inf1212 - Designing Explainable Artificial Intelligence (Complete module description)

Module label	Designing Explainable Artificial Intelligence
Module code	inf1212
Credit points	6.0 KP
Workload	180 h
Institute directory	Department of Computing Science
Applicability of the module	Master's Programme Computing Science (Master) > Praktische Informatik
Responsible persons	Sonntag, Daniel (module responsibility) Lehrenden, Die im Modul (authorised to take exams)
Prerequisites	Basic knowledge in Artificial Intelligence/Machine Learning Interest in the scientific development and evaluation of IT artifacts, which goes hand in hand with literature work Willingness to deal with qualitative and/or quantitative evaluation methods Interest in prototyping Recommended prior knowledge: Basic knowledge of artificial intelligence and/or relevant programming skills (e.g., Python) Familiarity with software for the design of prototypical information systems (e.g., for user interfaces)
Skills to be acquired in this module	Become acquainted with the research field of Explainable Artificial Intelligence (XAI) Become acquainted with different methods and techniques from the field of Explainable Artificial Intelligence (XAI) as well as their characteristics Hands-on experience creating XAI systems Professional competence The students: identify the basic concepts of Explainable Artificial Intelligence (XAI) Methological competence The students: apply different methods and techniques from the field of Explainable artificial Intelligence (XAI) and recognize their characteristics Social competence The students: present their solutions to the group discuss with each other different solution approaches to a given problem review and discuss relevant literature Self competence The students: acknowledge the limits of their ability to cope with approaching assignment deadlines reflect on the limits of their ability to structure their project workload
Module contents	This course combines theoretical foundations from the field of Explainable Artificial Intelligence (XAI) with practical implementations for real-world problems. This includes: communicating the status quo on the topic of Explainable Artificial Intelligence (XAI) and relevant use cases, stakeholders and research opportunities instantiating possible solutions using qualitative and/or quantitative research methods for the evaluation of possible solutions working on (inter)disciplinary questions with high relevance for research and practice
Recommended reading
Links
Language of instruction	English
Duration (semesters)	1 Semester
Module frequency	every summer term
Module capacity	unlimited
Teaching/Learning method	V+Ü

Type of course	SWS	Frequency	Workload of compulsory attendance
Lecture	2	SuSe or WiSe	28
Seminar	2	SuSe or WiSe	28
Total module attendance time			56 h

Examination	Prüfungszeiten	Type of examination
Final exam of module	at the end of the lecture period	practical work or term paper