- Ability to understand and identify the new challenges faced by the Social Sciences in the digital world. - Ability to understand and analyze individual and collective aspects of human behavior in the digital world. - Ability to understand and analyze the emerging social mechanisms in a hyperconnected and globalized world. - Ability to understand and analyze the consequences of technology on social relations. - Knowledge of good practices in ethical data management.

1. Introduction to data and algorithms ethics. 2. AI ethics and the European GDPR initiative and data strategy. 3. Alignment issues. 4. Data, bias and discrimination, transparency and explainability. 5. Practical session on biases, transparency and explainability. 6. Innovation and fundamental rights in the AI act of the EU and the rest of the world. 7. Copyright and current problems of generative AI.

Training Activities: - Theoretical classes - Theoretical-practical classes - Tutorials - Group work - Individual student work Teaching Methods: - Presentations in the professor's lecture room with computer and audiovisual support, in which the main concepts of the subject are developed and a bibliography is provided to complement the students' learning. - Critical reading of texts recommended by the subject professor: Press articles, reports, manuals and/or academic articles, either for later discussion in class, or to expand and consolidate knowledge of the subject. - Resolution of practical cases, problems, etc. raised by the professor, either individually or in a group. - Presentation and discussion in class, under the moderation of the professor, of topics related to the content of the subject, as well as practical case studies. - Developing pieces of work and reports, individually or in group. - Seminars/lectures by national and international experts, in face-to-face or remote synchronous sessions.