Algorithms and surveillance society
General data
Course ID: | 3500-SCC-asn |
Erasmus code / ISCED: |
14.2
|
Course title: | Algorithms and surveillance society |
Name in Polish: | Algorytmy i społeczeństwo nadzoru |
Organizational unit: | Faculty of Sociology |
Course groups: | |
ECTS credit allocation (and other scores): |
6.00
|
Language: | Polish |
Type of course: | obligatory courses |
Prerequisites (description): | (in Polish) Konieczna znajomość angielskiego umożliwiająca czytanie tekstów w języku angielskim |
Mode: | Classroom |
Short description: |
Algorithms are everywhere and when they work well we usually do not notice them. They are used among others to assess creditworthiness, assess job candidates, target ads, or prevent terrorist attacks. They are so common because the allow to simplify complex phenomena and process huge amounts of data, which facilitates decision making. In spite of appearances, these are not neutral and objective tools that only improve the management of complex problems. The aim of the course is to look at how algorithms are created, how they work, and what are the social and political consequences of their application. The focus will be on revealing the normative assumptions that underlie the selected algorithms. We will also focus on the threats they generate: strengthening inequalities, hampering democratic control of political processes, and interference with privacy. |
Full description: |
Algorithms are everywhere and when they work well we usually don't notice them. They are used, among others to assess creditworthiness, assess job candidates, target ads, or prevent terrorist attacks. They are so common because the allow to simplify complex phenomena and process huge amounts of data, which facilitates decision making. In spite of appearances, these are not neutral and objective tools that only improve the management of complex problems - many normative choices are made in the course of their design, and their use also has numerous negative social and political effects. The aim of the course is to look at how algorithms are created, how they work, and what are the social and political consequences of their application. The focus will be on revealing the normative assumptions that underlie the selected algorithms. We will also focus on the threats they generate: strengthening inequalities, hampering democratic control of political processes, and interference with privacy. The classes will also aim at familiarizing students with the key theoretical texts on the issues of supervision and control (including technology-related supervision) and the identification and categorization of individuals, i.e. how the collection of data about individuals is used to "sort them out” into better and worse (better and worse citizens, customers, employees). During the classes, we will analyze selected cases of using algorithm-based technologies, reflecting on broader issues such as privacy boundaries, dehumanization of decision-making processes, the weakness of democratic mechanisms when faced with the new supervision technologies, etc. Our primary interest will be the scoring systems (credit scoring and prediction models), profiling systems (crime profiling, migrant profiling, profiling of the unemployed) and other automated systems for classifying and assessing individuals (e.g. automated human resource management and employee assessments). We will reflect on the normative assumptions and value judgements about individuals (citizens, customers, employees) that underlie these systems and the social and political consequences of their use. We will use a variety of sources for analysis: scientific literature, watchdog reports, media publications, and documentaries. |
Bibliography: |
Bowker, G. C. & Star, S. L. (1999) Sorting things out: classification and its consequences, MIT Press, Cambridge, Mass. Bovens, M., Zouridis, S. (2002) From Street-Level to System-Level Bureaucracies: How Information and Communication Technology is Transforming Administrative Discretion and Constitutional Control, Public Administration Review, Vol. 62, No. 2, pp. 174-184. Citron D.K, Pasqualle F. (2014) The Scored Society: Due Process for Automated Predictions, University of Maryland Francis King Carey School of Law Legal Studies Research Paper No. 2014 – 8. Collingridge, D., and Reeve, C. (1986). Science Speaks to Power: The Role of Experts in Policy Making. New York: St. Martin’s Press Foucault, M. (1998) Nadzorować i karać: narodziny więzienia. (Warszawa: Fundacja Aletheia). Garfinkel, S. (2001) Database Nation: The Death of Privacy in the 21st Century. Cambridge, MA: O’Reilly. Gilliom, J. (2001) Overseers of the poor: surveillance, resistance, and the limits of privacy, University of Chicago Press, Chicago. Hacking, I. (1986), Making Up People, in Heller, Sosna, and Wellbery (eds), Reconstructing Individualism: Autonomy, Individuality, and the Self in Western Thought, Stanford: Stanford University Press, pp. 222-236. Lyon, D. (1994) The Electronic Eye: The Rise of Surveillance Society. Cambridge, MA: Polity Press. Lyon, D. (ed.) (2006) Theorizing Surveillance: The Panopticon and Beyond. Cullompton, UK: Willan. Lyon D. (2015) ‘Citizenfour Alert!’ and ‘Snowden Storm’ in Surveillance After Snowden Niklas, J., Sztandar-Sztanderska, K. & Szymielewicz, K. (2015) Profiling the Unemployed in Poland. Social and Political Implications of Algorithmic Decision Making. Warszawa, Panoptykon Foundation. O’Neil, Cathy 2017 Broń matematycznej zagłady: jak algorytmy zwiększają nierówności i zagrażają demokracji. Marcin Z Zieliński, tran. Warszawa: Państwowe Wydawnictwo Naukowe PWN Scheiner B. (2015) Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World, New York: W. W. Norton & Company. Scott, J. C. (1998) Seeing like a state: how certain schemes to improve the human condition have failed, Yale University Press, New Haven, dobrać fragment. Szadkowski K. (2015) Uniwersytet jako dobro wspólne. Warszawa: Scholar Whitaker, R. (1999) The End of Privacy: How Total Surveillance is Becoming a Reality. New York: The New Press |
Learning outcomes: |
(in Polish) K_W04 rozumie szczególny charakter zmian zachodzących we współczesnych społeczeństwach w związku z rozwojem nowych technologii K_W06 rozumienie zagrożenia wynikającego z używania nowych technologii i wykorzystywania dużych zbiorów danych K_W10 posiada pogłębioną wiedzę na temat najważniejszych międzynarodowych i krajowych badań socjologicznych odnoszących się do technologii informacyjnych i algorytmów K_W11 posiada pogłębioną wiedzę o technologiach informacyjnych i algorytmach jako narzędziach odpowiedzialnych za transmisję norm i reguł w społeczeństwie K_U06 potrafi posługiwać się kategoriami teoretycznymi do opisu i analizy procesów zachodzących we współczesnych społeczeństwach K_U10 potrafi dokonać krytycznej i refleksyjnej analizy konsekwencji zastosowania technologii informacyjnych i algorytmów we współczesnych społeczeństwach K_K01 jest świadom dylematów etycznych związanych z wykorzystaniem danych cyfrowych K_K02 potrafi dokonać krytycznej analizy procesów społecznych zachodzących w środowisku cyfrowym |
Assessment methods and assessment criteria: |
The basis for getting credit is attendance (2 absences are allowed). The grade is based on activity and class work + completion of tasks (40% of the grade), preparation of a presentation about a selected technology (60% of the grade). Presentations will be commented on by invited guests - researchers or practitioners who specialize in particular topics. |
Classes in period "Winter semester 2023/24" (past)
Time span: | 2023-10-01 - 2024-01-28 |
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MO KON
KON
TU W TH FR |
Type of class: |
Seminar, 45 hours, 30 places
|
|
Coordinators: | Marianna Zieleńska | |
Group instructors: | Marianna Zieleńska | |
Students list: | (inaccessible to you) | |
Examination: |
Course -
Grading
Seminar - Grading |
Classes in period "Winter semester 2024/25" (future)
Time span: | 2024-10-01 - 2025-01-26 |
Navigate to timetable
MO TU W TH FR |
Type of class: |
Seminar, 45 hours
|
|
Coordinators: | Marianna Zieleńska | |
Group instructors: | Marianna Zieleńska | |
Students list: | (inaccessible to you) | |
Examination: |
Course -
Grading
Seminar - Grading |
Copyright by University of Warsaw.