Course description
This course explores from an interdisciplinary perspective the transformative role of Artificial Intelligence in driving innovation and fostering creativity in business and society. By discussing how A.I. technologies are reshaping the landscape for generating new ideas and solutions, participants will gain insights into both the opportunities and challenges presented by this evolution. From enhancing decision-making processes to automating creative tasks, A.I. is not just a tool but a partner in the creative process. However, this partnership comes with its own set of challenges, including ethical considerations and the potential for stifling human creativity. Through interactive discussions, case studies and hands-on session attendees will gain understanding on the current impact of this technology on society.

The course is organized around 4 modules:

Module 1: The Basics - A Brief History of A.I. and How Generative AI Works
This module provides an introduction to Artificial Intelligence, tracing its evolution from the early concepts and theoretical foundations laid in the mid-20th century through the diffusion of Machine Learning to the development of modern generative AI technologies. Participants will learn about the milestones in AI development, including the transition from rule-based systems to machine learning, neural networks and deep learning. The focus will then shift to generative AI, explaining its mechanisms for creating new content, whether text, images, or music directly using AI tools like Chat GPT. Understanding these basics lays the groundwork for comprehending AI's role in innovation and creativity.

Module 2: The Impact of A.I. on the Creative Industry
This module explores how AI is revolutionizing the creative industries, from advertising to the music and movie industry. In advertising, AI tools are being used to generate creative content, target audiences more effectively, and optimize ad performance. In the movie industry, AI assists in scriptwriting, animation, and even in creating realistic visual effects. This module examines case studies where AI has been successfully integrated into creative processes, highlighting the benefits of such integration, including increased efficiency and the ability to generate innovative ideas and solutions. Attendees will also discuss the potential for AI to disrupt traditional creative roles and processes.

Module 3: A.I. and the Process of Innovation
In this module, we discuss how AI is facilitating process and product innovation, transforming business operations and workflows across various sectors. We'll explore how AI technologies, including machine learning and natural language processing, are being leveraged to optimize production processes, enhance supply chain management, and provide personalized customer experiences, but also to create new blue-prints in the semiconductor industry and new designs. Also this segment highlights practical examples of AI-driven process innovation, from automated content creation in digital marketing to the application in industrial design. Participants will learn how the introduction of AI is transforming the landscape of the innovation process leveraging on new skills, but making old competencies obsolete.

Module 4: Challenges: Originality, Control, and Ethical Considerations
This module tackles the significant challenges associated with the integration of AI, with a particular focus on issues of originality, control, and ethics. A critical look at AI's originality reveals a tendency towards redundancy, as these systems often rely heavily on existing content for training, raising questions about the true creativity of AI-generated outputs. This segment also addresses the complexities of maintaining control over increasingly autonomous AI systems, highlighting the need for mechanisms that ensure transparency and accountability.
Ethical considerations are thoroughly explored, including biases embedded within AI algorithms and the implications of generative AI on intellectual property. Through this module, participants are encouraged to critically evaluate the implications of AI's limitations and ethical dilemmas, fostering a dialogue on how to navigate these challenges while advancing innovation.

Learning outcomes of the course
• Understanding the intuition behind the function of A.I.
• Relating the function of AI to its main opportunities and challenges for business and society.
• Gaining knowledge about the use of AI in specific creative industries.
• Developing a clear understanding of the risks of AI for citizens and consumers.
• Developing horizontal skills in debating opportunities and risks of AI.

Teaching and evaluation methods
The course combines traditional frontal classes with interactive elements such as organized debates, case presentations and hands-on sessions with AI tools to foster a comprehensive understanding of AI's role in innovation and creativity. Frontal classes will provide the core knowledge and theoretical background, while debates and case presentations will allow students to delve deeply into specific topics, enhancing their research and presentation skills. AI tools will allow them to explore the potential and limitations of AI for content creation.

Evaluation will comprise class participation (20%), the quality and insightfulness of contributions during debates and presentations (40%), and a final written exam (40%) covering theoretical and practical aspects of the course content.

Bibliography
• Anantrasirichai, N., & Bull, D. (2022). Artificial intelligence in the creative industries: a review. Artificial intelligence review, 55(1), 589-656.
• Baronchelli, A., 2024. Shaping new norms for AI. Philosophical Transactions of the Royal Society B, 379(1897), p.20230028.
• Buchanan, B. G. (2005). A (very) brief history of artificial intelligence. Ai Magazine, 26(4), 53-53.
• Cao, Y., Li, S., Liu, Y., Yan, Z., Dai, Y., Yu, P. S., & Sun, L. (2023). A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt. arXiv preprint arXiv:2303.04226.
• Caplan, R., Donovan, J., Hanson, L., and Matthews, J. (2018). Algorithmic accountability primer. Data & Society.
• Fisher, M. (2022). The chaos machine: The inside story of how social media rewired our minds and our world. Little, Brown. (selected chapters)
• McCorduck, P., Minsky, M., Selfridge, O. G., & Simon, H. A. (1977, August). History of artificial intelligence. In IJCAI (pp. 951-954).
• Paul, D., Sanap, G., Shenoy, S., Kalyane, D., Kalia, K., & Tekade, R. K. (2021). Artificial intelligence in drug discovery and development. Drug discovery today, 26(1), 80.
• Van de Haar, I., Broberg, C. P., & Doshoris, I. (2019). How Artificial Intelligence is changing The Relationship Between The Consumer and Brand in The Music Industry. LBMG Strategic Brand Management-Masters Paper Series.
• Verganti, R., Vendraminelli, L. and Iansiti, M., 2020. Innovation and design in the age of artificial intelligence. Journal of product innovation management, 37(3), pp.212-227.
• Zhang, K., & Aslan, A. B. (2021). AI technologies for education: Recent research & future directions. Computers and Education: Artificial Intelligence, 2, 100025.

Last update: January 29, 2025