Further contributors:

• Jürgen Altmann (Dortmund): Expert reporting on the current state of military AI applications (confirmed)
• Selected further experts (e.g. from UNA Europa Network or from the emerging Berlin Ethics Lab)

Target group: Master’s students (Bachelor’s students from the fifth semester onwards)

Prerequisites: None

Block course format: The main part pf the seminar will be held in the form of a two week intensive block course (9:00-12:00 and 13:30--15:00) to be held from 14.-25. September. A mixture of lectures (including invited lectures by experts), student presentations and student projects/group work will be offered. The seminar includes an intensive preparation and postprocessing phase.

Student deliverables: Presentation (30 + 15 min), report (about 10 pages), further contributions depending on selected topic (surveys, programming, modeling, empirical studies), active participation in discussions

Description: Ethical and legal challenges in AI and Data science will be identified and options to resolve or control them will explored and discussed. The list of topics that will be addressed include:

• Introduction, survey and delineation on core notions, including "AI", "Data Science", "Machine Learning", "Ethics and Law in AI and Data Science"
• Survey and discussion of international positions and recommendations on ethical and legal regulation of AI and data science applications
• Clarification and discussion of relevant notions, including "Trustworthy AI", "Explainable AI", "Transparent AI"
• Elaboration of a spectrum of critical and non-critical applications of AI and data science technology
• Exemplary discussion of selected, critical application areas, including e.g. military applications, automated financial markets, criminal profiling, etc.
• Adversial attacks, and potential countermeasures
• Bias in data science and machine learning, and potential countermeasures
• Means to explain and assess decision making in data science and AI
• Means to enforce ethical and legal control in data science and machine learning
• Means to enforce ethical and legal control in large, integrated AI systems 
• Ethics and security