20/09/2024 4:00 pm |
| Essay/ Critique | Research Essay | 35% |
8/11/2024 4:00 pm |
Assessment details
Weekly Tutorial Workshops
- In-person
- Mode
- Activity/ Performance
- Category
- Participation/ Student contribution
- Weight
- 20%
- Due date
Week 2 - Week 13
These workshops will be completed during your tutorials.
- Learning outcomes
- L01, L02, L03
Task description
Each week you will complete an in-class activity, or workshop, during your tutorial, from Week 2 to Week 13. These workshops will be completed during your tutorials. You must attend your tutorial to complete that week’s workshop. Please advise your tutor if you are unable to attend. Each workshop will receive a grade of complete or incomplete. You must complete at least 5 workshops to pass this assignment.
Your workshop instructions will be provided each week on Blackboard.
This assessment task is to be completed in-person. The use of generative Artificial Intelligence (AI) or Machine Translation (MT) tools will not be permitted. Any attempted use of AI or MT may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
You can find a TurnItIn link in a folder for each tutorial in Learning Resource folder on Blackboard.
TurnItIn Receipts:
Assignments for this course will be submitted electronically via Blackboard and using TurnItIn. Before submitting any assignments for this course you must ensure you have completed UQ's compulsory online Academic Integrity Tutorial.
When you successfully submit your assessment to TurnItIn you will see text confirming your submission is complete, before being redirected to your Assignment inbox. On this page you can:
- View the name of the submitted file
- View date and time of the upload
- Resubmit your paper (if necessary)
- Download your submitted paper
- Download digital receipt.
If you cannot see your submission in your Assignment inbox you should regard your submission as unsuccessful. Students are responsible for retaining evidence of submission by the due date for all assessment items, in the required form (e.g. screenshot, email, photo, and an unaltered copy of submitted work).
If the submission was not successful:
- Note the error message (preferably take a screenshot).
- Go to your assignment page and see if it is possible to submit again.
- If you cannot submit again email your course coordinator immediately with the assignment attached.
Please visit this webpage for further advice on how to submit your TurnItIn assignment.
Deferral or extension
You cannot defer or apply for an extension for this assessment.
Please note: this is an in-class assessment item and students are NOT able to apply for an extension via the Unitask portal. Please advise your tutor if you are unable to attend.
Late submission
Late submission is not possible for this piece of assessment.
Discussion Leader + Critical Reflection
- In-person
- Mode
- Activity/ Performance
- Category
- Presentation, Reflection
- Weight
- 20%
- Due date
You will be allocated a week in which to lead a class discussion in your Week 2 tutorial. You must submit a written reflection by Friday 4pm before the tutorial you are allocated as a discussion leader.
- Learning outcomes
- L01, L03
Task description
You will be allocated a week in which to lead a class discussion in your Week 2 tutorial. You must submit a written reflection via TurnItIn by Friday 4pm before the tutorial you are allocated as a discussion leader.
Further information is available in the Assessment 2 folder on Blackboard.
This assessment task evaluates students' abilities, skills and knowledge without the aid of generative Artificial Intelligence (AI) or Machine Translation (MT). Students are advised that the use of AI or MT technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Recording of Oral and Practical Assessment
All presentations will be recorded for marking purposes via recording facilities available where the assessment takes place (eg. ECHO360, Zoom, camera device)
Recordings will be retained by the School of Communication and Arts for at least 12 months from the release of the final grade for the course.
Recordings will be stored in a secure manner and will only be accessed by authorised school staff for the purposes of:
- Moderation of marking;
- Provision of feedback to the student(s) recorded; and/or
- Re-marking following a successful re-mark application
Submission guidelines
Submit your written reflection via Turnitin.
TurnItIn Receipts:
Assignments for this course will be submitted electronically via Blackboard and using TurnItIn. Before submitting any assignments for this course you must ensure you have completed UQ's compulsory online Academic Integrity Tutorial.
When you successfully submit your assessment to TurnItIn you will see text confirming your submission is complete, before being redirected to your Assignment inbox. On this page you can:
- View the name of the submitted file
- View date and time of the upload
- Resubmit your paper (if necessary)
- Download your submitted paper
- Download digital receipt.
If you cannot see your submission in your Assignment inbox you should regard your submission as unsuccessful. Students are responsible for retaining evidence of submission by the due date for all assessment items, in the required form (e.g. screenshot, email, photo, and an unaltered copy of submitted work).
If the submission was not successful:
- Note the error message (preferably take a screenshot).
- Go to your assignment page and see if it is possible to submit again.
- If you cannot submit again email your course coordinator immediately with the assignment attached.
Please visit this webpage for further advice on how to submit your TurnItIn assignment.
Deferral or extension
You cannot defer or apply for an extension for this assessment.
Please note: this is an in-class assessment item and students are NOT able to apply for an extension via the Unitask portal. Please contact your tutor directly if you need to reschedule your in-class discussion session.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Late submission is not possible for the in-class discussion session part of this assessment.
Field Research
- Mode
- Written
- Category
- Paper/ Report/ Annotation
- Weight
- 25%
- Due date
20/09/2024 4:00 pm
- Learning outcomes
- L01, L04
Task description
For this assessment, you choose an example of automation in everyday life, related to (at least) one of the week’s readings or topics. Your example may include one of the museums on campus, an experience of automation you have had in every day life, or an analysis of automation in popular culture (such as playing an online game). You will write a 1000-word description or analysis of your chosen example.
Your text can include images, embedded video and sound files, as relevant. Your work must be fully referenced and properly formatted. It should include:
- A cover page with your name, the title of your assignment (blog post or case study), the course name, and the word count
- A clear explanation of your chosen example
- An argument or analysis about the cultural significance or impact of your example
- A complete list of references
Further information is available in the Assessment 3 folder on Blackboard.
This assessment task evaluates students' abilities, skills and knowledge without the aid of generative Artificial Intelligence (AI) or Machine Translation (MT). Students are advised that the use of AI or MT technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Submit via TurnItIn.
TurnItIn Receipts:
Assignments for this course will be submitted electronically via Blackboard and using TurnItIn. Before submitting any assignments for this course you must ensure you have completed UQ's compulsory online Academic Integrity Tutorial.
When you successfully submit your assessment to TurnItIn you will see text confirming your submission is complete, before being redirected to your Assignment inbox. On this page you can:
- View the name of the submitted file
- View date and time of the upload
- Resubmit your paper (if necessary)
- Download your submitted paper
- Download digital receipt.
If you cannot see your submission in your Assignment inbox you should regard your submission as unsuccessful. Students are responsible for retaining evidence of submission by the due date for all assessment items, in the required form (e.g. screenshot, email, photo, and an unaltered copy of submitted work).
If the submission was not successful:
- Note the error message (preferably take a screenshot).
- Go to your assignment page and see if it is possible to submit again.
- If you cannot submit again email your course coordinator immediately with the assignment attached.
Please visit this webpage for further advice on how to submit your TurnItIn assignment.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Research Essay
- Mode
- Written
- Category
- Essay/ Critique
- Weight
- 35%
- Due date
8/11/2024 4:00 pm
- Learning outcomes
- L01, L02, L04
Task description
For this assessment, you will write a formal research essay on a subject, question or issue related to automation, of your own choosing. You will have time to discuss and prepare the topic of your podcast or research essay in class.
Your research essay will draw on one or more examples of automation of your own choice. You are strongly encouraged to choose examples of automation that interest you, or with which you have first-hand experience. Originality and depth of analysis will be part of the assessment for your research essay, so it is advisable to focus your discussion on ONE or TWO specific case studies. Specific and detailed analysis will make a stronger argument than general or vague analysis.
Your essay will demonstrate research. It will critically discuss and engage with the course readings listed for at least two of the weeks of this course. You are encouraged to refer to the list of recommended readings as well as required readings. Your essay should demonstrate evidence of a comprehensive knowledge and understanding of your subject.
The text of your podcast or research essay should be fully and consistently referenced. The essay must have a bibliography of all sources you quote or consulted.
Further information is available in the Assessment 4 folder on Blackboard.
This assessment task evaluates students' abilities, skills and knowledge without the aid of generative Artificial Intelligence (AI) or Machine Translation (MT). Students are advised that the use of AI or MT technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Submit via TurnItIn.
TurnItIn Receipts:
Assignments for this course will be submitted electronically via Blackboard and using TurnItIn. Before submitting any assignments for this course you must ensure you have completed UQ's compulsory online Academic Integrity Tutorial.
When you successfully submit your assessment to TurnItIn you will see text confirming your submission is complete, before being redirected to your Assignment inbox. On this page you can:
- View the name of the submitted file
- View date and time of the upload
- Resubmit your paper (if necessary)
- Download your submitted paper
- Download digital receipt.
If you cannot see your submission in your Assignment inbox you should regard your submission as unsuccessful. Students are responsible for retaining evidence of submission by the due date for all assessment items, in the required form (e.g. screenshot, email, photo, and an unaltered copy of submitted work).
If the submission was not successful:
- Note the error message (preferably take a screenshot).
- Go to your assignment page and see if it is possible to submit again.
- If you cannot submit again email your course coordinator immediately with the assignment attached.
Please visit this webpage for further advice on how to submit your TurnItIn assignment.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Course grading
Full criteria for each grade is available in the Assessment Procedure.
| Grade | Cut off Percent | Description |
|---|---|---|
| 1 (Low Fail) | 1 - 24 |
Absence of evidence of achievement of course learning outcomes. |
| 2 (Fail) | 25 - 44 |
Minimal evidence of achievement of course learning outcomes. |
| 3 (Marginal Fail) | 45 - 49 |
Demonstrated evidence of developing achievement of course learning outcomes |
| 4 (Pass) | 50 - 64 |
Demonstrated evidence of functional achievement of course learning outcomes. |
| 5 (Credit) | 65 - 74 |
Demonstrated evidence of proficient achievement of course learning outcomes. |
| 6 (Distinction) | 75 - 84 |
Demonstrated evidence of advanced achievement of course learning outcomes. |
| 7 (High Distinction) | 85 - 100 |
Demonstrated evidence of exceptional achievement of course learning outcomes. |
Additional course grading information
- Where fractional marks occur in the calculation of the final grade, a mark of x.5% or greater will be rounded up to (x+1)%. A percentage mark of less than x.5% will be rounded down to x%.
- Where no assessable work is received, a Grade of X will apply. ﾠ
Supplementary assessment
Supplementary assessment is available for this course.
Additional assessment information
- Further information regarding the assessment, including marking criteria and/or marking rubrics are available in the ‘Assessment’ folder in Blackboard for this course.
- Marks Cannot Be Changed After Being Released: Marks are not open to negotiation with course staff. If you wish to discuss the feedback you have received, you should make an appointment to speak with the Course Coordinator.
- Assessment Re-mark: If you are considering an Assessment Re-mark, please follow the link to important information you should consider before submitting a request.
- Integrity Pledge: Assignments for this course will be submitted electronically via Blackboard and using Turnitin. Before submitting any assignments for this course, you must ensure you have completed UQ's compulsory online Academic Integrity Modules.ﾠIn uploading an assignment via Turnitin you are certifying that it is your original work, that it has not been copied in whole or part from another person or source except where this is properly acknowledged, and that it has not in whole or part been previously submitted for assessment in any other course at this or any other university.
- Withholding marks prior to finalisation of grades: Per UQ Assessment Procedures – Release of Assessment Item Marks and Grades: The final assessment item and the marks for the assessment item are to be released only after the final grade for the course has been released.
Learning resources
You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.
Library resources
Find the required and recommended resources for this course on the UQ Library website.
Learning activities
The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.
Filter activity type by
Please select
| Learning period | Activity type | Topic |
|---|---|---|
Week 1 (22 Jul - 28 Jul) |
Lecture |
Week 1: Welcome Lecture Learning outcomes: L01 |
Tutorial |
Week 1: NO TUTORIALS Tutorials start in Week 2. |
|
Week 2 (29 Jul - 04 Aug) |
Lecture |
Week 2 Lecture: Clockwork, the First Machines Required Reading: Schafer, Mechanical Marvels (Documentary) Learning outcomes: L01, L02 |
Tutorial |
Week 2 Tutorial: Early Automation Learning outcomes: L01, L02, L03, L04 |
|
Week 3 (05 Aug - 11 Aug) |
Lecture |
Week 3 Lecture: Industrial Automation Required Reading: Marvin, When Old Technologies Were New Learning outcomes: L01, L02 |
Tutorial |
Week 3 Tutorial: Electricity and Mass Production Learning outcomes: L01, L02, L03, L04 |
|
Week 4 (12 Aug - 18 Aug) |
Lecture |
Week 4: NO LECTURE DUE TO PUBLIC HOLIDAY |
Tutorial |
Week 4: NO TUTORIALS DUE TO PUBLIC HOLIDAY |
|
Week 5 (19 Aug - 25 Aug) |
Lecture |
Week 5 Lecture: Automated Media Required Reading: Andrejevic, Automated Media Learning outcomes: L01, L02 |
Tutorial |
Week 5 Tutorial: Automation in Popular Culture Learning outcomes: L01, L02, L03, L04 |
|
Week 6 (26 Aug - 01 Sep) |
Lecture |
Week 6 Lecture: Robots and Cyborgs Required Reading: Flash Forward (Podcast) Abnet, American Robot Learning outcomes: L01, L02 |
Tutorial |
Week 6 Tutorial: Automated Life Learning outcomes: L01, L02, L03, L04 |
|
Week 7 (02 Sep - 08 Sep) |
Lecture |
Week 7 Lecture: Smart Homes Required Reading: Sadowski, Too Smart Learning outcomes: L01, L02 |
Tutorial |
Week 7 Tutorial: Mechanisation in Everyday Life Learning outcomes: L01, L02, L03, L04 |
|
Week 8 (09 Sep - 15 Sep) |
Lecture |
Week 8 Lecture: Automated Futures Required Reading: "The Machine Stops" (short story) Learning outcomes: L01, L02 |
Tutorial |
Week 8 Tutorial: Popular Representations of Automation Learning outcomes: L01, L02, L03, L04 |
|
Week 9 (16 Sep - 22 Sep) |
Lecture |
Week 9 Lecture: Automation and Algorithms Required Reading: Slack et al, Algorithmic Cultures Learning outcomes: L01, L02 |
Tutorial |
Week 9 Tutorial: Automated Cultures Learning outcomes: L01, L02, L03, L04 |
|
Mid Sem break (23 Sep - 29 Sep) |
No student involvement (Breaks, information) |
Mid-Semester Break |
Week 10 (30 Sep - 06 Oct) |
Lecture |
Week 10 Lecture: Automation as Metaphor Required Reading: Garland, Ex Machina (film) Learning outcomes: L01, L02 |
Tutorial |
Week 10 Tutorial: Automation, Race and Gender Learning outcomes: L01, L02, L03, L04 |
|
Week 11 (07 Oct - 13 Oct) |
Lecture |
Week 11: NO LECTURE DUE TO PUBLIC HOLIDAY |
Tutorial |
Week 11: NO TUTORIALS DUE TO PUBLIC HOLIDAY |
|
Week 12 (14 Oct - 20 Oct) |
Lecture |
Week 12 Lecture: Artificial Intelligence Required Reading: Crawford, Atlas of AI Learning outcomes: L01, L02 |
Tutorial |
Week 12 Tutorial: AI and Automated Decision Making Learning outcomes: L01, L02, L03, L04 |
|
Week 13 (21 Oct - 27 Oct) |
Lecture |
Week 13 Lecture: "Fauxtomation" Required Reading: Tayler, "Automation Charade" Learning outcomes: L01, L02 |
Tutorial |
Week 13 Tutorial: Limits of Automation Learning outcomes: L01, L02, L03, L04 |
Policies and procedures
University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:
- Student Code of Conduct Policy
- Student Integrity and Misconduct Policy and Procedure
- Assessment Procedure
- Examinations Procedure
- Reasonable Adjustments - Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.