AANA18127U Economies of Tech (BOA)
The course is accepted as part of the BOA specialisation.
From spring 2024 the course is also offered to students at the
- Master Programme in Social Data Science
- Master Programme in Political Science
- Master Programme in Economics
- Master programme in Global Development
-Master Programme in Psychology
Enrolled students register the course through the Selfservice. Please contact the study administration at each programme for questions regarding registration.
The course is open to:
- Exchange and Guest students from abroad
- Credit students from Danish Universities
With the new forms of technology have come new ways of valuing people, things, practices, and ideas. From data-driven credit-ratings impacting people’s chance of a mortgage, to platforms monetizing attention in our digital dealings, the intersection of technology and economy plays a large role for people across the world. Popular documentaries and books point to the way economies in/of technologies have also become matters of public concern. The initial optimism and hype of tech and ‘free’ data has given way to a skepticism to the ways that new forms of digital technology and data seem instead to increase the wealth and power of a select few, on the one hand, and increasing surveillance and control for many, on the other. With these new technologies we must take into account powerful new actors such as tech-corporations, platforms, algorithms, and big data that shape the playing ground for our future society.
Within this nexus, anthropologists and social scientists from adjacent disciplines have the potential to contribute to both academic and public debates regarding economies of technology by engaging both critically and productively with the way that technology is shaping society and making specific assertions about what is “of value”. This course aims to equip students with knowledge, skills, and competencies to engage with the current developments in tech by building on classical as well as current theoretical perspectives from fields including economic and digital anthropology, sociology, and science and technology studies (STS).
The course begins with a historical perspective on the development of current economic and tech-structures, asking what is actually new. It then examines types of tech economies and forms of valuation, considering topics such as the power of platforms, the producers of tech such as software engineers and users, prediction algorithms, digital money and markets, and surveillance capitalism. Activities in the course include group discussions, exercises, debates, and group presentations based on a reading of students’ choice. Students will develop their own argument about the changing economies of tech during the course using an empirical case. Students will have the opportunity to submit a topic proposal (max 4 pages) for peer feedback and to present their case for feedback at a workshop, before writing the final essay.
At the end of the course students must be able to:
Knowledge:
- Describe key questions and debates regarding tech-related economies and economic practices
- Demonstrate knowledge of anthropological and related theories and cases relating to the study of economies and technologies based on relevant literature
- Demonstrate knowledge of developments in economic practices relating to technology
Skills:
- Identify and describe ethnographic and empirical cases relevant to the study of economies and technologies
- Identify how things, people, practices, and ideas are made to be of value
Competences:
- Formulate research questions and arguments that interrogate economic and valuation perspectives on technology in relation to empirical cases
- Apply the principles and theories acquired during the course to different ethnographic and empirical settings
- Analyze similarities and differences in changing economic and technological practices
- Analyze the impact of economic and technological practices for different actors
See Absalon
- Category
- Hours
- Lectures
- 42
- Preparation
- 133
- Exam
- 35
- Total
- 210
Feedback will be provided throughout the course, including oral and peer feedback.
When registered you will be signed up for exam.
- Full-degree students – sign up at Selfservice on KUnet
- Exchange and guest students from abroad – sign up through Mobility Online and Selfservice
- Credit students from Danish universities - sign up through this website.
The dates for the exams are found here Exams – Faculty of Social Sciences - University of Copenhagen (ku.dk)
Please note that it is your own responsibility to check for overlapping exam dates.
- Credit
- 7,5 ECTS
- Type of assessment
- Written assignment
- Type of assessment details
- One BA student: 21.600-26.400 keystrokes. For group responses,
Min. 6,750 and Max. 8,250 extra keystrokes per extra group member.
One MA student: 27,000-33,000 keystrokes. For group responses, Min. 8,450 and Max. 10,300 extra keystrokes per extra group member.
For groups with both BA and MA students:
A MA and a BA student: 31,900-38,975 (BA: 14.175-17.325 KA: 17.725-21.650)
A MA and two BA students: 38,050 – 46,475 (BA: 11,700-14.300 KA: 14.650-17.875)
A MA and three BA students: 44,525-54,375 (BA: 10.475-12,800 MA: 13.100-15.975)
Two MA and one BA student: 41,000-50,050 (BA: 11,700-14.300 KA: 14.650-17.875)
Two MA and two BA students: 47,150-57,550 (BA: 10.475-12,800 MA: 13.100-15.975)
Three MA and one BA student: 49,775-60,725 (BA: 10.475-12,800 MA: 13.100-15.975)
Literature
MA students must include supplementary literature in the exam assignment. The supplementary literature is chosen by the student.
Information of level and contribution
Students must indicate on the first page of the assignment whether they are a BA or MA students. In the case of group assignments, the contribution of each individual student must be clearly marked in the assignment.
Re-exam:
1st and 2nd re-exam: A new essay must be submitted. The new assignment must be submitted by the deadline for the re-exam. - Aid
- All aids allowed
Policy on the Use of Generative AI Software and Large Language Models in Exams
The Department of Anthropology allows the use of generative AI software and large language models (AI/LLMs), such as ChatGPT, in written exams, provided that the use of AI/LLMs is disclosed and specified (i.e., how it was used and for what purpose) in an appendix that does not count towards the page limit of the exam.
If AI/LLMs are used as source, the same requirements apply for using quotation marks and source referencing as with all other sources. Otherwise, it will be a case of plagiarism.
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
- Re-exam
Se "Type of assessment details" above
Criteria for exam assesment
See learning outcome.
Course information
- Language
- English
- Course code
- AANA18127U
- Credit
- 7,5 ECTS
- Level
- BachelorBachelor choice,Full Degree Master,Full Degree Master choice
- Duration
- 1 semester
- Placement
- Spring
- Schedule
- See timetable
Study board
- Department of Anthropology, Study Council
Contracting departments
- Department of Anthropology
- Department of Psychology
- Department of Political Science
- Social Data Science
- Department of Economics
Contracting faculty
- Faculty of Social Sciences
Course Coordinators
- Samantha Dawn Breslin (16-7765716572786c653266766977706d72446572786c7673326f7932686f)