Universität Wien
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210116 VO M7: SpezialVO State Activity, Policy and Governance Analyses (2021W)

Governing Algorithms: The Politics of Data and Decision-Making

4.00 ECTS (2.00 SWS), SPL 21 - Politikwissenschaft
MIXED

Nicht-prüfungsimmanente (n-pi) Lehrveranstaltung. Eine Anmeldung über u:space ist erforderlich. Mit der Anmeldung werden Sie automatisch für die entsprechende Moodle-Plattform freigeschaltet. Vorlesungen unterliegen keinen Zugangsbeschränkungen.

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Moodle

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Details

Language: English

Examination dates

Lecturers

Classes (iCal) - next class is marked with N

/// THE LECTURE WILL TAKE PLACE ONLINE VIA ZOOM. ///

(Link provided on Moodle.)

  • Monday 04.10. 18:30 - 20:00 Hybride Lehre
    Hörsaal 31 Hauptgebäude, 1.Stock, Stiege 9
  • Monday 11.10. 18:30 - 20:00 Hybride Lehre
    Hörsaal 31 Hauptgebäude, 1.Stock, Stiege 9
  • Monday 18.10. 18:30 - 20:00 Hybride Lehre
    Hörsaal 31 Hauptgebäude, 1.Stock, Stiege 9
  • Monday 25.10. 18:30 - 20:00 Hybride Lehre
    Hörsaal 31 Hauptgebäude, 1.Stock, Stiege 9
  • Monday 08.11. 18:30 - 20:00 Hybride Lehre
    Hörsaal 31 Hauptgebäude, 1.Stock, Stiege 9
  • Monday 15.11. 18:30 - 20:00 Hybride Lehre
    Hörsaal 31 Hauptgebäude, 1.Stock, Stiege 9
  • Monday 22.11. 18:30 - 20:00 Hybride Lehre
    Hörsaal 31 Hauptgebäude, 1.Stock, Stiege 9
  • Monday 29.11. 18:30 - 20:00 Hybride Lehre
    Hörsaal 31 Hauptgebäude, 1.Stock, Stiege 9
  • Monday 06.12. 18:30 - 20:00 Hybride Lehre
    Hörsaal 31 Hauptgebäude, 1.Stock, Stiege 9
  • Monday 13.12. 18:30 - 20:00 Hybride Lehre
    Hörsaal 31 Hauptgebäude, 1.Stock, Stiege 9
  • Monday 10.01. 18:30 - 20:00 Hybride Lehre
    Hörsaal 31 Hauptgebäude, 1.Stock, Stiege 9
  • Monday 17.01. 18:30 - 20:00 Hybride Lehre
    Hörsaal 31 Hauptgebäude, 1.Stock, Stiege 9
  • Monday 24.01. 18:30 - 20:00 Hybride Lehre
    Hörsaal 31 Hauptgebäude, 1.Stock, Stiege 9
  • Monday 31.01. 18:30 - 20:00 Hybride Lehre
    Hörsaal 31 Hauptgebäude, 1.Stock, Stiege 9

Information

Aims, contents and method of the course

Algorithms are a ‘grey eminence’ in a growing number of social contexts: from communication to consumption to dating to public administration. With increasingly abundant digital data and computing power, algorithms play an ever more pervasive role in producing and certifying knowledge and in informing decision-making. Though they promise efficiency and objectivity, algorithms have also been associated with new forms of power, exclusion and manipulation.

The present lecture series (Ringvorlesung) gives an overview over key debates on algorithmic governance at the intersection of political science, legal theory and technology studies. At the centre stands the question of how society is being governed by digital technologies and how digital technologies are themselves (to be) governed. The lecture series introduces core concepts and theories and explores a set of empirical cases and applications.
For the line-up of topics and speakers please see here: https://digigov.univie.ac.at/teaching/lecture-series/

The lecture is organised by the cross-faculty research platform ‘Governance of Digital Practices’ at the University of Vienna and is targeted at a non-specialist multi-disciplinary audience with an interest in the politics of technology. The lecture series explicitly invites the participation of students both from political science and from other disciplines.

The lecture will take place online via Zoom. (Linked provided on Moodle.)

Assessment and permitted materials

Digital written exam.

Students are assigned tasks to complete online (on Moodle) in open book format within a two-hour time slot. The net answering time is 90 minutes; 30 minutes are allocated to downloading and uploading the exam form. The exam is to be written in English.

Minimum requirements and assessment criteria

To pass the course, an exam must be taken at the end of term. The exam is based on a set of required readings (approximately, one text per session).

The exam assesses the ability of students to to both accurately describe the lecture contents and readings and provide one's own interpretation thereof. Students are required to independently establish connections between positions brought up throughout the lecture series.

All exam submissions are checked using the University of Vienna's plagiarism software (Turnitin). Answers copy-pasted from the lecture slides or the Internet, copying of texts without the corresponding bibliography or copying from other participants of the same exam will be detected and will be reported.

The independence of the submitted work might be checked in the form of an interview up to four weeks following the examination. Students are required to attend these appointments upon request.

Examination topics

Lecture readings, lecture slides, and oral presentations.

Reading list

Readings provided via Moodle.

Recommended readings:

• Latzer, M. & Just, N. (2020). Governance by and of Algorithms on the Internet: Impact and Consequences. Oxford Research Encyclopedia, Communication.

• Floridi, L., Cowls, J., King, T.C., & Taddeo, M. (2020). How to Design AI for Social Good: Seven Essential Factors. Sci. Eng. Ethics 26(3): 1771-1796.

• Fry, H. (2020). Hello World: Being Human in a World of Algorithms. Chapter: “Medicine”. S. 79-112.

• Conrad, P., & C. Stults (2010). “The Internet and the Experience of Illness.” In: Handbook of Medical Sociology, 6th ed., 179–91. Nashville: Vanderbilt University Press.

• Nunn, R. (2020). Discrimination in the Age of Algorithms. In W. Barfield (Ed.), The Cambridge Handbook of the Law of Algorithms (Cambridge Law Handbooks, pp. 182-198). Cambridge: Cambridge University Press.

• Leonelli, S. (2019). Data Governance is Key to Interpretation: Reconceptualizing Data in Data Science. Harvard Data Science Review, 1(1).

• Allhutter, D., Cech, F., Fischer, F., Grill, G. & Mager, A. (2020) “Algorithmic Profiling of Job Seekers in Austria: How Austerity Politics Are Made Effective”, Frontiers in Big Data.

• Manor, I. & Segev, E. (2020). Social Media Mobility: Leveraging Twitter Networks in Online Diplomacy. Global Policy. 11:2. p233-244.

• Gillespie, T. (2013). "The Relevance of Algorithms". In: Media Technologies: Essays on Communication, Materiality, and Society (Gillespie, T. & Boczkowski, P.J. & Foot, K.A., eds.). Cambridge: MIT Press. p. 167 - 193.

• Nowotny, Helga (2021). In AI We Trust: How the COVID-19 Pandemic Pushes us Deeper into Digitalization. Berlin: De Gruyter.

Association in the course directory

Last modified: Fr 12.05.2023 00:19