Dates: September 30th, October 14th, October 28th, November 11th, November 25th, December 9th,
Time: 14:00 – 17:00
Venue: Utrecht University, Drift 13, room 0.05
Open to: PhD candidates, (R)MA students, RMeS members, NOG members (Maximum participants 12)
Credits: 3,5 ECTS
Organization: Maranke Wieringa, Gerwin van Schie and Tim de Winkel
Registration: Please send an email to G.A.email@example.com to register
Register before: September 23rd
About the course
This reading seminar brings together perspectives on and approaches to research into various practices, systems and structures dealing with data and algorithms. We will bring together perspectives from critical data studies, gender studies, new materialism and STS in order to think through concepts such as bias, algorithms, data, platforms, knowledge and accountability.
Participants who want to take the course for ECTS, are required to 1) actively participate during the whole course (10%), and 2) write a research proposal (90%). In this research proposal, participants are required to demonstrate how the texts we’ve discussed in the previous weeks could be applied to a research project. The research itself does not have to be executed. Instead, students will produce a proposal, which includes a case, research question(s), and propose an adequate method(ology)/theoretical framework.
3,5 ECTS (of 28 hours each), equates to 98 hours of study load. The study load is distributed as follows:
- 6 seminars of 3 hours each = 18 hour;
- Preparation of seminars 5 x 12 hours (thoroughly reading the texts and formulating questions) = 60 hours;
- Writing a 2500 word research proposal = 20 hours.
About Datafied Society
The Datafied Society research platform addresses societal challenges emerging from novel data practices in public governance and management, (public) media and public space and seizes opportunities for using data practices to foster citizenship, civic participation and creative production. For the coming years, our focus areas are: Government and governmentalities, Social justice and public values, and tool criticism. As part of these focus areas, the Datafied Society will regularly offer rMA students, PhD candidates and other RMeS members a themed course in we will engage in a close-reading and discussion of selected texts.
Meeting 1: The Politics of “Bias”
Date: 30 September, 2019
Session Leader: Gerwin van Schie
- Dave, Kinjal. 2019. “Systemic Algorithmic Harms.” Medium. May 31, 2019. https://points.datasociety.net/systemic-algorithmic-harms-e00f99e72c42.
- Friedman, Batya, and Helen Nissenbaum. 1996. “Bias in Computer Systems.” ACM Transaction on Information Systems 14 (3): 330–47.
- Harding, Sandra. 1991. Whose Science? Whose Knowledge? Thinking from Women’s Lives. Ithaca, NY: Cornell University Press. (Chapter 5. What is Feminist Epistemology? p. 105-137)
- D’Ignazio, Catherine, and Lauren Klein. 2019. Data Feminism. Cambridge, MA: MIT Press Open. Chapter 1 (https://bookbook.pubpub.org/pub/zrlj0jqb)
Meeting 2: Diffraction and Irreducibility
Date: 14 October, 2019
Session Leader: Iris van der Tuin
- Barad, K. (2003). “Posthumanist Performativity: Toward an Understanding of How Matter Comes to Matter.” Signs: Journal of Women in Culture and Society 28(3): 801-31
- Miyazaki, S. (2018). ALGORHYTHMICS: A Diffractive Approach for Understanding Computation. The Routledge Companion to Media Studies and Digital Humanities, edited by Jentery Sayers, 243-249. London and New York: Routledge.
- Van der Tuin, I. 2019. “Deleuze and Diffraction.” In Posthuman Ecologies: Complexity and Process after Deleuze, edited by Rosi Braidotti and Simone Bignall. London: Rowman and Littlefield International. P. 17–39
- Verhoeff, N. and I. Van der Tuin. forthcoming. “Irreducibility.” Critical Concepts for the Creative Humanities
Meeting 3: Radical Technologies, Counter Publics, Fringe Platforms
Date: 28 October, 2019
Session Leader: Tim de Winkel
- Kampourakis, Ioannis. 2016. “Nancy Fraser: Subaltern Counterpublics.” Critical Legal Thinking (blog). November 6, 2016. http://criticallegalthinking.com/2016/11/06/nancy-fraser-subaltern-counterpublics/.
- Lima, L., J. C. S. Reis, P. Melo, F. Murai, L. Araujo, P. Vikatos, and F. Benevenuto. 2018. “Inside the Right-Leaning Echo Chambers: Characterizing Gab, an Unmoderated Social System.” In 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 515–22. https://doi.org/10.1109/ASONAM.2018.8508809.
- de Winkel, Tim. forthcoming. “Fringe Platforms”. chapter 1 of unpublished manuscript.
Meeting 4: Constructing Gender and Race in Biometric-Based Algorithm
Date: 11 November, 2019
Session Leader: Christine Quinan
- Buolamwini, Joy and Gebru, Timnit. 2018. ‘Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification.’ Proceedings of Machine Learning Research 81: 1-15.
- Pugliese, Joseph. 2005. ‘In Silico Race and the Heteronomy of Biometric Proxies: Biometrics in the Context of Civilian Life, Border Security and Counter-Terrorism Laws.’ Australian Feminist Law Journal 23: 1-32.
- Keyes, OS. 2018. ‘The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition.’ Proceedings of the ACM on Human-Computer Interaction 2, No. CSCW, Article 88.
Meeting 5: Algorithms and Art
Date: 25 November, 2019
Session Leader: Rosa Wevers
- Blas, Z., & Gaboury, J. (2016). Biometrics and Opacity: A Conversation. Camera Obscura: Feminism, Culture, and Media Studies, 31(2 92), 155–165. https://doi.org/10.1215/02705346-3592510
- Liljefors, M., & Lee-Morrison, L. (2015). Mapped Bodies : Notes on the Use of Biometrics in Geopolitical Contexts. In A. M. and F. Tylstrup (Ed.), Socioaesthetics: Ambience – Imaginary (pp. 53–72). Leiden, Boston: Koninklijke Brill NV.
- Magnet, S. A. (2011). ‘Representing Biometrics’. In When Biometrics Fail. Gender, Race, and the Technology of Identity. Durham, London: Duke University Press. https://read-dukeupress-edu.proxy.library.uu.nl/books/book/1609/
To watch: Zach Blas, Facial Weaponization Suite. http://www.zachblas.info/works/facial-weaponization-suite/
Meeting 6: Algorithmic Accountability
Date: 9 December, 2019
Session Leader: Maranke Wieringa
- Diakopoulos, N., Friedler, S., Arenas, M., Barocas, S., Hay, M., Howe, B., … Zevenbergen, B. (n.d.). Principles for accountable algorithms. Retrieved October 23, 2017, from http://www.fatml.org/resources/principles-for-accountable-algorithms
- Kemper, Jakko, and Daan Kolkman. 2018. “Transparent to Whom? No Algorithmic Accountability without a Critical Audience.” Information, Communication & Society 0 (0): 1–16. https://doi.org/10.1080/1369118X.2018.1477967.
- Neyland, Daniel. 2016. “Bearing Account-Able Witness to the Ethical Algorithmic System.” Science, Technology, & Human Values 41 (1): 50–76. https://doi.org/10.1177/0162243915598056.
- Seaver, Nick. 2017. “Algorithms as Culture: Some Tactics for the Ethnography of Algorithmic Systems.” Big Data & Society 4 (2): 2053951717738104. https://doi.org/10.1177/2053951717738104.
Preparation and readings:
Literature will be accessible online or will otherwise be made available to students prior to the start of the course.
Credits & certificate
Certificates of participation and credits are available upon request after the event. Event coordinators will decide whether the participant has fulfilled all requirements for the ECTS. Please direct your request to RMeSfirstname.lastname@example.org and include the postal address you want the certificate send to. Note: the certificate itself is not valid as ECTS, you need to validate it yourself at your local Graduate School.