Course Unit Code | 711-0116/02 |
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Number of ECTS Credits Allocated | 2 ECTS credits |
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Type of Course Unit * | Choice-compulsory type B |
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Level of Course Unit * | First Cycle |
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Year of Study * | First Year |
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Semester when the Course Unit is delivered | Winter, Summer Semester |
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Mode of Delivery | Face-to-face |
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Language of Instruction | Czech |
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Prerequisites and Co-Requisites | There are no prerequisites or co-requisites for this course unit |
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Name of Lecturer(s) | Personal ID | Name |
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| HAU40 | prof. Dr. Mgr. Tomáš Hauer |
| ZEM0106 | Mgr. Tomáš Zemčík, Ph.D. |
Summary |
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Over the course of about fifty years of artificial intelligence, new technologies have emerged that are enriching this field. It is a dynamic and rapidly evolving area. Even though we cannot precisely determine the very definition of intelligence. Nowadays, it is a broad field that applies knowledge from many areas such as psychology, neuroscience, logic, economics, philosophy, mathematics, management theory, etc. Artificial Intelligence is currently dealt with by a large number of scientists as well as philosophers who raise many questions. One of the most important one is the question whether machines can think and the question whether AI can have its own ethics. The course analyses the moral dilemmas associated with the dynamic development in the AI area and possible scenarios of future developments in this area. |
Learning Outcomes of the Course Unit |
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Students completing the course will be able to:
- Effectively use basic methodological approaches in ethics;
- To understand the basic ethical concepts;
- Ethically justify ours decisions in cases in which engineers and technicians are insufficient everyday moral intuitions.
- Assess the legitimacy of ethical arguments in solving conflict situations;
- Identify your own strengths and weaknesses in the present solutions ethical dilemma.
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Course Contents |
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1. The emergence of ethics as a science discipline, basic ethical issues and concepts.
2. Basic methodological approaches in ethics (descriptive ethics, normative ethics, meta-ethics, applied ethics).
3. Basic functions of morality, moral reasoning, historical overview of ethical theory.
4. Deontological ethics, utilitarianism and ethics of virtues.
5. Thought experiments in ethics.
6. Artificial Intelligence, its Characteristics and History
7. Development of paradigms of artificial intelligence
8. New Approaches to Artificial Intelligence
9. Current trends in AI research (superintelligence, singularity, transhumanism, etc.)
10. The Second Age of Machines, Artificial Intelligence and Ethical Dilemmas
11. Moral implications of superintelligence and artificial mind
12. Future of AI and possible scenarios
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Recommended or Required Reading |
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Required Reading: |
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Wendell Wallach. Moral Machines: Teaching Robots Right from Wrong, Oxford University Press; 1 edition (June 3, 2010), ISBN-10: 0199737975
Paula Boddington: Towards a Code of Ethics for Artificial Intelligence (Artificial Intelligence: Foundations, Theory, and Algorithms), Springer; 1st ed. 2017, ISBN-13: 978-331960647
Mel Thompson, Ethical Theory, Hodder Education an Hachette UK company 2008, ISBN: 978- 0340- 95779- 0
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THOMPSON, M. Přehled Etiky, Portál , Praha 2004. ISBN 80-7178-806-6
Azenbacher, A. Úvod do etiky, Zvon 1994, ISBN 80-7113-111-3
David J. Gunkel: The Machine Question: Critical Perspectives on AI, Robots, and Ethics, (MIT Press 2012) |
Recommended Reading: |
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WHITBECK, C. ETHICS IN ENGINEERING PRACTICE AND RESEARCH (Second Edition), Cambridge University Press 2011, New York, USA, Second edition published 2011, ISBN 978-0-521-89797-6.
FLEDDERMANN, CH, B. Engineering Ethics, Pearson Education Limited 2014, Edinburgh, ISBN 10:1-292-01252-8.
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BRAZDA, R. ETHICUM, VeRBuM Brno 2010, ISBN 978-80-904273-9-6.
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Planned learning activities and teaching methods |
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Seminars, Tutorials, Project work |
Assesment methods and criteria |
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Task Title | Task Type | Maximum Number of Points (Act. for Subtasks) | Minimum Number of Points for Task Passing |
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Credit | Credit | 85 | 85 |