Universitat Internacional de Catalunya
AI in Dentistry
Other languages of instruction: Catalan, English
Teaching staff
Introduction
Artificial Intelligence (AI) has become something ubiquitous in our society today. The enormous impact of this technology is already beginning to be seen in very technological areas, and it is expected to reach more and more all professional sectors, with still uncertain work consequences and important ethical challenges.
That is why the UIC is committed to offering this subject to all its undergraduate students. On the one hand, it seeks to give some basic knowledge about technology, and on the other hand it aims to analyze the possible impact on the future of the labor market of each of the disciplines.
Objectives
. Provide a solid understanding of the fundamental principles of AI.
' To explore the current and future impact of AI in various professional sectors.
. Reflect on the ethical challenges presented by the implementation of AI in that sector.
. Promote critical thinking about the role of AI in job transformation.
2. Learning Outcomes
2.1 Knowledge
Identify the key concepts and underlying technologies of AI.
Quote the main areas of application of AI and its effects in different disciplines.
Recognize the challenges and opportunities that AI offers in the work context.
Discriminate reliable sources of information about AI.
2.2 Skills
Critically analyze AI case studies in industry and society.
Evaluate the implications of AI in the student's own field of study.
Communicate effectively on AI to non-specialized audiences.
2.3 Competences
Develop analytical capacity to predict trends in AI.
Solve ethical problems through the development of responsible solutions.
Integrate knowledge of AI into professional decision making.
Syllabus
The subject has a first block of common contents, and a second block of specialized contents in the area of knowledge of each degree.
Block of common contents (2ECTS):
1. Introduction to Artificial Intelligence: what we understand by AI, the first decades.
2. Fundamentals of AI: data, neural networks, supervised and unsupervised learning.
3. Convergence between AI and supercomputing: the disruptive role of GPUs.
4. AI geopolitics: value chain, technological sovereignty, geopolitical shocks.
5. General applications of AI: examples from Medicine to Art and Creativity.
6. Ethics and AI: Privacy, Bias, and Governance of AI.
Block of specific contents (1ECTS):
7. Impact of AI in the corresponding area of knowledge.
8. Real cases of application of AI to professions associated with the area of knowledge.
9. Future trends and opportunities.
Teaching and learning activities
In person
The basic methodology will be the theoretical and expository classes. There will also be interactive seminars with case analysis and expert guests, as well as conferences of AI experts. Group work will also be valued to promote collaboration and peer learning, and individual previous readings on the topics to be dealt with in class.
Evaluation systems and criteria
In person
The evaluation will be based on the following activities:
. Active participation and contribution in class discussions.
. Written works that reflect on the material studied.
s Oral presentations to evaluate communication skills.
. Final exams that measure the integral understanding of the subject.
Evaluation period
- E1 13/05/2025 A08 08:00h
- R1 03/06/2025 A08 09:00h