Identify and recognize the potential benefits and ethics/legal risks of the deployment of AI. Learn and understand the fundamental regulatory issues that have emerged in relation to the deployment of AI, and the relevance of design choices in the architecture of AI. Understand the complexity of the regulatory and policy landscape to address the legal and regulatory issues arising from the use of AI. Learn practical methodologies to evaluate and mitigate the potential risks arising from the implementation of AI. This knowledge should equip students with the ability to weigh and evaluate the development of specific AI applications, to see where potential regulatory and ethical challenges might arise in their use or deployment, and to learn methodologies to be able to give advice on designing AI technologies in a way that mitigates such issues. Human Rights and Fundamental Rights The sections related to the study of the legal regime for the protection of personal data serve the purpose of promoting knowledge and promotion of observance of fundamental rights, specifically, the right to information privacy. Gender equality, equal treatment and non-discrimination Discrimination issues are preferably addressed in the sections related to the risk management system in AI solutions and its ethical implications, since algorithmic discrimination is one of the aspects that generates the greatest concern among public powers and the Mitigation, if not elimination, of this risk has been identified as essential to strengthening confidence in the use of the systems.

Data, information and artificial intelligence as legal notions. The protection of personal and non-personal data Special rules for systems that use health and geolocation data. Special rules for intelligent transport systems and for behavior monitoring. The risk management approach in systems using AI techniques The liability regime associated with the creation and exploitation of AI solutions The Electronic Administration and the services of the information society Professional ethics and codes of conduct International ethics and Artificial Intelligence initiatives

Learning activities Theoretical and practical classes (AF1 and AF3). Tutorials (AF5). Team work (AF6) Exams (AF8) Methodology - Presentations in class by the teacher with the support of computer and audiovisual media, in which the main concepts of the subject are developed and the bibliography is provided to complement the students' learning. (MD1) -Read Critique of recommended by the teacher of the subject texts: newspaper articles, reports, manuals and / or academic papers, either for later discussion in class, either to expand and consolidate the knowledge of the subject. (MD2) -Resolution Of practical cases, problems, etc. posed by the teacher individually or in groups. (MD3) Exhibition and discussion in class or in the virtual forum of the subject, under the moderation of teacher issues related to the content of matter, as well as case studies.¡ (MD4) -Production of papers and reports individually or in group (MD5) For the elaboration of the work, at least 2 group tutorials will be organized.