Postgraduate Course: Ethical Data Futures (EFIE11554)
Course Outline
| School | Edinburgh Futures Institute |
College | College of Arts, Humanities and Social Sciences |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Not available to visiting students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | *EFI Skills and Methods Suite*
Please Note:
This course is only available to students enrolled on one of Edinburgh Futures Institute's postgraduate programmes.
This course introduces the fundamentals of data ethics as the building blocks of a mature data philosophy. By examining contemporary data practices in their historical, moral and political contexts, students will identify how values in data practice shape our past, present and futures, while developing through collaborative activities six critical data skills required for responsible and ethical data practice. |
| Course description |
This 20-credit core EFI shared course provides an in-depth introduction to ethical data futures, examining how values, norms, and power shape data practices and data-driven technologies. Building on ethical theory and contemporary debates in data ethics, the course situates data practices within their historical, social, political, and institutional contexts.
Through lectures, seminars, and collaborative workshops, students engage with real-world data scenarios to identify morally salient features of data artefacts and infrastructures, analyse stakeholder interests, and deliberate on ethically responsible courses of action. Emphasis is placed on collective ethical reasoning, disagreement, and uncertainty as integral to responsible data practice.
The course supports students in synthesizing collaborative ethical deliberation into individual analytical and reflective work, equipping them with conceptual tools and practical skills for ethical judgement in data-intensive domains. By the end of the course, students will be prepared to engage critically and responsibly with emerging data futures across professional and societal contexts.
Edinburgh Futures Institute (EFI) - Hybrid Course Delivery Information:
The Edinburgh Futures Institute delivers many of its courses in hybrid mode. This means that you may have some online students joining sessions for this course. To enable this, the course will use technologies to record and live-stream student and staff participation during their teaching and learning activities.
Students should be aware that:
- Classrooms used in this course will have additional technology in place: in some cases, students might not be able to sit in areas away from microphones or outside the field of view of all cameras.
- All presentations, and whole class discussions will be recorded (see the Lecture Recording and Virtual Classroom policies for more details).
You will need access to a personal computing device for this course. Most activities will take place in a web browser, unless otherwise stated. We recommend using a device with a screen, a physical keyboard, and internet access.
|
Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Course Delivery Information
|
| Academic year 2026/27, Not available to visiting students (SS1)
|
Quota: 120 |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 20,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
176 )
|
| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
The course will be assessed by means of the following components:
1) Collaborative Ethical Case Analysis (60%)
A group-based collaborative ethical case analysis, drawing on a shared data scenario. Students participate in structured ethical deliberation and submit an individual 2,000 analytical write-up.
Learning Outcomes Assessed by Component: 1, 2, 3, 4
2) Individual Reflective and Synthetic Essay (40%)
Students will produced a 2,000 word Individual reflective and synthetic essay integrating collaborative discussion, ethical theory, and critical reflection on data futures.
Learning Outcomes Assessed by Component: 1, 3, 5
|
| Feedback |
Feedback on any formative assessment may be provided in various formats, for example, to include written, oral, video, face-to-face, whole class, or individual. The Course Organiser will decide which format is most appropriate in relation to the nature of the assessment.
Feedback on both formative and summative in-course assessed work will be provided in time to be of use in subsequent assessments within the course.
Feedback on the summative assessment(s) will be provided in written form via Learn, the University of Edinburgh's Virtual Learning Environment (VLE).
Formative Feedback Opportunity:
Formative feedback is ongoing feedback which monitors learning and is intended to improve performance in the same course, in future courses, and also beyond study.
Online discussions will receive group-level feedback at the midpoint during the course, highlighting for students areas where their critical ethical skills are being successfully deployed and where their application could be strengthened to facilitate the collaborative task.
This feedback will be formative in strengthening students' metacognitive attention to the collaborative dimension of ethical data challenges. The goal is to move students away from the common- but limiting- idea of ethics as a private, subjective domain of personal value commitments or preferences, and toward an engagement with data ethics as a maturing social, moral and political practice through which more just and sustainable futures are co-constructed.
This will also feed-forward into the final assessment, in which students must analyse the discussions as data that can inform the development of more successful collective responses to the ethical challenges facing our shared futures with data. |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Critically reflect, individually and collaboratively, on the values and norms embedded in contemporary data practices and data-driven systems.
- Identify and analyse morally salient features of data artefacts, infrastructures, and practices across social, institutional, and technological contexts.
- Evaluate ethical challenges and possible courses of action for diverse stakeholders affected by data-driven decision-making.
- Articulate, justify, and contest ethical positions concerning data futures using appropriate ethical concepts and frameworks.
- Synthesize collaborative ethical deliberation into clear, well-reasoned individual analysis.
|
Reading List
Ethics and politics of data
Excavating AI: The Politics of Images in Machine Learning Training Sets.
Author: Crawford, Kate and Trevor Paglen Type: Website Publisher: The AI Now Institute Publication Date:
2019
An Introduction to Data Ethics
Author: Vallor, Shannon Type: Document Publisher: Markkula Center for Applied Ethics Publication Date:
2018
Ethics of contemporary data practices
Voices in the Code A Story About People, Their Values, and the Algorithm They Made Author: David G. Robinson Type: E-book ISBN: 978-0-87154-777-4 Publisher: Russell Sage Foundation Publication Date: September, 2022
Economies of Virtue: The Circulation of 'Ethics' in Big Tech
Science as culture Author: Phan, Thao ; Goldenfein, Jake ; Mann, Monique ; Kuch, Declan Type: Article ISSN: 09505431 Publisher:
Routledge Place of Publication: ABINGDON Publication Date: 2022-01-02 Total Pages: 121-135 Pages:
121-135 Volume: 31 Issue: 1 DOI: 10.1080/09505431.2021.1990875
Emerging challenges in ethical data practice
On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?
FAccT '21: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency
Author: Bender, Emily M., Gebru, Timnit, McMillan-Major, Angelina and Schmitchell, Shmargaret. 202 Type:
Article Publication Date: March 3 10, 2021 Pages: 610-623 DOI: 10.1145/3442188.3445922
MEAN IMAGES New Left review
Author: Steyerl, Hito Type: Article ISSN: 00286060 Publisher: New Left Rev Ltd Place of Publication:
LONDON Publication Date: 2023-03-01 Total Pages: 82-97 Pages: 82-97 Volume: 140-141 Issue: 140
Politics and power dynamics in contemporary data practices
The Threat of Algocracy: Reality, Resistance and Accommodation
Philosophy & technology
Author: Danaher, John Type: Article ISSN: 22105433 Publisher: Springer Netherlands Place of Publication:
Dordrecht Publication Date: 2016 Total Pages: 245-268 Pages: 245-268 Volume: 29 Issue: 3 DOI:
10.1007/s13347-015-0211-1
Data feminism Author: D'Ignazio, Catherine and Lauren F. Klein. Additional Person Name: Klein, Lauren F., author. Type:
E-book ISBN: 0262358530 OCLC Number: (ckb)4100000010465076 Publisher: The MIT Press Place of
Publication: Cambridge, Massachusetts Publication Date: 2020 Notes: Includes bibliographical references
(pages [235]-301) and indexes.
Data ethics as a collaborative social project of futures-building
Race after technology : abolitionist tools for the New Jim Code / Ruha Benjamin.
Author: Benjamin, Ruha, author. Type: E-book ISBN: 9781509526437 LCCN: 2018059981 OCLC Number: (ocolc)1078415817 Publisher: Polity Press Place of Publication: Newark Publication Date: 2019 Notes:
Includes bibliographical references (pages 240-273) and index.
Data Science as Political Action: Grounding Data Science in a Politics of Justice
Journal of social computing
Author: Green, Ben Type: Article ISSN: 26885255 Publisher: Tsinghua University Press Publication Date:
2021-09-01 Total Pages: 249-265 Pages: 249-265 Volume: 2 Issue: 3 DOI: 10.23919/JSC.2021.0029 |
Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | EFI,Edinburgh Futures Institute,Level 11,PGT,Ethics,Data,Values,ethical skills |
Contacts
| Course organiser | Dr Cristina Richie
Tel:
Email: crichie2@ed.ac.uk |
Course secretary | Miss Abby Gleave
Tel: (0131 6)51 1337
Email: abby.gleave@ed.ac.uk |
|
|
University Homepage