Introductory description

This module gives participants theoretical and practical knowledge about applying Artificial Intelligence in real-world business and managerial environments. Participants will explore the different types of Artificial Intelligence, they will discover how they are developed, they will discuss their implication on jobs and tasks and tackle the ethical and environmental challenges associated with it.

Module web page

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

Introduction to AI and its terminologies
Supervised Learning
Unsupervised Learning
Deep Learning
Generative AI
Changes in Job tasks and roles with AI
AI Ethics
AI and Environmental Impact

Learning outcomes

By the end of the module, students should be able to:

• Demonstrate comprehensive understanding of the strategic nature of Artificial Intelligence in business
• Demonstrate comprehensive understanding of the challenges and implications of Artificial Intelligence in business for a variety of stakeholders
• Demonstrate critical reflection on the topic of Artificial Intelligence.

Indicative reading list

Akerkar, R. (2019). Artificial Intelligence for Business. Springer.
Mohanty, S. and Vyas, S. (2018). How to Compete in the Age of Artificial Intelligence. Apress.
Yao, M., Jia, M., Zhou, A. (2018). Applied Artificial Intelligence: A Handbook for Business Leaders. TOPBOTS.
Russell, S., Norvig, P. (2020). Artificial Intelligence A Modern Approach. Pearson, 4th Edition.
Albright, S.C., Winston, W.L. (2014). 5th ed. Business Analytics: Data Analysis & Decision Making. Cengage Learning.
Fischer, I. 2023, Evaluating the ethics of machines assessing humans The case of AQA: An assessment organisation and exam board in England. Journal of Information Technology Teaching Cases, https://doi.org/10.1177/20438869231178844
Fischer, I., Beswick, C. and Newell, S. 2021, Rho AI – Leveraging artificial intelligence to address climate change : financing, implementation and ethics,Journal of Information Technology Teaching Cases, https://journals.sagepub.com/doi/full/10.1177/2043886920961782
Brynjolfsson, E. and McAfee, A. (2017) The Business of Artificial Intelligence. Harvard Business Review. July 18, 2017. Available at: https://org/cover-story/2017/07/the-business-of-artificial-intelligence
Raisch, S. and Krakowski, S. (2021). 'Artificial Intelligence and Management: The Automation–Augmentation Paradox'. Academy of Management Review, 46, 192-210.
Zhang, Z., Nandhakumar, J., Hummel, J. T., and Waardenburg, L. 2020. "Addressing the Key Challenges of Developing Machine Learning AI Systems for Knowledge-Intensive Work," MIS Quarterly Executive (19:4), pp. 221-238.

Interdisciplinary

The module is interdisciplinary in nature as :

• A numerous example of AI applications will be provided for different disciplines
  -Students from different background will work in group during workshop to discuss AI applications in different disciplines
  -Both the technical aspect of AI and the societal aspect of AI will be discussed

International

Understanding AI requires understanding the international aspect of AI. AI is spread all over the world and we will discuss both its international use but also the different regulations associated with it.

Subject specific skills

Identify and evaluate opportunities for AI-transformation of business processes.
Identify and evaluate the managerial and organisational issues associated with the use of Artificial Intelligence.
Demonstrate research skills and the ability to effectively search, gather and utilise information and knowledge.

Transferable skills

Written communication
Systemic review of a topic