Postgraduate course
2024/2025
Philosophy of Artificial Intelligence
Type:
Elective course
Area of studies:
Postgraduate Studies
Delivered by:
School of Philosophy and Cultural Studies
When:
2 year, 1 semester
Mode of studies:
offline
Open to:
students of one campus
Instructors:
Louis Vervoort
Language:
English
ECTS credits:
2
Course Syllabus
Abstract
This is a course on the philosophy of Artificial Intelligence (AI) on graduate level. We will start with an overview of the basic concepts of the philosophy of AI. We then continue with more advanced insights about Deep Learning / Machine Learning (DL/ML) based on artificial neural networks (ANN). AI is nowadays widely used, and will become particularly powerful and ubiquitous in the near future. Several philosophers and AI experts have extolled the quasi-unlimited potential of this technology; others have warned for an imminent ‘singularity’ in human history in which superintelligent AI systems will overtake the hegemony over people. It therefore is important to reflect on the foundational aspects of this potentially disruptive technology. LLMs (Large Language Models) have recently made such spectacular progress that several philosophical questions become urgent as never before.
We will study some of the latest writings of experts as Vincent Mueller and Cameron Buckner, to try to grasp what the evolution of advanced AI may look like. Some other questions we will investigate are: What is the difference between human intelligence and AI? Could computers have a mind and consciousness? Is thinking computing? Finally, we will also study some of the research done at HSE about these questions
Learning Objectives
- Have analytic and synthetic knowledge of the main themes and questions related to the philosophy of AI. Be able to critically engage with the literature on the conceptual foundations of AI, as well as with advanced concepts and questions related to DL/ML and ANN.
Expected Learning Outcomes
- Know the basic problems and theories on the philosophy and ethics of AI.
- Know key definitions of concepts related to intelligence, mind, consciousness, Turing test, Goedel’s theorem and other concepts seen in the course.
- Know the key ethical issues related to AI.
- Have a conceptual basis for assessing the potential, the possible evolution, the risks of AI.
- Have a basis for thinking creatively about new developments in AI.
- Present and argue for key ideas in the philosophical and scientific debate.
Course Contents
- Intro. What is AI ? What is intelligence ?
- Intro. Artificial Neural Nets (ANN)
- Foundations of AI; some history.
- Foundations of AI; some history2.
- Intro on (normative) ethics. What is ethics?
- Weak AI versus strong AI.
- Ethics of AI 1
- Ethics of AI 2
Assessment Elements
- Test 1Mid-term and end-of-term written test, in-class, all books closed.
- Test 2Oral presentation of book chapter
Bibliography
Recommended Core Bibliography
- AI ethics, Coeckelbergh, M., 2020
- Artificial intelligence : the basics, Warwick, K., 2012
Recommended Additional Bibliography
- Gordon, B. M. (2011). Artificial Intelligence : Approaches, Tools, and Applications. New York: Nova Science Publishers, Inc. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=440805