This course should provide an overview of the developments in artificial intelligence (AI) and how AI will transform industries as we know them.

The main goal of this course is to equip students with foundational knowledge concerning the AI technologies available today and how industries are leveraging them to enhance productivity as well as improve their underlying business models. We will also touch upon the major business and societal risks involved and how to mitigate them. Finally, we will work through selected topic areas and discuss example use cases to ensure an in-depth understanding of the capabilities of AI.

After successfully completing the Transformation through AI Zone, students will be able to:

• Understand the developments on AI until today
• Gain a better understanding of business impact related to AI
• Understand the underlying AI technologies
• Understand risks associated with AI

Students must attend at least 80% of all classes and events to successfully complete the course.

The appointment on November 8th is an optional coaching session. 

We strive to use a variety of learning methods:

• Expert lecturer
• Group exercises
• In-class discussions

30% Presentation (group grade, peer evaluation)

30% Final Essay (individual grade)

30% Active Participation (individual grade)

10% Reflection Reel (individual grade)

Please log in with your WU account to use all functionalities of read!t. For off-campus access to our licensed electronic resources, remember to activate your VPN connection connection. In case you encounter any technical problems or have questions regarding read!t, please feel free to contact the library at readinglists@wu.ac.at.

https://hbr.org/2024/05/transformations-that-work   

https://hbr.org/2023/08/ai-wont-replace-humans-but-humans-with-ai-will-replace-humans-without-ai 

https://www.ll.mit.edu/sites/default/files/publication/doc/2021-03/Artificial%20Intelligence%20Short%20History%2C%20Present%20Developments%2C%20and%20Future%20Outlook%20-%20Final%20Report%20-%202021-03-16_0.pdf

https://web.mit.edu/dxh/www/marvin/web.media.mit.edu/~minsky/papers/steps.html

https://academic.oup.com/mind/article/LIX/236/433/986238

https://web.mit.edu/6.034/www/6.s966/dendral-history.pdf

https://www.mckinsey.com/featured-insights/mckinsey-explainers/whats-the-future-of-ai

https://www.alexanderthamm.com/en/blog/an-introduction-to-large-language-models/

https://www.mckinsey.com/featured-insights/mckinsey-explainers/what-is-generative-ai

https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier#business-value

https://arxiv.org/ftp/arxiv/papers/1802/1802.07228.pdf

https://aiindex.stanford.edu/report/

https://plato.stanford.edu/entries/ethics-ai/