Introduction to Human - AI systems

Objectives

This course takes an interdisciplinary approach to address the opportunities, challenges, and risks associated with human-AI systems. AI is transforming the way humans and AI interact to co-learn, co-work, co-create, co-lead, etc. The aim of the course is to enable participants to develop an informed and critical understanding of the potential of AI to support learning, working, and democratic participation in society. Students will gain the ability to evaluate its strengths, limitations, and societal impact, fostering a nuanced perspective on its role in shaping the future.

Content

Students will gain a comprehensive overview of relevant perspectives on human-AI systems, including hybrid intelligence, ethical dilemmas, legal issues and practical use in different contexts. The course provides cross-disciplinary coverage of human-AI systems from technological, human-computer interaction, education, psychology, philosophy, sociology, and law perspectives.

Upon completion of the course, the student will have the following learning outcomes:

Knowledge

The student can:

• describe human - AI systems from various perspectives (multi-agent eco-systems, pedagogical, ethical, etc.) and contexts (co-learn, co-work, co-create, co-lead ...)
• explain the theoretical foundations underlying human-AI systems, including hybrid intelligence, human-AI interaction/collaboration ...
• recognise ethical, privacy, and legal considerations for human-AI systems

Skills

The student can:

• apply knowledge to the critiquing, evaluation, and implementation of AI for learning in various contexts
• discuss critical perspectives on human-AI systems
• carry out research on human-AI systems

General competencies

The student can:

• critically assess the role of Human-AI systems in various contexts