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| Semester | spring semester 2020 |
| Course frequency | Once only |
| Lecturers |
Bernice Simone Elger (b.elger@unibas.ch, Assessor)
Georg Starke (georg.starke@unibas.ch) |
| Content | The integration of machine learning-based programs into ordinary life raises important ethical questions on an individual and public level. Drawing on relevant case studies, this introductory course aims to improve your understanding of the underlying problems and further your ability to tackle them in real-life contexts. In particular, we will focus on three topics: 1) What does it mean for a program to be fair and how can we address obstacles to such fairness? 2) What levels of transparency and explainability can and should we expect of machine learning-based programs in socially relevant contexts? 3) Who can be held accountable for a program’s decisions, particularly if its inner workings are opaque to both designers and users? We will read recent papers proposing technical and non-technical solutions for these ethical challenges and discuss them critically. Evaluation will be ongoing, and participants will be required to present during one of the sessions. |
| Comments | The course is primarily intended for graduate students in computer science. Other interested students are welcome to join, but kindly asked to contact Georg Starke (georg.starke@unibas.ch) in advance. |
| Course application | Mona |
| Language of instruction | English |
| Use of digital media | No specific media used |
| Interval | Weekday | Time | Room |
|---|
No dates available. Please contact the lecturer.
| Modules |
Aufbaumodul (Teil C) (Transfakultäre Querschnittsprogramme im freien Kreditpunkte-Bereich) Aufbaumodul (Teil D) (Transfakultäre Querschnittsprogramme im freien Kreditpunkte-Bereich) Doctorate Biomedical Ethics: Recommendations (PhD subject: Biomedical Ethics) Doctorate Computer Science: Recommendations (PhD subject: Computer Science) Module: Applications of Distributed Systems (Master's Studies: Computer Science) Module: Applications of Machine Intelligence (Master's Studies: Computer Science) |
| Assessment format | continuous assessment |
| Assessment details | Individual presentations. |
| Assessment registration/deregistration | Reg.: course registration; dereg.: teaching staff |
| Repeat examination | no repeat examination |
| Scale | Pass / Fail |
| Repeated registration | no repetition |
| Responsible faculty | Faculty of Medicine |
| Offered by | Institut für Bio- und Medizinethik |