From ranking of news media and social media content to the communication via voice assistants and chat bots – algorithms are ubiquitous. Considering the huge potential of algorithms and artificial intelligence, business leaders and scholars need to attain a deeper understanding of chances and challenges of algorithms, as well as their multiple implications on consumers.

This course is designed to provide participants with a deeper understanding about the applications of AI and algorithms in consumer contexts and in behavioral research, as well as psychological mechanisms and ethical considerations that influence consumer experiences with AI and algorithms (e.g., experiences of data collection, classification, task delegation, decision making, social and communication).

Although we cover the theory of the technology of algorithms and AI (no coding required), the main focus is the application of algorithms and AI in consumer and marketing research and behavioral science more generally. The course will start with foundations and a definition of AI. It will then dive into different applications of AI in the consumer experience by analyzing and discussing cutting-edge research and practical examples. Based on this theoretical foundation and enriched by guest lectures, students will work on an own business problem or research question related to algorithms in marketing/consumer contexts and behavioral science.

In particular, in this course you will

1. acquire a fundamental overview of algorithmic applications in consumer research on the one hand, and insights into psychological mechanisms that drive consumer experiences with algorithms on the other hand. The course particularly draws on several psychological concepts and biases that explain how we perceive algorithms, and how algorithms change our ways of thinking, decision making, and behavior.
2. evaluate and discuss cutting-edge research articles in this timely domain. Students shall be ready to prepare and discuss current research articles as a discussion foundation for the course lecture.

apply the theoretical concepts to a relevant and current case in a group project. You will work together with international students on a self-selected case. The case can either be a specific research question or a concrete business problem related to the course topic. Either way, the question should be very specific (e.g., develop design principles for a service bot, or develop a solution for data collection concerns of a voice assistant). In a final session, you present your case, followed by a joint discussion. You are required to hand in a critical reflection of your group project as an essay after the course.

Participation in all sessions is mandatory. You may miss up to max. 20% of lecture hours, but please note that content is build-up in a modular way. Thus, absences should be minimized to ensure your optimal learning outcomes.

Your grade will be the sum of the following components (max. 100 points)

• Final project presentations: 40 pts
• Report and critical reflection of group project: 40 pts
• Peer evaluation of group work: 10 pts
• Participation in discussion during lectures: 10 pts

The project presentation is graded at group level, while the written group project is graded at the individual level. The peer review is used to assess the individual contribution of each group member to the group project.

Grades are as follows: 90 pts or more: 1 (= excellent), 80 pts or more: 2 (= good), 70 pts or more: 3 (=satisfactory), 60 pts or more: 4 (= sufficient), 59 pts or less: 5 (= fail).