70227 - Information Technology and Law

Learning outcomes

At the end of the course, the student: - acquires awareness of the existence of legal problems related to new technologies; - understands how to develop and use (as a professional or user) new technologies in compliance with laws and regulations; - is able to find qualified sources and autonomously interpret the current legislation applicable to his/her area of interest; - develops the ability to manage projects that involve legal knowledge; - interacts in a qualified manner with lawyers and legal experts.

Course contents

Professional Responsibility of the Computer Engineer

IT consulting. Programmer liability. Software development contracts. Design and engineering errors. Liability in safety-critical systems. Insurance and professional risk management

Internet of Things (IoT): Privacy, Data, and Digital Platforms

Emerging technologies. Regulation of digital platforms from the perspectives of users, developers, and businesses. Smart technologies. E-commerce. Surveillance technologies. The role of the Data Protection Officer (DPO). Privacy by Design and Privacy by Default. Cookies, profiling, and algorithmic advertising. Virtual environments and digital identity. Key regulations and legal frameworks: Data Act, Data Governance Act, Digital Services Act (DSA), General Data Protection Regulation (GDPR), and Digital Markets Act (DMA). Practical exercises

Artificial Intelligence

Liability for automated decision-making. Algorithmic bias and discrimination. Accountability of AI systems. Generative AI and legal risks. Digital twins in the context of Industry 4.0. Prompt engineering and professional responsibility. Foundation Models and General-Purpose AI (GPAI). Key regulations and legal frameworks: AI Act (including the latest guidelines). Practical exercises.

IT Governance
Regulatory frameworks and Project Management models. Smart Cities as a case study in governance, artificial intelligence, and data protection. Smart contracts and blockchain technologies. Practical exercises.

Cybercrime
Professional roles in cyber law engineering. Types of cybercrime. Social engineering. Cyber intelligence, cyber espionage, and cyber terrorism. Digital forensics. Incident response. Data breach notification obligations. Cyber resilience. Key regulations and legal frameworks: Cybersecurity Act, Cyber Resilience Act, and Network and Information Systems Directive 2 (NIS 2).

Patents and Copyrights
Intellectual Property Rights. Open-source software. Video games and copyright law. Software licensing models (GPL, MIT, Apache). Software patents. Copyright and generative AI. Datasets and licensing.

Case Studies
Analysis and discussion of real-world cases

 

Readings/Bibliography

The supporting teaching documentation will consist of the lecture slides and the handouts/papers provided by the teacher through the Virtual Learning Environment platform.

Books for non-attending students, in addition to the supporting teaching documentations on the VLE:

• Amidei A. Ruffolo U (2024), Diritto dell'intelligenza artificiale. Responsabilità. Contratto. Regolazione. Veicoli autonomi (Vol. 1) (Luiss University Press)
• Amidei A. Ruffolo U (2024), Diritto dell'intelligenza artificiale. Proprietà industriale e intellettuale. CorpTech. Giustizia predittiva. Transumanesimo. AI generativa. Metaverso. (Vol. 2) (Luiss University Press)

 

 

Teaching methods

Frontal lessons (blended mode) held by the teacher. Practical cases will be analyzed and exercises will be carried out during the lessons.

The lessons will also be recorded and published on Virtuale.

Teaching innovation strategy
Emphasis on learning-by-doing with a focus on practice. The student-centered model allows sessions with specific group work activities.

Teaching innovation methodology
In particular, the innovative training activity, which will also be developed through meetings with professionals in the sector and group work, will be based on two main methodologies (guided by the teacher): a) one based on investigation, which stimulates the student to formulate investigable questions, carry out useful actions to solve problems and understand the phenomena presented more deeply; b) one of group analysis, aimed at allowing individual students and groups to be more receptive to new ideas, evaluating different points of view, and to develop them in a creative and constructive way

  

Assessment methods

For attending students (minimum attendance of 70% of classes, except in duly justified cases), assessment will be carried out throughout the course and will consist of the following components:

1. APPLICATION

   The quality of the group laboratory exercises carried out during class will be taken into account. These activities are designed to apply and consolidate the knowledge and skills acquired throughout the course. An integral part of the assessment process is the sharing, discussion, and critical reflection on the work produced within the group.

   Note: Course handouts may be used during these exercises. The substantial use of AI tools is not permitted. Any violation will result in the student being required to complete an individual replacement exercise on a different topic and without access to the course handouts.

2. CONTENT KNOWLEDGE

   Students will take an individual test covering one topic from the syllabus, not addressed during the practical exercises.

   Note: The use of AI tools, as well as any electronic device, is strictly prohibited.

3. STUDENT'S PERSONAL INTEREST

   Individually or in pairs, students will present a short research project to the class on a topic of particular personal interest related to the course.

   Note: Limited, declared, and non-substantial use of AI is permitted solely for support activities, such as summarization and rephrasing.

The final grade will be officially recorded and expressed on the Italian 30-point grading scale.

Non-attending students will be assessed on the entire course syllabus, using the materials provided by the instructor during the lectures and the recommended textbook.

Students must contact the instructor in advance to agree on the examination format and assessment procedures.

Note: The use of AI is prohibited. Any use of AI constitutes a violation of academic integrity.

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Teaching tools

Possible tools:

Digital presentations, videos, short webinars with external experts, publication of handouts, use of a forum for ongoing questions and clarifications, collaborative writing and communication.

Multimedia tools: Virtual, videoconferencing tool, Asynchronous communication and collaboration apps, Investigation and analysis tools

Office hours

See the website of Luisa Dall'Acqua