Regulation of AI
Code: 106560 ECTS Credits: 6| Degree | Type | Year |
|---|---|---|
| 2504392 Artificial Intelligence | OB | 3 |
Contact
- Name:
- Noelia Igareda Gonzalez
- Email:
- noelia.igareda@uab.cat
Teachers
- Susana Navas Navarro
Teaching groups languages
You can view this information at the end of this document.
Prerequisites
This course does not have any requirements.
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
- Analyse AI application cases from an ethical, legal and social point of view.
- Analyse how data protection regulations and the right to privacy are applied to the design and development of AI.
- Analyse intellectual property in relation to AI.
- Communicate effectively, both orally and in writing, adequately using the necessary communicative resources and adapting to the characteristics of the situation and the audience.
- Critically analyse the principles, values and procedures that govern the practice of the profession.
- Develop critical thinking to analyse alternatives and proposals, both one's own and those of others, in a well-founded and argued manner.
- 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.
- Explain the code of ethics, explicit or implicit, that pertains to the field of knowledge.
- Identify cases of civil liability in the use of AI.
- 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.
- Understand the social, ethical and legal implications of professional AI practice.
- Work independently, with responsibility and initiative, planning and managing time and available resources, and adapting to unforeseen situations.
Content
1st part Noelia Igareda
- Introduction to Law /foundations of the law
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
- AI Regulation
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
Activities and Methodology
| 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.
Assessment
Continous Assessment Activities
| 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.
Bibliography
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
Llorente Sánchez-Arjona, M. (25/03/2021) “Big Data, Inteligencia Artificial y Violencia de Género”. Diario La Ley. Ciberderecho
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/
Software
The subject does not requiere any specific software
Language list
| 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 |