Can a technology really be trustworthy or even responsible? Since the success of LLMs at the latest, this question has been increasingly asked in society. With the increasing use of artificial intelligence, terms such as "Trustworthy AI", "Responsible AI" or "Ethical AI" are therefore gaining in importance. But what exactly is behind them? Technology is only ever used by people for specific purposes. So if we want to "trust" an AI solution, we need to understand how the people and organizations involved develop AI responsibly. According to the European Commission's HLEG AI, trustworthy AI must be lawful, ethical and robust.

This lecture sheds light on all these areas and thus provides an answer to the question of what a responsible and thus sustainable approach to AI can look like. After an introduction to AI and data, various approaches will be discussed with which actions and technology applications can be morally evaluated. The aim of this ethical reflection is to find out what we should do with AI instead of limiting ourselves to what we can do with AI.

In the context of robustness, vulnerabilities of AI and measures to address them will be discussed. The lecture will cover other topics such as bias, adversarial attacks, transparency, privacy and human-computer interaction. Current developments in regulatory requirements at European level will also be discussed. Guest lectures and continuous insights into business practice complement the foundations laid.

After successfully completing the course, students should be able to:

• classify and evaluate the scientific discussion on ethics in artificial intelligence systems,
• understand the concept of trust and responsibility in the context of artificial intelligence and apply the relevant knowledge to change processes in companies, 
• shape the social and entrepreneurial discussion on the use of AI themselves and
• know the legal requirements for AI and implement them in the corporate context.

Die Vorlesung und die Übung wechseln sich im zweiwöchentlichen Rhythmus ab: In den Vorlesungswochen liegt die Veranstaltung von 15:45 – 19:00 Uhr (2 SWS), in den Übungswochen von 15:45 – 17:15 Uhr (1 SWS).

Die Übung findet planmäßig online statt.