Class Computational Thinking

This Curricular Unit intends to offer students a perspective on the evolution of technology, demystify it and how its influencing modern day cinema. This unit intends to be primarily philosophical in nature, offering insight on the inner workings of technology without being too technical. Furthermore, this unit intends to push students to think critically, report and research about different topics that are currently changing the art of cinema, and push students to openly discuss these changes in class with their colleagues, debating on its influence on their art.

1. Module 1 - Virtual Production
   1. The Virtual Playground
   2. Extended Reality for Movie-Making
   3. The Age of Synthetic Cinema
   4. Debate and Presentations
2. Module 2 - Machine Creativity
   1. Machine Creativity and Mixed-Initiative Co-Creation
   2. Procedural Content Generation: Building Worlds at a push of a button
   3. Debate and Presentations
3. Module 3 - Profiling and Data-Driven Systems
   1. The Rise of Streaming
   2. A Data-Driven Production Decision: Netflix and Profiling
   3. How far is too far? - The Ethics of AI Systems in Data Driven Approaches
   4. Debate and Presentations
4. Module 4 - Final Discussions and Reports

The subject is taught with an alternation between the following methods:

• Expository, in the presentation of the concepts.
• Demonstrative, in the demonstration of concepts through examples.
• Participative, in the form of presentations and discussions of the concepts presented.
• By research, so that students can independently learn some of the proposed concepts.

Evaluation is carried out as follows:

• Several presentations throughout the semester on topics chosen by the students
• Participation in class and in discussions on the various topics
• Writing of a short report on a topic chosen by the student

• Kadner, Noah - The Virtual Production Field Guide: Volume 1. Published by Epic Games, 2019
• Kadner, Noah - The Virtual Production Field Guide: Volume 2. Published by Epic Games, 2021
• Yannakakis, G. N., Spronck, P., Loiacono, D., & Andre, E. (2013). Player modeling. In S. M.
• Lucas, M. Mateas, M. Preuss, P. Spronck, & J. Togelius (Eds.), Artificial and computational intelligence in games, DFU, 6 (pp.45-59). Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik.
• Yannakakis, G. N., & Togelius, J. (2018). Artificial intelligence and games (Vol. 2, pp. 2475-1502). New York: Springer.
• El-Nasr, M. S., Nguyen, T. H. D., Canossa, A., & Drachen, A. (2021). Game data science. Oxford University Press.