The Minor in "A Critical Approach to AI-Aided Decision Making" offers students a comprehensive exploration of the intersection between artificial intelligence (AI) technologies and decision-making processes in various domains. Through a blend of theoretical insights and practical applications, students will develop the critical thinking skills necessary to navigate the complexities of AI-driven decision-making landscapes.

Minor content

Critical Thinking: This module equips students with the foundational skills required to analyze and evaluate information critically. Through engaging coursework and interactive exercises, students will learn to identify biases, recognize logical fallacies, and assess the reliability of sources. They will also explore strategies for synthesizing diverse perspectives and forming well-reasoned arguments—an essential skill set for navigating the ethical and social implications of AI technologies.

Business Analytics: In this module, students delve into the principles of business analytics and data-driven decision making. Through hands-on projects and case studies, students will learn how to collect, analyze, and interpret data to inform strategic decision-making processes. They will also explore the role of AI algorithms and machine learning techniques in extracting insights from large datasets, enabling them to leverage data-driven approaches effectively in real-world scenarios.

Generative AI: This module introduces students to the exciting field of generative AI, where algorithms are used to create new content, such as images, text, and music. Through practical workshops and experimentation with state-of-the-art AI tools, students will explore the creative potential of generative AI technologies. They will examine ethical considerations surrounding AI-generated content, including issues related to intellectual property, bias, and privacy, fostering a critical understanding of the opportunities and challenges inherent in AI creativity.

This minor is offered by International Business.

Structure of the minor

• Develop critical thinking skills for analyzing and evaluating information in the context of AI-aided decision making.
• Understand the principles of business analytics and data-driven decision making, including the role of AI algorithms.
• Gain practical experience with generative AI technologies and their ethical implications.
• Apply multidisciplinary knowledge to address complex challenges in AI-augmented decision making.

This minor consists of 2 parts that can also be taken separately:

• Minor Critical Thinking and Statistics (P1)
• Minor Decision Making and Generative AI (P2)

This minor is accessible for a maximum of 30 students who obtained a propaedeutic degree or comparable from a Bachelor's program and have a good command of English (at least CEFR level B2 level).

• Critical Reflections and Essays: Critical reflections and essays provide opportunities for students to engage in critical thinking and analytical writing. Students may be asked to reflect on ethical dilemmas, evaluate research findings, or analyze case studies from a multidisciplinary perspective.
• Assignments and Projects: Assignments and projects provide opportunities for students to apply their knowledge and skills in practical scenarios. These may include case studies, data analysis tasks, coding assignments, or research projects related to AI-driven decision making.
• Presentations: Students may be required to deliver presentations to demonstrate their understanding of key concepts, findings from projects, or critical analyses of case studies. Presentations encourage students to articulate their ideas effectively and engage in peer-to-peer learning.