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363-0311-00L 3 Credits DS , MSC , NDS D-MTEC , D-GESS

AI Implementation & Risk: The Human Factor

Lecturers & Examiners: PD Dr. Nadine Bienefeld-Seall
VVZ CR n/a

Last Updated: 2026-06-03 00:07:51

Abstract

Many AI initiatives fail because they neglect human factor-based risks from poor AI implementation and use. This course guides participants to integrate human-centered approaches and consider psychological aspects of risk management for safe and effective AI use. Students apply these insights to company case studies and, where applicable, their own workplace experiences, ensuring real-world impact

Objective

After taking this course, students will be able to: • Identify psychological factors in AI risk management. • Develop specific mitigation strategies for human factor-based risks from poor AI implementation and use. • Apply socio-technical system principles to enhance safe and responsible use of AI. • Integrate insights from case studies in high-reliability organizations, such as healthcare and aviation. • Transfer the learnings to one’s own or other company cases.

Content

Course Description This 3-day block course guides participants on how to integrate human-centered approaches and consider psychological aspects of risk management for safe and effective AI use. Through essential frameworks, hands-on methodologies, and real-world case discussions, students learn how to implement AI solutions based on organizational contexts and socio-technical system principles. By examining psychological factors such as trust, automation bias, overreliance, and potential deskilling, participants gain the skills to anticipate human factors risks and develop risk mitigation strategies. The ultimate objective is to promote responsible and safe use of AI. Target Group This course welcomes students from various backgrounds who aim to drive AI initiatives within their organizations. Participants should have a basic understanding of AI (e.g., machine learning and LLMs). No extensive coding skills are required. Students with roles in product development, R&D, or operations will gain particular value as they refine how to deploy AI safely and responsibly in real business environments. Expected Course Deliverables • Group Project: Students collaborate in teams (3-4 members) to tackle a real or fictional AI implementation project from their workplace, applying frameworks discussed in class to outline a strategic approach, socio-technical integration, and human-centered risk mitigation strategy. • Individual Reflection: A short-written paper (2-3 pages) where each participant connects key concepts to their own professional context. • Participation & Discussions: Active engagement in class exercises, case analyses, and peer feedback sessions. Final Assessment The course concludes with a group presentation and final project report, showcasing the human-centered risk mitigation strategy of the chosen AI implementation project, each evaluated according to criteria that emphasize both theoretical understanding and practical application.

Resources

Lecture Notes

There is no script, but slides will be made available before the lectures.

Literature

There are texts for each of the course topics made available before the lectures.

General Information

Language
English
Levels
DS , MSC , NDS
Frequency
Yearly recurring

Examination

Type
graded semester performance
Evaluation of student performance is based on two kinds of deliverables: a 60% weight is put on a team assignment, consisting of a short written report and an in-class presentation. An individual score is given for the completion of a short, written paper (2-3 pages) where each participant connects key concepts to their own professional or educational context (40% weight).

Registration & Places

Max Places
65
Signup End
23.09.2026

Course Components

Type Title Time & Place Hours
lecture AI Implementation & Risk: The Human Factor
Block course
No time listed 21 h semesterly

Offered In