MVV347K Artifical Intelligence, Law, and Governance

Právnická fakulta
jaro 2024
Rozsah
0/1/0. 3 kr. Ukončení: k.
Vyučující
Dr. Michaela MacDonald (cvičící), prof. JUDr. Ing. Michal Radvan, Ph.D. (zástupce)
prof. JUDr. Ing. Michal Radvan, Ph.D. (cvičící)
Garance
prof. JUDr. Ing. Michal Radvan, Ph.D.
Právnická fakulta
Kontaktní osoba: Mgr. Věra Redrupová, B.A.
Dodavatelské pracoviště: Právnická fakulta
Rozvrh seminárních/paralelních skupin
MVV347K/01: Po 22. 4. 18:00–19:40 041, Út 23. 4. 16:00–17:40 041, 18:00–19:40 041, St 24. 4. 18:00–19:40 041, Čt 25. 4. 18:00–19:40 041, M. MacDonald
Omezení zápisu do předmětu
Předmět je určen pouze studentům mateřských oborů.

Předmět si smí zapsat nejvýše 30 stud.
Momentální stav registrace a zápisu: zapsáno: 39/30, pouze zareg.: 5/30
Mateřské obory/plány
předmět má 38 mateřských oborů, zobrazit
Cíle předmětu
The evolving area of AI and robotics gives rise to many ethical and legal questions over the status of robots, the rights and responsibilities arising from their use and liability for any harm caused. The course will explore the issues of legal personhood, the protection of autonomous agents and their outputs through IP law, the responsibilities arising from data use and the various approaches to allocating responsibility and liability.

The course aims:
• To acquaint students with both regulatory as well as non-regulatory mechanisms (standards and best practices) with regards to development and deployment of AI technologies across different sectors of their application.
• To provide understanding of potential legal, regulatory, and practical challenges in relation to development and deployment of AI, including accuracy, accountability, fairness and discrimination.
• To enable students to reflect on the benefits and limitations of the governance frameworks when developing and deploying AI applications and expert systems.
Výstupy z učení
Sophisticated robots and other manifestations of artificial intelligence have left the research lab and arrived in our homes, businesses and public spaces. This course examines the wide spectrum of ethical, public policy and legal issues that needs to be addressed by designers, manufacturers and legislators alike.

Learning Outcomes
• Demonstrate a broad understanding of the legal issues created by autonomous technologies, and an awareness of the range of legal issues that are affected
• Have extensive knowledge of existing legal responses, both through legislation and relevant case law
• Comprehend and analyse the interaction between economic, psychological, political, societal and ethical issues that regulators face when dealing with autonomous technologies and identify legislative initiatives and reform proposals both nationally and internationally.
Osnova
  • Lecture 1 – Introduction to the course
  • The course will start with an overview of the wide scope of AI applications and significant milestones in their development and deployment. It proceeds to outline core concepts and modes of governance that can effectively address potential risks. The host of legal and ethical dilemmas include discrimination, privacy, agency, authenticity, cybersecurity and democracy.
  • • Should there be restrictions on what AI can do?
  • • Should we be concerned about AI taking over? Who is responsible?
  • • Should there be global agreements?
  • Lecture 2 – Potential Legal Risks
  • This session explores specific areas and justifications for regulating AI applications, including:
  • • AI-enabled decisions and predictions
  • • Cybersecurity
  • • Facial recognition and computer vision
  • • Autonomous vehicles
  • • Malicious AI, AI-enabled fakery, and forgery
  • • General AI (if possible and implications requiring regulation)
  • The global response has varied in jurisdictions across the world, and we will explore the range of legal and regulatory responses to the ethical and legal risks posed by the development and deployment of AI, focusing on China, EU, US, and other countries where relevant. What role do regulation, self-regulation, regulatory guidance, standards, and best practice play in this field?
  • Lecture 3 – Governance of AI
  • As outlined in previous sessions, a number of governance models co-exist and complement each other. It is important to evaluate their efficiency and suitability with regards to a specific industry and AI application.
  • Application of hard law in specific areas (i.e., already regulated)
  • • Autonomous vehicles
  • • Healthcare
  • • Finance
  • • Cybersecurity
  • Application of privacy law
  • Application of criminal laws
  • Application of antitrust / competition laws
  • Legal precedents from around the world
  • The role of contract law and insurance to manage risk for developers and other participants
  • Application of soft law
  • • e.g., Singapore Model AI Governance Framework
  • • Good data accountability practices
  • o Data lineage issues
  • o Ensuring data quality
  • o Minimizing inherent bias
  • o Different datasets for training, testing, and validation
  • • Algorithms and Models
  • o Enhancing the transparency and trustworthiness of algorithms in AI
  • o The ‘black box’ problem
  • • Other foundational AI ethical principles
  • o EU draft ethic guidelines for trustworthy AI
  • o China – development of model framework
  • Lecture 4 – Applicability of IPRs to AI and AI outputs
  • This lecture will explore the concept of creativity and the capacity to invent and the scope for protecting AI-generated works and inventions.
  • Truly autonomous computer system – personhood and attribution issues
  • • Developments in the EU, US, China
  • Specific IPR-related considerations with regards to AI include:
  • • Copyright
  • • Text and data mining
  • • Patents
  • • Confidentiality and trade secrets
  • • Protectability of algorithms as such
  • • Works and inventions generated with the assistance of AI tools
  • Lecture 5a – Case study
  • In the first part of the lecture, we will use a case study to demonstrate the issues and challenges that businesses, individuals and policymakers need to navigate in order to provide a robust legal and regulatory framework where AI systems and applications can thrive, without posing unnecessary risks.
  • Lecture 5b – Future developments and policies The second part will provide an opportunity to discuss and formulate the main principles for governing AI.
Literatura
  • Reading list will be provided.
Výukové metody
lectures and discussions
Metody hodnocení
Attendance. Participation. Written assignment.
Vyučovací jazyk
Angličtina
Další komentáře
Studijní materiály
Předmět je vyučován jednorázově.
Předmět je zařazen také v obdobích jaro 2022, jaro 2023.
  • Statistika zápisu (nejnovější)
  • Permalink: https://is.muni.cz/predmet/law/jaro2024/MVV347K