Universität Wien
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040231 UK SOLV (2025S)

AI & Economics: Opportunities, Dangers and the future of decision making

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Prüfungsimmanente Lehrveranstaltung
VOR-ORT

Selbstorganisierte Lehrveranstaltung der Studienrichtungsvertretung VWL
Moodle
Mi 05.03. 16:45-18:15 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock

Details

max. 50 Teilnehmer*innen
Sprache: Englisch

Lehrende

    Termine (iCal) - nächster Termin ist mit N markiert

    • Mittwoch 19.03. 16:45 - 18:15 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
    • Mittwoch 26.03. 16:45 - 18:15 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
    • Mittwoch 02.04. 16:45 - 18:15 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
    • Mittwoch 09.04. 16:45 - 18:15 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
    • Mittwoch 30.04. 16:45 - 18:15 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
    • Mittwoch 07.05. 16:45 - 18:15 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
    • Mittwoch 14.05. 16:45 - 18:15 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
    • Mittwoch 21.05. 16:45 - 18:15 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
    • Mittwoch 28.05. 16:45 - 18:15 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
    • Mittwoch 04.06. 16:45 - 18:15 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
    • Mittwoch 11.06. 16:45 - 18:15 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
    • Mittwoch 18.06. 16:45 - 18:15 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
    • Mittwoch 25.06. 16:45 - 18:15 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock

    Information

    Ziele, Inhalte und Methode der Lehrveranstaltung

    The self-organized course (SOLV) is focused on the link between AI and Economics. This weekly course, complemented by lectures from external experts, aims to provide a comprehensive, interdisciplinary, and critical understanding of how artificial Intelligence changes the discourse. At the end of the course you will be familiar with the following topics:
    Technical introduction of AI (For Econ students)
    (Big) Data Analytics for Economic forecasting
    Ethics of AI: Inequality & Fairness
    Decision making & public policy
    Sustainability in AI
    Effects on the labor market
    Global Economic impact of AI
    Guest Lectures (Placeholder)

    Prerequisites:
    A foundational understanding of basic econometric models is essential to actively engage in this course.

    Especially useful if you plan on using AI in your Thesis/Seminar's

    Be aware: The SOLV will be conducted in English.

    About the SOLV:
    SOLV (Selbst Organisierte Lehrveranstaltung/Self-Organized Course) is part of a series organized by the Economics-Grassroots group, Roter Börsenkrach (www.roterboersenkrach.at). Designed to fill gaps in the traditional curriculum, SOLV puts the organization, choice of topics, and teaching responsibilities into the hands of dedicated students. If you are passionate about shaping the next SOLV, we encourage you to reach out to us at solv@roterboersenkrach.at.

    Art der Leistungskontrolle und erlaubte Hilfsmittel

    75% Practical Task & In-Class presentation -> Students will use AI in the practical task and are expected to deliver a group presentation (Graded individually!).
    15% Quiz
    10% Active participation

    Mindestanforderungen und Beurteilungsmaßstab

    weekly Attendance (max. 3 unexcused absences) is required.

    Grading Scale
    [86%; 100%]: 1.0
    [74%; 86%): 2.0
    [62%;74%): 3.0
    [50%; 62%): 4.0
    [0; 50%): 5.0

    Percentage Distribution:

    Task + Presentation (75%)
    Quiz (15%)
    Participation (10%)

    you will be able to get bonus points.

    Prüfungsstoff

    Task: You will engage in a task requiring the pracitcal use of AI and afterwards you will be able to present your findings in a group presentation. (No group grades but individual ones).
    Quiz: There will be a short quiz (tba) during the semester (15-20 min)
    Participation (especially guest lectures)

    Literatur

    Recommended but not mandatory readings will be announced in the lectures and on moodle. These are mostly journal articles and book chapters that are nontrivial to process and hence, not required to read.
    When, however, something is unclear please email me. I respond to your question asap and rediscuss the focal issue at the next class. Should it still be unclear, please ask for a personal appointment.

    Zuordnung im Vorlesungsverzeichnis

    Letzte Änderung: Mi 15.01.2025 14:46