Online schedule

• Prof. Monica Dragoicea: Responsible AI in Service Design (2 + 2 hours)
  Today we want to see AI adopted more widely, as it can bring significant benefits to society, companies, and individuals. One key advantage is the increased automation of tasks. However, for AI to be successfully adopted, we must build trust in its reasoning processes. Creating this trust is essential. According to the latest EU regulations, AI systems must meet three key requirements: Compliance with the law; Robustness and reliability; and Trustworthiness. The third element, trustworthiness, is more abstract and difficult to define. It's a somewhat fuzzy concept, and we need to identify the factors that help us evaluate how trustworthy an AI system truly is. This lecture addresses specific principles of responsible innovation and trustworthy AI in smart, data intensive service design. Specifically, it will explain how trustworthy AI integrates with the AI and analytics life cycle and the data supply chain, how to identify unwanted biases throughout the AI and analytics life cycle, and how to understand the principles of responsible innovation in smart service design.
• Prof. Mouzhi Ge: Recommender Systems and AI in Services (2 + 2 hours)
  This session provides a conceptual and foundational overview of recommender systems and the role of AI in modern service industries. We'll begin with the evolution of recommender systems, covering key paradigms such as collaborative filtering, content-based methods, and hybrid approaches. Alongside technical foundations, we'll work on the strategic role of AI in service personalization, decision support, and customer engagement. We also touch base some use cases like e-commerce, and healthcare. This lecture is designed for participants who want to build a solid theoretical ground in AI-driven recommendation and service systems. You would expect a mix of technical insights and real-world context, which is to help you understand why these systems matter, how they work and the broader implications of embedding AI in service environments. No deep coding is expected. This lecture is about principles, models, and mindset.
• Prof. Luca Carrubbo: Smart Service Systems (3 hours)
  An overview on Smart Service Systems’ design and management will be taken, with a specific focus on practical evidence in real life about how (and how much) versatile, functional, scalable they can be. A comparison on different strategies and operations performed by competitive firms nowadays helps in highlighting special features of their typical reactive, proactive, adaptive and dynamic approaches. Finally, an analysis in depth of ongoing interactions among entities in a (smart) service eco-system, as consequence of all of that, completes the scientific framework.
• Ph.D. Leonard Walletzký: Service Complexity, Smart Service Design and AI (2 + 2 hours)
  This session delves into the intricacies of service complexity and the principles of smart service design. Participants will explore how AI can be leveraged to enhance service design, focusing on practical applications and theoretical foundations. Topics include the role of AI in optimizing service processes, improving customer experiences, and driving innovation in service industries. The session aims to provide a comprehensive understanding of how AI can be integrated into service design to create resilient and smart service systems.
• doc. Tomáš Brázdil: Introduction to LLMs and Agentic AI with Applications in Service Sciences (3 hours)
  The lecture will provide an introduction to current AI systems based on large language models (LLMs) and agentic approaches. I will describe the basics of training LLMs using large amounts of data, supervised fine-tuning, reinforcement learning, etc., on an intuitive level without mathematical details. Then, I will elaborate on basic notions of agentic AI, such as agent communication and memory, and their implementations. These concepts will be illustrated using the OpenAI platform. The rest of the lecture will be devoted to applications of these methods in service sciences. Notably, I will present applications from diverse areas, such as recommendation engines, maintenance in manufacturing services, automated customer services, etc.