Undergraduate Course: Ethics and Politics of Data (EFIE08004)
Course Outline
| School | Edinburgh Futures Institute |
College | College of Arts, Humanities and Social Sciences |
| Credit level (Normal year taken) | SCQF Level 8 (Year 1 Undergraduate) |
Availability | Available to all students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | The story of data helps us better understand the growing power of data in today's world. This course asks the question 'what are the ethical implications of data, and how do they come to be?' Working collaboratively, students from across the disciplines will uncover the moral and political values that shape human practices of counting, measuring, and labelling reality, in the process developing the foundational skills of critical and responsible data practice. |
| Course description |
This course asks and answers the question 'what are the ethical implications of data, and how do they come to be?' The story of data reveals the moral and political values that shape human practices of counting, measuring, and labelling reality, and helps us better understand the growing power of data in today's world. Designed to engage students across the disciplines, this introductory course offers a foundational integration of basic concepts and methods of data science with the historical and philosophical context that reveals their ethical and political dimensions as inseparable from their scientific value. The course draws from the disciplines of philosophy, critical race and gender studies, sociology, history, mathematics, computer science and the design arts to build up a more comprehensive picture of how data are constructed, interpreted, shared and used for a growing range of scientific, commercial, public and creative purposes.
The course content begins with a general introduction to the concept of data and its origins and uses, building up to an outline of the core data concepts and methods increasingly that increasingly shape contemporary society. In the second course phase, ethical and political theories of justice, power, bias, identity, consent, and rights, among others, are used to further contextualise our relationships to data. The third phase reveals how unreflective views about the relationship between data and reality have often led to failed scientific endeavours and harmful social and political outcomes. In the fourth and final phase, students use the conceptual tools they have acquired to practice identifying and correcting these limited perspectives on data. (These four phases are overlapping and enmeshed, rather than cleanly demarcated; the progression represents the dominant theme/emphasis of each course phase). Throughout the course, 2 hour seminars are structured to accomplish 1) short (35-45 min) lectures on historical, moral and political context of a data practice; 2) an active discussion (45 minutes) of theoretical frames, concepts and critical tools from the reading as they apply to the practice; 3) presentation and discussion (15 min) of an artefact, technique or case study related to the data practice that will be the subject of tutorial group task (1 hour weekly).
By engaging in discussion-centered seminars and, during non-teaching weeks, working collaboratively in tutorial groups on well-defined critical and analytical tasks related to the seminar content, students will experience the transformation from a passive understanding of data and a data-driven society, to a habit of active, collaborative and critical engagement with data and how they are constructed and used to promote particular social and political values, goals and arrangements. This habit is the cornerstone of the mature data philosophy that students will build throughout their EFI journey, as they acquire and practice the critical data skills needed for the responsible and trustworthy use of data across a wide range of academic and professional settings.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Information for Visiting Students
| Pre-requisites | None |
| High Demand Course? |
Yes |
Course Delivery Information
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| Academic year 2024/25, Available to all students (SV1)
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Quota: 40 |
| Course Start |
Semester 1 |
| Course Start Date |
16/09/2024 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Seminar/Tutorial Hours 22,
Other Study Hours 15,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
159 )
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| Additional Information (Learning and Teaching) |
Other Study: Scheduled Group-work Hours - 15
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
All assessment is pass/fail.
Short Blog Post - 750 word blog post - Week 5
- Demonstrates ability to articulate ethical and political dimensions of a data context or artefact already discussed in lecture, readings & autonomous learning groups, and begin to reflect critically upon their implications for the truth-value, reliability, limitations and moral and political uses of the data for specific human purposes. Students will be required to use a combination of written and visual media to identify and display the unresolved tensions, conflicts, ambiguities and uncertainties in the data story.
Case Study Analysis - 1500 words - Final
- Demonstrating ability to identify the ethical and political values and assumptions embedded in a novel data context (a research study, dataset, other data artefact, technique or initiative), as well as critically assess its potential moral and political risks or benefits, as well as identifying potential remedies/mitigations. Lectures and autonomous learning groups in weeks 8-11 will support and scaffold this analysis, though the final will be an individual pass/fail assignment rather than a group project. |
| Feedback |
Feedback will be in the form of written comments on assignments, with the option for students to attend office hours for further individualised feedback.
Feedback for assessment 1 will feed forward to assessment 2 (the final assessment ) in showing where the moral and political dimensions of data practices and their implications might have been more effectively identified or analysed. From this feedback, the student is encouraged to reflect more fully in preparation for the final assessment about the ethical and political implications of data shape individual outcomes, events, trends and institutions. |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Explain and give examples of how ethical and political factors have shaped particular historical and contemporary data practices.
- Identify and distinguish relevant ethical and political dimensions across a range of emerging data contexts and practices, for example, through analysis of a novel research study, commercial technology, data-driven scientific technique or local government initiative.
- Recognize basic concepts and widely used methods of qualitative and quantitative data collection, labelling, analysis, interpretation, presentation and use, and describe how and where ethical and political values and structures may be implicitly or explicitly embedded within these.
- Deploy critical thinking and collaboration skills to interrogate and test specific assumptions, methodologies, or artefacts that may reveal naïve, skewed, or incomplete understandings of data, assess their potential harms to scientific research and/or to society, and collectively envision potential mitigating/corrective steps to improve data understanding and practice.
- Identify and reflect upon key value tensions, unresolved conflicts and ambiguities surrounding our historical, moral and political relationships with data; for example: open questions about data ownership, rights, justice and public good, the complex relationship between data bias and objectivity or 'ground truth', and the future role of data in addressing complex social challenges such as climate change, public health, ecological degradation, and rising inequality.
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Reading List
Essential
Race After Technology : Abolitionist Tools for the New Jim Code
Author: Benjamin, Ruha. Type: E-book ISBN: 9781509526437 LCCN: 2018059981 OCLC Number: (ocolc)1078415817 Publisher: Polity Press Place of Publication: Cambridge ; Melford Publication Date: 2019
Sorting Things Out : Classification and its Consequences
Author: Bowker, Geoffrey C and Susan Leigh Star Type: E-book ISBN: 9780262269070 OCLC Number: (mitcognet)120216 Publisher: The MIT Press Place of Publication: Cambridge, MA Publication Date: 2000 DOI: https://doi-org.ezproxy.is.ed.ac.uk/10.7551/mitpress/6352.001.0001
Ghost work : How to Stop Silicon Valley from Building a New Global Underclass
Author: Gray, Mary L and Siddharth Suri Type: E-book ISBN: 9781328566287 LCCN: 2018044155 OCLC Number: (ocolc)1052904039 Publisher: Harcourt Place of Publication: Boston Publication Date: 2019
Dark Data : Why What You Don't Know Matters
Author: Hand, David J. Type: E-book ISBN: 9780691198859 LCCN: 2019022972 OCLC Number:
(de-b1597)544509 Publisher: Princeton University Press, Place of Publication: Princeton Publication Date: 2020 DOI: 10.1515/9780691198859
Terms of Inclusion: Data, Discourse, Violence
New media & society
Author: Hoffmann, Anna Lauren Type: Article ISSN: 14614448 Publisher: SAGE PUBLICATIONS LTD Place of Publication: LONDON Publication Date: 2020 Total Pages: 146144482095872- Pages: 3539-3556 Volume: 23 Issue: 12 DOI: 10.1177/1461444820958725
Data Lives : How Data are Made and Shape Our World
Author: Kitchin, Rob. Type: E-book ISBN: 9781529215168 OCLC Number: (stdubds)edz2592846 Publisher: Bristol University Press Place of Publication: Bristol Publication Date: 2021 Edition: 1 DOI: 10.1332/policypress/9781529215144.001.0001
Privacy in Context : Technology, Policy, and the Integrity of Social Life
Author: Nissenbaum, Helen Fay. Type: E-book ISBN: 9780804772891 LCCN: 2009026320 OCLC Number: (ocolc)436310287 Publisher: Stanford University Press Place of Publication: Stanford Publication Date: 2010
Data Feminism
Author: D'Ignazio, Catherine and Lauren F. Klein Type: E-book ISBN: 9780262358521 OCLC Number: 1130235839 Publisher: MIT Press Place of Publication: Cambridge Publication Date: 2020 DOI: https://doi.org/10.7551/mitpress/11805.001.0001
Excavating AI: The Politics of Images in Machine Learning Training Sets
AI & society
Author: Crawford, Kate ; Paglen, Trevor Type: Article ISSN: 09515666 Publication Date: 2021 Pages: 1105-1116 Volume: 36 DOI: 10.1007/s00146-021-01162-8
Voices in the Code : A Story About People, Their Values, and the Algorithm They Made
Author: Robinson, David G Type: E-book ISBN: 9780871547774 OCLC Number: (caonfjc)cis64359592 Publisher: Russell Sage Foundation Place of Publication: New York Publication Date: 2022 DOI: https://doi-org.ezproxy.is.ed.ac.uk/10.7758/9781610449144
Using AI ethically to tackle covid-19
BMJ (Online)
Author: Cave, Stephen ; Whittlestone, Jess ; Nyrup, Rune ; O hEigeartaigh, Sean ; Calvo, Rafael A Type: Article ISSN: 09598146 Publisher: Bmj Publishing Group Place of Publication: LONDON Publication Date: 2021-03-15 Total Pages: n364-n364 Pages: n364-n364 Volume: 372 DOI: 10.1136/bmj.n364
Ethical Dimensions of Visualization Research
Author: Correll, Michael Type: Conference Publisher: Cornell University Library, arXiv.org Place of Publication: Ithaca Publication Date: 2019-01-01 Pages: 1-13 DOI: 10.1145/3290605.3300418
Critical InfoVis: Exploring the Politics of Visualization
CHI 2013 Extended Abstracts, April 27¿May 2, 2013, Paris, France.
Author: Marian Do¿rk, Christopher Collins, Patrick Feng, Sheelagh Carpendale Type: Article Publication Date: April 2013 Pages: 2189-2198 DOI: https://doi.org/10.1145/2468356.2468739
When AI can make art: What does it mean for creativity?
The Guardian
Author: Laurie Clarke Type: Article Publication Date: 12 Nov 2022
India Has Been Collecting Eye Scans and Fingerprint Records from Every Citizen. Here¿s
What to Know
Time Magazine
Author: Billy Perrigo Type: Article Publication Date: 28 September 2018
Recommended
Cloud Ethics : Algorithms and the Attributes of Ourselves and Others
Author: Amoore, Louise. Type: E-book ISBN: 9781478009276 OCLC Number: 1142244622 Publisher: Duke University Press Place of Publication: Durham Publication Date: 2020 DOI: https://doi-org.ezproxy.is.ed.ac.uk/10.1215/9781478009276
Browne, Simone. Dark matters: On the surveillance of blackness. Duke University Press, 2015.
Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence
Philosophy & technology
Author: Mohamed, Shakir ; Png, Marie-Therese ; Isaac, William Type: Article ISSN: 22105433 Publisher: Springer Netherlands Place of Publication: Dordrecht Publication Date: 2020-07-12 Total Pages: 659-684 Pages: 659-684 Volume: 33 Issue: 4 DOI: 10.1007/s13347-020-00405-8
Do Datasets Have Politics? Disciplinary Values in Computer Vision Dataset Development
Proceedings of the ACM on human-computer interaction
Author: Scheuerman, Morgan Klaus ; Hanna, Alex ; Denton, Emily Type: Article ISSN: 25730142 Publication
Date: 2021-10-13 Total Pages: 1-37 Pages: 1-37 Volume: 5 Issue: CSCW2 DOI: 10.1145/3476058
How We Became Our Data : A Genealogy of the Informational Person
Author: Koopman, Colin. Type: E-book ISBN: 9780226626611 LCCN: 2018048197 OCLC Number: (ocolc)1051697173 Publisher: The University of Chicago Press Place of Publication: Chicago Publication Date: 2019 Student note: Introduction, 1-32, Chapter 2, "Algorithmic Personality", 66-107 and Chapter 3, "Outputs Segregating Data", 108-150. .
Further Reading
Where Fairness Fails: Data, Algorithms, and the Limits of Antidiscrimination Discourse
Information, communication & society
Author: Hoffmann, Anna Lauren Type: Article ISSN: 1369118X Publisher: Routledge Place of Publication: ABINGDON Publication Date: 2019-06-07 Total Pages: 900-915 Pages: 900-915 Volume: 22 Issue: 7 DOI: 10.1080/1369118X.2019.1573912
Numbered Lives : Life and Death in Quantum Media
Author: Wernimont, Jacqueline. Type: E-book ISBN: 9780262350174 LCCN: 2018010473 OCLC Number: (ocolc)1028604269 Publisher: MIT Press Place of Publication: Cambridge, MA Publication Date: 2018
The Sum of the People : How the Census has Shaped Nations, from the Ancient World to
the Modern Age
Author: Whitby, Andrew Type: Book ISBN: 9781541619340 LCCN: 2019956629 OCLC Number: (ocolc)1140116172 Publisher: Basic Books Place of Publication: New York Publication Date: 2020 Edition: First edition.
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Additional Information
| Graduate Attributes and Skills |
This course will incorporate knowledge and understanding of the historical, moral and political contexts of data; skills of practice in applying this knowledge to concrete case studies and contemporary challenges with data; cognitive skills of critical reflection, analysis, and evaluation of data practices, ICT and collaborative skills in critically analysing data artefacts and practices in learning groups. |
| Keywords | Data ethics,justice,human rights,values,ground truth,bias,power,representation,data models,imaging |
Contacts
| Course organiser | Dr Cristina Richie
Tel:
Email: crichie2@ed.ac.uk |
Course secretary | Miss Katarzyna Pietrzak
Tel:
Email: K.Pietrzak@ed.ac.uk |
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