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Regulation of AI

Code: 106560 ECTS Credits: 6
2025/2026
Degree Type Year
Artificial Intelligence OB 3

Contact

Name:
Marc Abraham Puig Hernandez
Email:
marcabraham.puig@uab.cat

Teachers

Santiago Robert Guillén

Teaching groups languages

You can view this information at the end of this document.


Prerequisites

This course does not have any requirements. This subject will be taught with a perspective of the Sustainable Development Goals.


Objectives and Contextualisation

The objectives of the course will be:

  • Basic knowledge of the role of the law in the field of artificial intelligence
  • Legal framework applicable to the artificial intelligence
  • Understanding of the main legal aspects in relation to artificial intelligence at national, European and international level.

 


Competences

  • Act with ethical responsibility and respect for fundamental rights and duties, diversity and democratic values.
  • Communicate effectively, both orally and in writing, adequately using the necessary communicative resources and adapting to the characteristics of the situation and the audience.
  • Develop critical thinking to analyse alternatives and proposals, both one's own and those of others, in a well-founded and argued manner.
  • Identify, analyse and evaluate the ethical and social impact, the human and cultural context, and the legal implications of the development of artificial intelligence and data manipulation applications in different fields.
  • Students must be capable of collecting and interpreting relevant data (usually within their area of study) in order to make statements that reflect social, scientific or ethical relevant issues.
  • Work independently, with responsibility and initiative, planning and managing time and available resources, and adapting to unforeseen situations.

Learning Outcomes

  1. Analyse AI application cases from an ethical, legal and social point of view.
  2. Analyse how data protection regulations and the right to privacy are applied to the design and development of AI.
  3. Analyse intellectual property in relation to AI.
  4. Communicate effectively, both orally and in writing, adequately using the necessary communicative resources and adapting to the characteristics of the situation and the audience.
  5. Critically analyse the principles, values and procedures that govern the practice of the profession.
  6. Develop critical thinking to analyse alternatives and proposals, both one's own and those of others, in a well-founded and argued manner.
  7. Evaluate the difficulties, prejudices and discriminations that can be found in actions or projects, in a short or long term, in relation to certain people or groups.
  8. Explain the code of ethics, explicit or implicit, that pertains to the field of knowledge.
  9. Identify cases of civil liability in the use of AI.
  10. Students must be capable of collecting and interpreting relevant data (usually within their area of study) in order to make statements that reflect social, scientific or ethical relevant issues.
  11. Understand the social, ethical and legal implications of professional AI practice.
  12. Work independently, with responsibility and initiative, planning and managing time and available resources, and adapting to unforeseen situations.

Content

PART I – Prof. Marc-Abraham Puig Hernández

1. Introduction to Law / Fundamentals of Law. 1.1. Differences between law, ethics, morals and other types of norms. 1.2. International Law, European Law and State Law. 1.3. Ethical guidelines and soft law. 1.4. Regulation and self-regulation. 1.5. Elaboration of the Law, legal adjudication and access to justice.

2. AI and human rights. 2.1. Differentiate between human rights, fundamental rights and other types of rights. 2.2. Legal protection, guarantees of human rights, and their application in the field of AI. 2.3. Ethical principles of AI: respect for human autonomy, prevention of evil, equity and explicability. 2.4. Transparency in decision making.

3. AI and anti-discrimination law. 3.1. Legal frameworks against discrimination: international, European and statewide. 3.2. AI and discriminatory bias: legal tools and legal obligations. 3.3. Content moderation and codes of practice.

4. AI, gender and childhood. 4.1. Gender equality, gender perspective and anti-gender. 4.2. AI as gender technology: legal instruments and legal consequences. 4.3. AI and minors.

5. Digital rights and AI systems. 5.1. Legal framework and implications in the field of AI. 5.2. The Charter of Digital Rights. 5.3. Seven requirements of AI systems.

6. AI and Protection of Personal Data. 6.1. Impact of the General Data protection Regulation (GDPR) on AI. 6.2. Legal and legitimate use of personal data through AI.



PART II –Prof. Santiago Robert Guillén

7. Fundamentals of Private Law. 7.1. Right of contracts. Consumer rights 7.1.1. Right of contracts. 7.1.2. Consumer rights. 7.2. Contracts for the provision of services and digital content. 7.3. Civil liability and non-contractual responsibility. 7.4. Regulation of Digital Services. 7.4.1. Introduction. 7.4.2. A paradigm shifts in digital services.

8. Evolution and regulation of AI. 8.1. Digital Decade for 2030. 8.2. Risk-based AI regulation. 8.2.1. Scope of application. 8.2.2. Legal definitions. 8.3. AI systems. Legal requirements. 8.4. Objectives of AI models. Legal requirements. 8.5. AI Generative. 8.6. Cybersecurity.

9. Regulation of data. 9.1. What is a data and how to classify it. 9.2. The text and the exception of data mining in copyright law. 9.3. Data governance. 9.4. The European Regulation on Data (Data Act).

10. Extracontractual liability derived from damages caused by AI systems. 10.1. The proposal for a European regulation on non-contractual liability. 10.2. The European proposal to regulate the liability of AI system producers.

11. The legal protection of AI systems. 11.1. Basic copyright and creation. 11.2. Software regulation. 11.3. The Sui generis right of the databases. 11.4. The regulation of trade secrets in Europe.


Activities and Methodology

Title Hours ECTS Learning Outcomes
Type: Directed      
Attendance to class and participation 44 1.76 5, 2, 11, 4, 6, 10, 1, 7
Case study 50 2 5, 3, 2, 11, 6, 9, 10, 1, 12, 7
Practices and exercices 50 2 5, 3, 2, 11, 6, 9, 10, 1, 12, 7 

The orientation of the course is predominantly practical. Each class will generally begin with the presentation of a real case or a problem, which will lead to a group discussion. 
Afetrwards, the professor will explain the key  legal concepts, the legal framework applicable to AI and legal challenges for artificial intelligence.

Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.


Assessment

Continous Assessment Activities

Title Weighting Hours ECTS Learning Outcomes
Assessment practical case 25% 3 0.12 3, 2, 11, 6, 8, 9, 10, 1, 12, 7
News analysis 25% 3 0.12 5, 11, 4, 6, 10, 1, 12, 7

The final grade will be obtained according to the following criteria:

 

1.  Continuous evaluation (40% of the final grade). Considering:

Evidence of the first part (Marc-Abraham Puig) (20% of the final grade)

Evidence of the second part (Santiago Robert) (20% of the final grade)

The evidence are the results of the cases presented in each class.

2. Partial exam (20 % of the final grade)

If the student passes this exam with a 6 mark or more, these contents will not appear again in the final exam.

3.  Final exam (40% of the final grade)

To successfully complete the course, it is imperative to achieve a minimum of 5 marks on the final exam and to compute the final grade sum. A student will undergo revaluation if the continuous evaluation yields a score below 5.

 

REVALUATION

The revaluation will be another exam (like the final exam), and the maximum grade will be a 6.

The student will be evaluated if he/she does at least 2/3 parts of the activities. If not, the student will be considered “not assessable”. 

 

SINGLE EVALUATION

Final exam (50% of the final grade)

Realisation of 4 practical cases (50 % of the final grade)

The same criteria of “no assessable” of the continuos evaluated will be applied in the one sate evaluation.

 

USE OF AI

Restricted use: for this subject the use of Artificial Intelligence (AI) technologies is allowed except for all those activities that compute for the final grade. In this case, the teacher will indicate how it could be used and how its use will be evaluated. The students will have to clearly identify which parts have been generated with this technology, specify the tools used and include a critical reflection on how these have influenced theprocess and the result of the activity. The non-transparency of the use of AI in this evaluable activity will be considered lack of academic honesty and may lead to a partial or total penalty in the grade of the activity, or greater penalties in cases of severity.


Bibliography

COURSEBOOK

Navas Navarro, S. (Coord.). (s.f.). Inteligencia artificial, tecnología y derecho. Tirant lo Blanch.

 

FURTHER READING

AA.VV. (2022). Las cláusulas específicas del Reglamento General de Protección de Datos en el Ordenamiento Jurídico español: Cuestiones clave de orden nacional e internacional. Tirant lo Blanch.

AEPD, APDCAT, & AVPD (2018). Guía del Reglamento General de Protección de Datos para responsables de tratamiento. Agencia Española de Protección de Datos.

AEPD (2017). Protección de datos: Guía para el ciudadano. Agencia Española de Protección de Datos.

Atienza Navarro, M. L. (2022). Daños causados por inteligencia artificial y responsabilidad civil. Atelier.

Azuaje Pirela, M. (Coord.). (2023). Introducción a la ética y el derecho de la inteligencia artificial. LA LEY Soluciones Legales.

Barrio, M. (2021). Manual de Derecho digital. Tirant Lo Blanch.

Bello Janeiro, D. (Coord.). (2020). Nuevas tecnologías y responsabilidad civil. Reus.

Bercovitz Rodríguez-Cano, R. (2019). Comentarios a la Ley de Propiedad Intelectual (6ª ed.). Tecnos.

Bourcier, D., & Casanovas, P. (2012). Inteligencia artificial y derecho. Editorial UOC.

Casanovas, P. (2024). On ambiguity and the expressive function of law: The role of pragmatics in smart legal ecosystems. arXiv. https://doi.org/10.48550/arxiv.2406.05084

Casanovas, P., Hashmi, M., & de Koker, L. (2024). A three steps methodological approach to legal governance validation. arXiv. https://doi.org/10.48550/arxiv.2407.20691

Casanovas, P., &Oboler, A. (2025). Foreword: A holistic framework for hate speech modelling. En Regulating Hate Speech Created by Generative AI (pp. xii–xvi). CRC Press. https://doi.org/10.1201/9781032654829

Casas Bahamonde, M. E. (Dir.). (2025). Derecho y tecnologías. Fundación Ramón Areces.

Cerrero Martínez, A., & Peguera Poch, M. (Coords.). (2020). Retos jurídicos de la inteligencia artificial. Aranzadi.

Cotino Hueso, L. (Dir.). (2022). Derechos y garantías ante la inteligencia artificial y las decisiones automatizadas. Aranzadi.

Council of Europe (2023). Human rights by design: Future-proofing human rights protection in the era of AI. Consejo de Europa.

Custers, B., & Fosch-Villaronga, E. (Eds.). (2022). Law and Artificial Intelligence: Regulating AI and Applying AI in Legal Practice. Springer.

Díaz Alabart, S. (2018). Robots y responsabilidad civil. Reus.

Ebers, M., & Navas, S. (Eds.) (2020). Algorithms and Law. Cambridge University Press.

Fernández Carballo-Calero, P. (2021). La propiedad intelectual de las obras creadas por inteligencia artificial. Aranzadi.

FRA (European Union Agency for Fundamental Rights) (2018). #BigData: Discrimination in data-supported decision making. https://fra.europa.eu/en/publication/2018/bigdata-discrimination-data-supported-decision-making

FRA (European Union Agency for Fundamental Rights) (2020). Getting the future right – Artificial intelligence and fundamental rights. https://fra.europa.eu/en/publication/2020/artificial-intelligence-and-fundamental-rights

Gamaero Casado, E., & Pérez Guerrero, F. L. (Coords.) (2023). Inteligencia artificial y sector público: retos, límites y medios. Tirant lo Blanch.

Garon, J. M. (2025). Artificial Intelligence Law and Regulation in a Nutshell. West Academic. 

Garriga Domínguez, A. (2023). Las exigencias de transparencia para los sistemas algorítmicos de recomendación, selección de contenidos y publicidad en línea en el nuevo Reglamento Europeo de Servicios Digitales. Revista Española de la Transparencia, 2023(2444-2607).

Moreno Rebato, M. (2021). Inteligencia artificial: Umbrales éticos, derecho y administraciones públicas. Aranzadi.

Llano Alonso, F. H. (2022). Inteligencia artificial y filosofía del derecho. Laborum.

Llorente Sánchez-Arjona, M. (2021, 25 de marzo). Big Data, Inteligencia Artificial y Violencia de Género. Diario La Ley. Ciberderecho.

Martínez Nadal, A. (Dir.). (2021). Plataformas digitales: Aspectos jurídicos. Thomson Reuters – Aranzadi.

Marín Salmerón, A. (2023). El defecto de diseño en los productos digitales. Aranzadi.

Monterroso Casado, E. (Dir.). (2019). Inteligencia artificial y riesgos cibernéticos: Responsabilidades y aseguramiento. Tirant lo Blanch.

Pegueras Poch, M. (Coord.). (2023). Perspectivas regulatorias de la inteligencia artificial en la Unión Europea. Reus.

Presno Linera, M. A. (2022). Derechos fundamentales e inteligencia artificial en el estado social, democrático y digital de derecho. El Cronista del Estado Social y Democrático de Derecho, (100).

Puig Hernández, M.-A. (2025). La dignidad humana y la singularidad de la IA. En N. Reynal Querol, F. Ramos Romeu, A. Libano Beristain, et al. (Coords.), De la ejecución a la historia del Derecho Procesaly de sus protagonistas: Libro V: Apuntes históricos y otros estudios.Liber Amicorum en homenaje al Profesor Manuel-Jesús Cachón Cadenas (pp. 479–493). Atelier.

Rodríguez García, J. A., & Moreno Rebato, M. (2018). ¡El futuro ya está aquí! Derecho e inteligencia artificial. Revista Aranzadi de Derecho y Nuevas Tecnologías, (48).

Sartor, G., Casanovas, P., Biasiotti, M. A., & Fernández-Barrera, M. (Eds.). (2011). Approaches to Legal Ontologies: Theories, Domains, Methodologies. Springer.

UNESCO. (2021). Recomendación sobre la ética de la inteligencia artificial. Organización de las Naciones Unidas para la Educación, la Ciencia y la Cultura.

Villás Olmeda, M., & Camacho Ibáñez, J. (2022). Manual de ética aplicada en inteligencia artificial. Anaya.

Zurita Martín, I. (2020). La responsabilidad civil por los daños causados por los robots inteligentes como productos defectuosos. Reus.

 

LINKS

 https://www.gov.uk/government/publications/ai-regulation-a-pro-innovation-approach/white-paper.

 https://www.whitehouse.gov/ostp/ai-bill-of-rights/

 https://commission.europa.eu/system/files/2020-02/commission-white-paper-artificial-intelligence-feb2020_en.pdf


Software

The subject does not requiere any specific software


Groups and Languages

Please note that this information is provisional until 30 November 2025. You can check it through this link. To consult the language you will need to enter the CODE of the subject.

Name Group Language Semester Turn
(PAUL) Classroom practices 711 English first semester afternoon
(PLAB) Practical laboratories 711 English first semester afternoon
(TE) Theory 71 English first semester afternoon