Universitat Internacional de Catalunya
AI in Decision-Making
Other languages of instruction: Catalan, Spanish,
Teaching staff
Introduction
Artificial Intelligence (AI) has become an omnipresent technology in today’s society. Its impact is already evident in highly technological sectors, and in the coming years, it is expected to transform all professional fields, bringing profound changes to the labor market and posing significant ethical challenges.
Aware of this reality, UIC is committed to offering this course to all its undergraduate students. The goal is twofold: on the one hand, to provide a solid foundation on the principles and fundamentals of AI; and on the other, to analyze its potential impact on the immediate future of each discipline, especially within the business and management context.
Objectives
- Provide a solid understanding of the fundamental principles of AI.
- Explore the current and future impact of AI across various professional sectors.
- Reflect on the ethical challenges posed by the implementation of AI in that sector.
- Foster critical thinking about the role of AI in workforce transformation.
Learning outcomes of the subject
Knowledge
- Identify key concepts and underlying technologies of AI.
- Cite the main areas of AI application and its effects on different disciplines.
- Recognize the challenges and opportunities that AI offers in the workplace context.
- Distinguish reliable sources of information about AI.
Skills
- Critically analyze AI case studies in industry and society.
- Assess the implications of AI in the student’s own field of study.
- Communicate effectively about AI to non-specialized audiences.
Competencies
- Develop analytical skills to predict AI trends.
- Solve ethical problems through the development of responsible solutions.
- Integrate AI knowledge into professional decision-making.
Syllabus
The course consists of a first block of common content and a second block of specialized content in the knowledge area specific to each degree.
Common content block:
- Introduction to Artificial Intelligence: what we understand by AI, the early decades.
- Foundations of AI: data, neural networks, supervised and unsupervised learning.
- Convergence between AI and supercomputing: the disruptive role of GPUs.
- Geopolitics of AI: value chain, technological sovereignty, geopolitical clashes.
- General applications of AI: examples ranging from Medicine to Art and Creativity.
- Ethics and AI: Privacy, Bias, and AI Governance.
Specific content block:
- Impact of AI on Business Administration and Management (ADE).
- Real cases of AI application in professions related to business and management areas.
- Future trends and opportunities
Teaching and learning activities
In person
The basic methodology will be theoretical and expository classes. Demonstrations will also be carried out to facilitate the understanding of different concepts, group dynamics among students, and practical business cases aimed at illustrating their applicability in the corporate world.
Finally, a group project will be conducted at the end of the module, in which students will have to solve a company problem by applying an AI-based solution. Students will present the main conclusions to the entire class.
Evaluation systems and criteria
In person
Active participation and contribution in class discussions
Tests to assess the learning of theoretical concepts taught in the module
Presentation of the final group project at the end of the module
The final grade consists of:
- Active attendance (minimum of 80%): 20%
- Class participation: 20%
- Learning test: 20%
- Oral presentation of the final project: 40%