Degree | Type | Year |
---|---|---|
2504392 Artificial Intelligence | OB | 3 |
You can view this information at the end of this document.
This course does not have any requirements.
The objectives of the course will be:
1st part Noelia Igareda
1.1. Differences between law, ethics, morality and other rules.
1.2. International law, European law, national law.
1.3. How the law is elaborated, applied and access to justice
2. Artificial Intelligence and Human Rights
2.1. Differences between human rights, fundamental rights and other rights.
2.2. Human rights legal protection and standards, and their application on the field of AI.
3. Artificial Intelligence and anti-discrimination law
3.1. International, European and national legal frameworks to combat discrimination.
3.2. AI and discriminatory bias: legal tools and legal obligations
3.3. Moderation of contents and Codes of conduct
4. Artificial Intelligence, Gender and Minors
4.1. Gender equality, parity, gender perspective, genderism.
4.2. AI as a technology of gender: legal instruments and legal consequences
4.3. Minors
5. Digital rights
5.1. Definition and legal implication on the field of AI
5.2. Charter of Digital Rights6.
6. Personal data protection and AI
6.1. The impact of the General Data Protection Regulation (GDPR) on AI
6.2. How to useAI and personal data appropriately and lawfully
2nd part Susana Navas
7. Fundamentals
7.1. Contract Law. Consumer Rights
7. 1.1.Contract Law
7. 1.2.Consumer Rights
7. 2. Contracts for the supply of digital services and digital content
7. 3. Civil Liability. Non-contractual liability
7.4. Digital Services Regulation
7.4.1. Introduction
7.4.2. Digital services paradigm shift
8.1. Digital Decade for 2030
8.2. Risk-based AI Regulation
2.1. Scope of application
2.2. Legal definitions
8.3. AI-systems. Legal requirements
8.4. General purpose AI models. Legal requirements
8.5. Generative AI
8.6. Cybersecurity
9. Data Regulation
9.1. What is Data and How to Categorize It
9.2. The Text and Data Mining Exception in Copyright Law
9.3. Data Governance
9.4. The European Regulation on Data (Data Act)
10. Non-contractual Liability for Damages Caused by AI-systems
10.1. The forthcoming European Regulation on Non-Contractual Civil Liability
10.2. The forthcoming European Regulation on the Producer’s Liability for AI- systems
11. AI-systems Legal Protection
11.1. Basics on Copyright Law
11.2. The Software Regulation by Copyright Law
11.3. Sui generis right on databases
11.4. The Regulation of Trade Secrets in Europe
Title | Hours | ECTS | Learning Outcomes |
---|---|---|---|
Type: Directed | |||
Attendance to class and participation | 44 | 1.76 | 1, 2, 4, 5, 6, 7, 10, 11 |
Case study | 50 | 2 | 1, 2, 3, 5, 6, 7, 9, 10, 11, 12 |
Practices and exercices | 50 | 2 | 1, 2, 3, 5, 6, 7, 9, 10, 11, 12 |
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.
Title | Weighting | Hours | ECTS | Learning Outcomes |
---|---|---|---|---|
Analysis of a new | 25% | 3 | 0.12 | 1, 4, 5, 6, 7, 10, 11, 12 |
Assessment practical case | 25% | 3 | 0.12 | 1, 2, 3, 6, 7, 8, 9, 10, 11, 12 |
The final grade will be obtained according to the following criteria:
1 Continuous evaluation (40% of the final grade)
Submission of proofs of the first part (Noelia Igareda ) (20% of the final grade)
Submmission of proofs of the second part (Susana Navas( (20% os the final grade)
The proofs are the results of the practicals cases presented in each class.
2. Partial exam (20 % of the final grade)
If the student passes this exam with a 6 or more, these contents will be questioned in the final exam.
2 Final exam (40% of the final grade)
It is necessary to obtain a 5 or more to pass the course and to make average with the rest of the grades.
REAVALUATION
The reevaluation will be another exam and the maximum grade will be a 6.
The student will be evaluated as long as he/she does at least 2/3 parts of the activities. If not, the student will be considered not evaluated.
ONE STAGE EVALUATION
It will be:
Final exam (50% of the final grade)
Realisation of 4 practical cases (50 % of the final grade)
The same criteria of no evaluated of the continuos evaluated will be applied in the one sate evaluation.
AEPD (2017): Protección de datos. Guía para el Ciudadano https://www.aepd.es/es/documento/guia-ciudadano.pdf
AEPD, APDCAT, AVPD (2018): Guía del Reglamento General de Protección de Datos para responsables de tratamiento (Document en línia) https://www.aepd.es/es/documento/guia-rgpd-para-responsables-de-tratamiento.pdf-0
Barrio, Moisés (2021): Manual de Derecho digital, Tirant Lo Blanch, Valencia, 2021.
Council of Europe (2023): Human rights by design future-proofing human rights protection in the era of AI, disponible en : chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://rm.coe.int/follow-up-recommendation-on-the-2019-report-human-rights-by-design-fut/1680ab2279
Custers, Bart and Fosch-Villaronga, Eduard (eds.) (2022): Law and Artificial Intelligence. Regulating AI and Applying AI in Legal Practice, The Hague, Springer.
Ebers, Martin; Navas, Susana (eds.) (2020): Algorithms and Law, Cambridge University Press.
Fournier-Tombs, Eleonore y Castets-Renard, Celine (2021): Algorithms and the Propagation of Gendered Cultural Norms, disponible en:
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3980113
FRA (European Union Agency for Fundamental Rights) (2018): #BigData: Discrimination in data-supported decision making. Disponible en: https://fra.europa.eu/en/publication/2018/bigdata-discrimination-data-supported-decision-making
FRA (2020): Gettingthe future right – Artificial intelligence and fundamental rights Disponible en: https://fra.europa.eu/en/publication/2020/artificial-intelligence-and-fundamental-rights
Presno Linera, Miguel Angel (2022): “Derechos fundamentales e inteligencia artificial en el estado social, democrático y digital de derecho”, El Cronista del Estado social y democrático de Derecho, núm. 100, 2022, disponible en: https://www.academia.edu/89821366/Derechos_fundamentales_e_inteligencia_artificial_en_el_Estado_social_democrático_y_digital_de_Derecho?email_work_card=title.
https://www.gov.uk/government/publications/ai-regulation-a-pro-innovation-approach/white-paper.
https://www.whitehouse.gov/ostp/ai-bill-of-rights/
The subject does not requiere any specific software
Name | Group | Language | Semester | Turn |
---|---|---|---|---|
(PAUL) Classroom practices | 1 | English | first semester | afternoon |
(PLAB) Practical laboratories | 1 | English | first semester | afternoon |
(TE) Theory | 1 | English | first semester | afternoon |