Description

The founding fathers of artificial intelligence viewed the mind as an information-processing
machine that can be understood, modeled, and replicated. This computer metaphor of the brain had
a profound influence not only on AI algorithms, but also on the study of the mind. In the previous
five decades the so-called cognitive science emerged as an interdisciplinary field operating at the
intersection of artificial intelligence, psychology, linguistics, neuroscience and philosophy. Its aim
is to advance our understanding of, for example, how we think and feel, how we make complex
decisions, and how we assess our experiences and learn from mistakes. In the age of hyped AI
dreams and nightmares, it is more important than ever to study the mechanisms that underlie human
cognition and emotion in order to reflect in a scientific way on the potentials and limits of artificial
intelligence. In this course we will discuss topics as diverse as the mathematics of intuition,
emotional intelligence, the relationship between language and intelligence, embodiment and
consciousness, as well as modelling complex motives.
The instructors come from different academic backgrounds that cover various aspects of cognitive
science. Thus, this course should be accessible not only to computer science, but also to
psychology, linguistics, neuroscience and philosophy students.

Suggested reading

• Baars, B. (1989). A cognitive theory of consciousness. Cambridge, Mass.: Cambridge University Press.
• Bermúdez, J. (2014). Cognitive Science: An Introduction to the Science of the Mind. 2nd ed.
• Cambridge: Cambridge Univ. Press.
• Chalmers, D. J. (1996). The Conscious Mind: In Search of a Fundamental Theory. New York, Oxford: Oxford University Press
• Damasio, A. (2005). Descartes' Error: Emotion, Reason, and the Human Brain. New York: Penguin Books.
• Dennett, D. 1991. Consciousness Explained. Little, Brown
• Dennett, D. (1996). Kinds of minds: towards an understanding of consciousness. London: Weidenfeld and Nicholson.
• Donald M, Origin of the Modern Mind, Harvard University Press, Cambridge, 1991.
• Dörner, D. (2001). Bauplan für eine Seele. Zweite Auflage. Hamburg: Rowohlt Taschenbuch Verlag.
• Engeler, E. (2019). Neural algebra on “how does the brain think?”. Theoretical Computer Science, 777, pp. 296-307. doi:10.1016/j.tcs.2019.03.038
• Frith, C. (2007). Making up the mind. How the brain creates our mental world. London: Blackwell.
• Goleman, D. (1996). Emotional Intelligence: Why It Can Matter More than IQ. London: Bloomsbury Publishing.
• Haugeland, J. 1981. Semantic engines: An introduction to mind design. In Mind Design:
• Philosophy, Psychology, Artificial Intelligence, ed. J. Haugeland. MIT Press
• LeDoux, J. E. (1996). The Emotional Brain. New York: Simon & Schuster.
• Marblestone, A. H., Wayne, G., & Kording, K. P. (2016). Toward an Integration of Deep Learning and Neuroscience. Frontiers in computational neuroscience, 10, 94. doi:10.3389/fncom.2016.00094
• Penrose R, The Emperor’s New Mind: Concerning Computers, Mind, and the Law of Physics, Oxford: Oxford University Press, 1989.
• Pinker, S. (2009). How the Mind Works. New York: W. W. Norton & Company.
• Searle J. (1980). Brains and Programs, Behavioral and Brain Sciences, 3:417-57
• Searle J (1992). The Rediscovery of the Mind, the MIT Press, Cambridge, 1992
• Sloman, A. (1978). The Computer Revolution in Philosophy. Hassocks, Sussex: Harvester Press (and Humanities Press).
• Wittgenstein, L, Philosophical Investigations, Basil Blackwell Ltd, 1953
   
  It is also useful to consult the journal Cognitive Science, published on behalf of the CognitiveScience Society.

Christoph Benzmüller (FU Berlin, AI & Logic) and Nabil Alsabah (bitkom.org, AI & Psychology)

Course language: English
Target group: Master’s students (Bachelor’s students from the fifth semester onwards)
Prerequisites: Some papers might require knowledge in mathematics and AI, others do not