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Semester | fall semester 2025 |
Course frequency | Irregular |
Lecturers | Ranjodh Singh Dhaliwal (ranjodhsingh.dhaliwal@unibas.ch, Assessor) |
Content | Generative AI is a form of artificial intelligence in which computer systems are used to generate text, images, sound, video, computer code, or other medial outputs based on prompts or other data provided to the computer. These systems—including, but not limited to, ChatGPT, Gemini, Claude, Midjourney, and DALL-E—have been evolving rapidly and have led to plenty of excitement, confusion, and fear. This course provides a sociocultural, politicoeconomic, and technical survey that helps understand and creatively/critically use a number of these tools, including through explorations in prompt engineering. The course will address a range of issues from across the humanities, social sciences, sciences, engineering, and the arts. The course is organized in 3 general phases. These phases are not entirely distinct but fuse into each other: 1. Introduction to computing (and AI) as a social and technological endeavor that can be studied from the perspective of various humanities and social scientific disciplines along with the scientific, technological, engineering, and organizational frameworks. 2. Using—largely critically and creatively—Generative AI tools via methods and practices such as prompt engineering with an aim towards thinking experimentally, in light of the many disparate socio-cultural perspectives. 3. Working towards integrating students' projects/skillsets that will demonstrate cumulative knowledge, skills, experiences, and perspectives gained over the course. |
Learning objectives | The goal of this course is to empower you with the skills and perspectives necessary to manage, use, critique, and explore generative AI tools. At the end of this course you should, at varied levels of expertise, be able to: a) Understand and articulate the sociocultural nature of computing, b) Describe and explain the key social and cultural issues in modern computing, c) Describe and explain some key evolutionary points in the history of modern computing with respect to AI, d) Understand the logic & processes under-girding generative AI systems, e) Produce a high-level explanation of how different computational approaches work to create generative AI including the processes and data involved, f) Be able to explain the computational and social strengths and weaknesses of different generative AI processes or products and the implications of those limits for its use/abuse/misuse, g) Understand, apply, critique, and explore the principles of prompt engineering, h) Conduct experiments and create reports about variations in prompt use for text, images, and/or sound, and be able to tie these empirical activities to the social, linguistic and cultural principles introduced earlier in the course, and i) Understand and articulate the major research questions around Generative AI across the humanities. |
Bibliography | All recommended literature will be provided in the class. |
Comments | While we are still working on determining the right technical infrastructure for this course and hope to mitigate or avoid it, it is possible (if not likely)—depending on the developments in this fast-moving space—that the students may have to personally acquire access to some of the state-of-the-art AI technologies. |
Admission requirements | Participation is limited. Priority will be given to students of Digital Humanities if the course is oversubscribed. |
Language of instruction | English |
Use of digital media | No specific media used |
Interval | Weekday | Time | Room |
---|---|---|---|
wöchentlich | Wednesday | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
Date | Time | Room |
---|---|---|
Wednesday 24.09.2025 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
Wednesday 01.10.2025 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
Wednesday 08.10.2025 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
Wednesday 15.10.2025 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
Wednesday 22.10.2025 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
Wednesday 29.10.2025 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
Wednesday 05.11.2025 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
Wednesday 12.11.2025 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
Wednesday 19.11.2025 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
Wednesday 26.11.2025 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
Wednesday 03.12.2025 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
Wednesday 10.12.2025 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
Wednesday 17.12.2025 | 10.15-12.00 | Kollegienhaus, Hörsaal 119 |
Modules |
Modul: Humanities and Social Science Coding (Master's degree subject: Digital Humanities) |
Assessment format | continuous assessment |
Assessment registration/deregistration | Reg.: course registration; dereg.: not required |
Repeat examination | no repeat examination |
Scale | Pass / Fail |
Repeated registration | as often as necessary |
Responsible faculty | Faculty of Humanities and Social Sciences, studadmin-philhist@unibas.ch |
Offered by | Digital Humanities Lab |