Decision Making in a Social World
General data
Course ID: | 3500-FAKANG-DMSW |
Erasmus code / ISCED: |
14.2
|
Course title: | Decision Making in a Social World |
Name in Polish: | Decision Making in a Social World |
Organizational unit: | Faculty of Sociology |
Course groups: | |
ECTS credit allocation (and other scores): |
5.00
|
Language: | English |
Type of course: | foreign languages |
Prerequisites (description): | (in Polish) While the mathematical apparatus will be kept minimal, readiness to deal with very abstract constructs in a formal way will be needed. |
Mode: | Classroom |
Short description: |
(in Polish) This course concentrates on how people make judgments and decisions in a complex social environment where information is often scarce and uncertain, but sometimes also overwhelmingly abundant. We will be exploring how the process of decision making is being described by different disciplines: psychology, economics and sociology. We will discuss how we can use these different inputs to understand better both why individuals make decisions in certain ways (for example relying on social learning and social norms) and how social reality is shaped. Specifically, we will: ● Take a closer look at what is rationality in decision making and talk about bounded rationality and simple heuristics ● Show how the environment can shape choices in decision making processes and the other way around ● Introduce a computational approach to cognitive processes and behavioural theories using some prominent examples. ● Reflect on the use of empirical data in social modelling for decision making. |
Full description: |
(in Polish) Climate change, loss of bio-diversity, managing a pandemic, these are all problems we face as humanity that require an adaptation of our behaviour and the choices that we make. Many policies are developed to support such behavioural changes, for example the taxation of fossil fuel, informing us about the state of nature and legislation on wearing masks and social distancing. Increasingly, models are being used to forecast the impact of policy. And obviously, these models are based on assumptions on human behaviour. Since economics has always been a discipline where formal models were being used, many policy models are based on assumptions of economic rationality of the people. However, there are many reasons to believe that we do not behave as optimisers. Instead, we have habits, learn from others and are often satisfied with “good enough” choices. These mechanisms have serious impacts on the efficiency of social policies. To design better social interventions we need to reflect on how we as humans make decisions. This course concentrates on how people make judgments and decisions in a complex social environment where information is often scarce and uncertain, but sometimes also overwhelmingly abundant. We will be exploring how the process of decision making is being described by different disciplines: psychology, economics and sociology. We will discuss how we can use these different inputs to understand better both why individuals make decisions in certain ways (for example relying on social learning and social norms) and how social reality is shaped. Specifically, we will: ● Take a closer look at what is rationality in decision making and talk about bounded rationality and simple heuristics ● Show how the environment can shape choices in decision making processes and the other way around ● Introduce a computational approach to cognitive processes and behavioural theories using some prominent examples. ● Reflect on the use of empirical data in social modelling for decision making. |
Bibliography: |
(in Polish) Bendor, Jonathan, Swistak, Piotr. 2004. The rational foundations of social institutions. W: J. Berg, Nathan, Abramczuk K., Hoffrage U. 2010. Fast Acceptance by Common Experience: FACE-recognition in Schelling’s model of neighborhood segregation. “Judgment and Decision Making” 5(5): 391-410. Coleman, James S. 1986. Social theory, social research, and a theory of action. “American Journal of Sociology” 91: 1309-35. Gigerenzer, Gerd, Gaissmaier, W. 2011. Heuristic decision making. “Annual review of psychology” 62: 451-482. Henrich, Joseph, Robert Boyd, Samuel Bowles, Colin Camerer, Ernst Fehr, Herbert Gintis, and Richard McElreath. 2001. "In Search of Homo Economicus: Behavioral Experiments in 15 Small-Scale Societies." American Economic Review, 91 (2): 73-78. Kahneman, Daniel. 2003, Maps of bounded rationality: Psychology for Behavioral Economics. “The American Economic Review” 93(5): 1449-1475. Simon, Herbert A. 1990. Invariants of Human Behaviour. “Annual Review of Psychology” 41: 1-19. Schwarz, N., Dressler, G., Frank, K., Jager, W., Janssen, M., Müller, B., ... & Groeneveld, J. (2020). Formalising theories of human decision-making for agent-based modelling of social-ecological systems: practical lessons learned and ways forward. Socio-Environmental Systems Modelling, 2, 16340-16340. Straffin Jr, P. D. (1993). Game theory and strategy (Vol. 36). MAA. Wilkinson, N. (2007). „An Introduction to Behavioral Economics: A Guide for Students.” Palgrave Macmillan. |
Learning outcomes: |
(in Polish) K_W03 Is aware of ongoing theoretical and methodological disputes conducted in modern sociology; is reflective and critical of various positions K_W27 Has in-depth knowledge of the 19th, 20th and 21st ideas and social processes which have shaped the face of the modern world K_U04 Can critically select information and materials for academic work, using various sources in Polish and a foreign language as well as modern technologies K_U17 Can relate an academic text to the problems of social life and its empirical studies K_U18 Can identify the kinds of research in which the scientific texts read can be applicable K_K01 Can initiate, plan, organize and manage work of a task team K_K02 Can propose a solution to a problem that requires an interdisciplinary research approach K_K05 Can gather, find, synthesize and critically assess information about social sciences K_K14 Takes responsibility for planned and performed tasks |
Assessment methods and assessment criteria: |
(in Polish) Permanent evaluation of student engagement in discussions during the course. Small group tasks assigned during the course. Final test checking understanding of the core concepts and problems. |
Classes in period "Winter semester 2023/24" (past)
Time span: | 2023-10-01 - 2024-01-28 |
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MO TU KON
W TH FR |
Type of class: |
Seminar, 40 hours, 15 places
|
|
Coordinators: | Katarzyna Abramczuk | |
Group instructors: | Katarzyna Abramczuk | |
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 |
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MO TU W TH FR |
Type of class: |
Seminar, 30 hours
|
|
Coordinators: | Katarzyna Abramczuk | |
Group instructors: | Katarzyna Abramczuk | |
Students list: | (inaccessible to you) | |
Examination: |
Course -
Grading
Seminar - Grading |
Copyright by University of Warsaw.