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77512-01 - Seminar: Generative AI in Social Science Research (3 KP)
| Semester | Herbstsemester 2025 |
| Angebotsmuster | unregelmässig |
| Dozierende | Johanna Einsiedler (johanna.einsiedler@unibas.ch, BeurteilerIn) |
| Inhalt | This course will cover new developments on the usage of generative AI - particularly large language models (LLMs) - as tools in social science research. Drawing on recent empirical studies, we examine how LLMs are used across the research pipeline: as tools for hypothesis generation, synthetic survey respondents, qualitative interviewers, behavioral simulation agents, causal inference assistants, and tools for text analysis. We will critically assess both the methodological potential and ethical challenges these tools pose, and engage hands-on with current frameworks, experiments, and applications. Through structured discussions and active experimentation, students will explore how LLMs can enhance, reshape, or challenge traditional empirical methods in the social sciences. The seminar will be a mixture of discussion and experimentation. Students will be expected to read literature, lead discussions and develop their own research plans. Use of generative AI is encouraged. No prior coding experience is required. Familiarity with core social science research concepts such as surveys, experiments and observational data analysis is heavily recommended. A basic understanding of inferential statistics is also preferred. |
| Lernziele | Students will learn to critically evaluate the use of generative AI tools in social science research, identifying their strengths, limitations, and appropriate applications. Students will gain practical experience designing and analyzing studies that integrate large language models into the research process. This course has a learning-by-doing format. Students must bring their own laptops to the course. Only three absences are permitted; medical attestation is required for further absences. |
| Literatur | Bail, C. A. (2024). Can generative AI improve social science? Proceedings of the National Academy of Sciences, 121(21), e2314021121. https://doi.org/10.1073/pnas.2314021121 Research articles will be provided for every session. |
| Teilnahmevoraussetzungen | Participation is limited. Priority will be given to students of Digital Humanities if the course is oversubscribed. |
| Unterrichtssprache | Englisch |
| Einsatz digitaler Medien | kein spezifischer Einsatz |
| Intervall | Wochentag | Zeit | Raum |
|---|---|---|---|
| wöchentlich | Montag | 14.15-16.00 | Kollegienhaus, Seminarraum 106 |
Einzeltermine
| Datum | Zeit | Raum |
|---|---|---|
| Montag 22.09.2025 | 14.15-16.00 Uhr | Kollegienhaus, Seminarraum 106 |
| Montag 29.09.2025 | 14.15-16.00 Uhr | Kollegienhaus, Seminarraum 106 |
| Montag 06.10.2025 | 14.15-16.00 Uhr | Kollegienhaus, Seminarraum 106 |
| Montag 13.10.2025 | 14.15-16.00 Uhr | Kollegienhaus, Seminarraum 106 |
| Montag 20.10.2025 | 14.15-16.00 Uhr | Kollegienhaus, Seminarraum 106 |
| Montag 27.10.2025 | 14.15-16.00 Uhr | Kollegienhaus, Seminarraum 106 |
| Montag 03.11.2025 | 14.15-16.00 Uhr | Kollegienhaus, Seminarraum 106 |
| Montag 10.11.2025 | 14.15-16.00 Uhr | Kollegienhaus, Seminarraum 106 |
| Montag 17.11.2025 | 14.15-16.00 Uhr | Kollegienhaus, Seminarraum 106 |
| Montag 24.11.2025 | 14.15-16.00 Uhr | Kollegienhaus, Seminarraum 106 |
| Montag 01.12.2025 | 14.15-16.00 Uhr | Kollegienhaus, Seminarraum 106 |
| Montag 08.12.2025 | 14.15-16.00 Uhr | Kollegienhaus, Seminarraum 107 |
| Montag 15.12.2025 | 14.15-16.00 Uhr | Kollegienhaus, Seminarraum 106 |
| Module |
Europäische Geschichte in globaler Perspektive (Masterstudium - Philosophisch-Historische Fakultät) Modul: Digital Humanities, Culture and Society (Master Studienfach: Digital Humanities) Modul: Forschung und Praxis (Master Studienfach: Osteuropäische Geschichte) Wahlbereich Bachelor Geschichte: Empfehlungen (Bachelor Studienfach: Geschichte) Wahlbereich Master Geschichte: Empfehlungen (Master Studienfach: Geschichte) |
| Prüfung | Lehrveranst.-begleitend |
| An-/Abmeldung zur Prüfung | Anmelden: Belegen; Abmelden: nicht erforderlich |
| Wiederholungsprüfung | keine Wiederholungsprüfung |
| Skala | Pass / Fail |
| Belegen bei Nichtbestehen | beliebig wiederholbar |
| Zuständige Fakultät | Philosophisch-Historische Fakultät, studadmin-philhist@unibas.ch |
| Anbietende Organisationseinheit | Digital Humanities Lab |