Data & AI Ethics

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Data & AI Ethics

Delve into the course contents and find out about the faculty members.

Course Description

Data Science is powerful, but with this power comes a host of obligations and responsibilities that professionals in this field need to be aware of, and to behave and decide in an ethical manner. As “big data” gets bigger and bigger, and applications of data science and artificial intelligence permeate a wider and wider range of different aspects of our lives, new and important ethical issues are arising all the time. This course is about ethics related to data, artificial intelligence and data science and provides you with the opportunity to clarify ethical issues and ambiguities when dealing with data and artificial intelligence. Building on ethics shared values that help distinguish right from wrong. Through this course, you will learn who owns data, how we value different aspects of privacy, how to obtain informed consent, and what it means to develop sustainable and fair algorithms to be used for decision making.

Course Objectives:
The aim of the course is to provide participants with frameworks to discuss and analyze ethical issues, algorithmic challenges, and managerial decisions that arise when addressing business problems via the lens of data science and artificial intelligence. The objectives of the course are therefore as follows:

  • Develop fluency in the key ethical terms and concepts related to data science;
  • Learn about algorithmic and data-driven approaches for mitigating biases in AI/ML systems;
  • Reason through problems with no clear answer in a systematic manner, taking and defending different viewpoints, and justifying your conclusions in a rigorous manner;
  • Listen, understand and communicate with people of varying opinions, viewpoints, and ideas. Disagreement and debate is expected, as is respectful open communication.

Optional tutorials included:

  • Data Science With R
  • Data Science With Python



Prof. Dr. Florian Stahl

Academic Director for the Mannheim Master in Management Analytics, Chair holder Quantitative Marketing and Consumer Analytics at the University of Mannheim

Researched / taught previously at:
Florian Stahl earned a Master's Degree in Economics from the University of Zürich (Switzerland) in 2001 and a PhD in Business Economics in 2005 from the University of St. Gallen (Switzerland). Between 2005 and 2008, he was a postdoctoral research fellow at Columbia Business School in New York. Before joining the University of Mannheim faculty of business administration in 2013, he was an Assistant and Associate professor (with tenure) of Quantitative Marketing at the Department of Business Administration of University of Zürich.

Fields of interests / research areas:
Florian Stahl's research interests are primarily in empirical quantitative marketing, business economics and information systems research. Specifically, his research addresses business related questions of the digital economy and, in particular, of online social networks and social media. Methodically his research is based on empirical modeling, applied econometrics, Bayesian modeling and experimental studies (laboratory as well as field experiments). The results of Florian Stahl's research have been published in top-tier journals such as Journal of Marketing or Journal of Marketing Research and won the 2012 H. Paul Root Award and the 2012 Robert D. Buzzell / Marketing Science Institute Best Paper Award.

Most recently in Journal of Research in Marketing, Journal of Marketing and International Journal of Research in Marketing


Located in the heart of the German and European economy, Mannheim Business School (MBS), the umbrella organization for management education at the University of Mannheim, is considered to be one of the leading institutions of its kind in Germany and is continuously ranked as Germany’s #1.