Artificial Intelligence

Learning objectives:

• Explain concisely the scope of AI, its potential for society as well as its limitations.
• Discuss contemporary applications of AI from technical, legal, ethical and economical perspectives
• Describe in overall terms the main paradigms of AI and explain their respective strengths and weaknesses
• Describe in overall terms the most prevalent methods in current AI and their respective application areas, strengths and weaknesses
• Explain the meaning of, and difference between, concepts often used to describe AI or parts of AI, including deep learning, neural networks, machine learning, natural-language processing, knowledge representation, automated planning, artificial general intelligence, generative AI, large language models.
• Given a task in the participant’s own area of work, analyse which methods of AI could potentially solve it, and what consequences it would have in terms of efficiency, robustness, transparency, as well as its overall ethical, economical and societal consequences
• Describe the main trade-offs in designing AI systems in terms of generality vs. scalability, flexibility vs. explainability, etc.
• Explain the main characteristic differences between human and machine intelligence, and the potential in human-machine collaboration.