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Course Syllabus

Bachelor 2024/2025

Philosophy of Artificial Intelligence

Type: Elective course (Data Science and Business Analytics)
Area of studies: Applied Mathematics and Information Science
Delivered by: Big Data and Information Retrieval School
Where: Faculty of Computer Science
When: 4 year, 1 module
Mode of studies: offline
Open to: students of one campus
Language: English
ECTS credits: 3

Course Syllabus

Full Syllabus

Abstract

This course is an introduction to the philosophy and ethics of Artificial Intelligence (AI), and of robots based on AI. AI is a recent technology that is already widely used, and that will become particularly powerful and ubiquitous in the near future. Several researchers and writers 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. We will start with having a look at what AI and Machine Learning are, and at the tasks they can execute for the time being. The main part of the course will be dedicated to questions as: What is the difference between human intelligence and AI? Could computers have a mind and consciousness? Is thinking computing? Can ChatGPT think? How could AI evolve, ideally and less ideally? What are the risks related to AI? Can we ensure that AI behaves ethically? Which ethical principles (and governmental rules) have been proposed for the reasonable use of AI? What is the research done at HSE related to these questions?
Learning Objectives

Learning Objectives

  • Have basic analytic and synthetic knowledge of the main themes and questions related to the philosophy and ethics of AI. Be able to critically engage with philosophical literature on the conceptual foundations of AI.
Expected Learning Outcomes

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.
  • Understand the difference human / artificial intelligence.
  • 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

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.
  • Ethics of AI 2.
  • Ethics of AI 3.
Assessment Elements

Assessment Elements

  • non-blocking Test1
  • non-blocking OralPres1
  • non-blocking OralPres2
  • non-blocking Exam1
Interim Assessment

Interim Assessment

  • 2024/2025 1st module
    Final = 0.25*Test1 + 0.2*OralPres1 + 0.2*OralPres2 + 0.35*Exam1
Bibliography

Bibliography

Recommended Core Bibliography

  • AI ethics, Coeckelbergh, M., 2020

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

Authors

  • VERVURT LUIPOLDZH -