Artificial Intelligence Specialization
Artificial Intelligence: Theoretical Foundations and Speculative Ramifications
This is a specialization within the Philosophy MA degree programme.
The specialization introduces artificial intelligence’s philosophical, scientific, cultural, and political challenges. Beginning with the logical and cybernetic foundations of the project of automated cognition, courses introduce AI problematics from a transdisciplinary perspective, from the philosophical foundations of scientific modeling of thinking to psychoanalysis and the biopolitics of algorithms. The courses within the program provide a broad coverage of the current state of the AI/non-human cognition problem.
Instructors: Maksim Miroshnichenko PhD, Isabel Millar PhD, Martin Horsch PhD, Catherine Malabou PhD (Guest Professor), Keti Chukhrov (Guest Professor)
To obtain the concentration in Artificial Intelligence you must:
Successfully complete 5 courses in the philosophy programme (these may be any five courses)
Successfully complete 4 of the 5 courses listed below
Successfully complete either 1 elective course (in another concentration, for example, English Literature and Philosophy); or 1 independent study
You thus must successfully pass 10 courses in total. Upon completion of the concentration you will be certified in Artificial Intelligence by GCAS. You will receive a certificate in “Advanced Research in Artificial Intelligence”.
Length of Degree:
You can complete the MA in one year (full-time).
Cost:
The tuition investment is €6,000
Application Deadline:
Apply at any time. We are currently accepting applications.
Credits:
90 ECTS credits with MA thesis research, writing, and defending.
Prerequisites:
BA Degree or higher
Introduction to AI
Intelligence, Justice, and the Future: A Very Short Introduction to AI
This course will introduce the concept of artificial intelligence, its history, primary metaphors, and some ethical challenges of automation. The emergence of AI was preceded by specific technoscientific discourses, constructions, and inventions that developed an analogy between humans and computers. The seminars will address the similarities between the brain and computing machinery, the automation of governance and control, and the relevance of AI in designing a shared future.
Instructor: Maksim Miroshnichenko, PhD in Philosophy, Bauhaus-Universität Weimar
Advanced AI Seminar
AI, From Automated Care to Queer Futures
This advanced seminar will explore critical perspectives on artificial intelligence in culture and society. Focusing on cases from art, medicine, normativity, and utopia, it will show how the idea of automating intelligence penetrates deep levels of biopolitics and control. The seminar will focus on texts by philosophers, machine learning specialists, robot ethicists, artists, and art theorists reflecting on AI.
Instructor: Maksim Miroshnichenko, PhD in Philosophy, Bauhaus-Universität Weimar
Applied AI & Bioethics
AI, Cyborgs, and Cosmic Cognition: The Bioethics of Alterity
The seminar focuses on a wide range of metaphors, analogies, speculations, and conceptualizations of artificial intelligence as overcoming anthropocentrism. Drawing on concepts from biology, robotics, cybernetics, psychology, and philosophy, the course will discuss the problems of interaction and communication between humans and AI, especially in the context of cyborgization and the fusion of humans and machines. One of its main aims is to show the deep connections between ethics, cognition, and cosmology while thinking about speculative AI.
Instructor: Maksim Miroshnichenko, PhD in Philosophy, Bauhaus-Universität Weimar
Sex, AI and Psychoanalysis
This seminar will provide an introduction to the ‘Psychoanalysis of Artificial Intelligence’. Highlighting some of the key psychoanalytic concepts at stake and articulating their relationship to a more critical approach to intelligence, the body, thought and their simulation. We will interrogate the Lacanian notion of sexuation in relation to the idea of the ‘Singularity’ and the concept of enjoyment as a factor in the creation of AI. The seminar will approach the psychoanalytic challenges of AI in the shape of Kant’s four questions; What can we know? What should we do? What may we hope for? and What is man?
Instructor: Isabel Millar, PhD in Philosophy and Psychoanalysis, Kingston University
Applied ontology and knowledge representation for explainable modelling
This seminar will cover semantic technology with a focus on its practical use for modern explainable AI methods, where learning by deduction and induction are combined. The exploration of this field will be based on a critical discussion of common practices, and recommendations for good practice (FAIR principles, and going beyond the FAIR principles). Knowledge graph technology and methods for designing and aligning semantic artefacts, such as ontologies, will be introduced and connected to the logical-mathematical foundations. Dedicated logical formalisms for use in a knowledge-driven AI context, e.g., description logic and logic programming (such as answer set programming), will be presented and compared.
Instructor: Martin Thomas Horsch, Associate Professor in Data Science, NMBU, Ås, Norway