Regulating AI: Law, Policy and Ethics
| Module title | Regulating AI: Law, Policy and Ethics |
|---|---|
| Module code | LAWM181 |
| Academic year | 2023/4 |
| Credits | 15 |
| Module staff | Dr Robin Pierce (Convenor) |
| Duration: Term | 1 | 2 | 3 |
|---|---|---|---|
| Duration: Weeks | 11 |
| Number students taking module (anticipated) | 20 |
|---|
Module description
Artificial intelligence has ushered in the so-called “The Fourth Revolution”. The expected benefits from increasing use of automated systems and devices span across sectors – from healthcare and banking to law enforcement, scientific research, and legal practice. However, the use of AI raises many legal, policy, and ethical issues, giving rise to perhaps the greatest challenge -- how to regulate AI? Starting with a foundation in principles of regulation of technology, you will examine legal and policy implications of deployment of AI to increase accuracy, efficiency, and profit. The module provides you with an examination of regulatory approaches to governing the rapidly growing use of AI across sectors.
Module aims - intentions of the module
The primary aim of this module is to facilitate a solid understanding of the legal, policy and ethical issues that arise with the introduction of AI applications in different contexts, and how these create challenges for effective regulation. Students will gain a firm grounding in the EU approach as well as other jurisdictions, including the UK, US, and selected countries in South America, Africa, and Asia. Close examination of major regulatory proposals, such as the EU AI Act, alongside other key legislations such as the GDPR, AI Liability Directive, and the Digital Governance Act, will allow students to develop an understanding of the challenges in regulating a rapidly evolving technology. This module aims to provide students with the tools to identify and analyse risks attending the use of AI in various sectors, the regulatory challenges, and the regulatory approaches to governing AI that are being deployed around the globe.
This module is a firm foundation for those wishing to engage in policy debates about the use and regulation of AI at various levels. The grounding in the theory of regulation of technology will serve those wishing to focus on emerging technologies in various career paths.
Intended Learning Outcomes (ILOs)
ILO: Module-specific skills
On successfully completing the module you will be able to...
- 1. demonstrate a comprehensive knowledge and thorough understanding of the main principles and theories of the regulation of technology and how they apply to regulating AI
- 2. identify, examine, analyse, interpret, and critically evaluate current and proposed laws dealing with AI
- 3. independently examine, research and analyse current and emerging legal, policy, and ethical issues relating to AI
ILO: Discipline-specific skills
On successfully completing the module you will be able to...
- 4. demonstrate comprehensive knowledge and understanding of the range of legal and policy issues arising from the use of AI and explain interrelationships with values, principles, institutions, and procedures
- 5. demonstrate comprehensive knowledge of legal concepts and their contextual, social and commercial implications
- 6. apply legal knowledge to a problem/ case study and to suggest a conclusion supported by relevant arguments
- 7. integrate and assess information from primary and secondary legal sources using appropriate interpretative and analytical techniques
ILO: Personal and key skills
On successfully completing the module you will be able to...
- 8. manage relevant learning resources/ information
- 9. independently develop arguments and opinions with minimal guidance
- 10. critically assess regulatory challenges
- 11. communicate and engage in debate effectively and accurately, orally and in writing, in a manner appropriate to the discipline
Syllabus plan
- Principles and Theories of Regulation of Technology
- Introduction to AI, Machine Learning, and Algorithms
- Algorithmic Discrimination
- Law and policy regarding predictive uses of AI
- Data protection and AI
- Regulatory challenges regarding AI
- Case Study: Regulating AI in healthcare and medicine
- Proposals for the regulation of AI
Learning activities and teaching methods (given in hours of study time)
| Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
|---|---|---|
| 15 | 135 | 0 |
Details of learning activities and teaching methods
| Category | Hours of study time | Description |
|---|---|---|
| Scheduled Learning and Teaching | 15 | 10 weekly 1.5 hour seminar: each topic will be introduced by a lecture. Students are expected to prepare to discuss assigned questions and engage in general discussion. |
| Guided Independent Study | 60 | Assigned seminar readings |
| Guided Independent Study | 10 | Preparation of one debate |
| Guided Independent Study | 20 | Formative assessment preparation |
| Guided Independent Study | 45 | Summative assessment preparation |
Formative assessment
| Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|
| Formative Essay | 1000 words | 1-11 | Oral and Written |
Summative assessment (% of credit)
| Coursework | Written exams | Practical exams |
|---|---|---|
| 100 | 0 | 0 |
Details of summative assessment
| Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|---|
| Essay | 100 | 2000 words | 1-11 | Oral and Written |
Details of re-assessment (where required by referral or deferral)
| Original form of assessment | Form of re-assessment | ILOs re-assessed | Timescale for re-assessment |
|---|---|---|---|
| Essay (2000 words) | Essay (2000 words) | 1-11 | Referral/Deferral period |
Indicative learning resources - Basic reading
- Black, Julia, and Andrew Douglas Murray. "Regulating AI and machine learning: setting the regulatory agenda." European journal of law and technology 10.3 (2019).
- Morgan, Bronwen, and Karen Yeung. An introduction to law and regulation: text and materials. Cambridge University Press, 2007.
- Veale, Michael, and Frederik Zuiderveen Borgesius. "Demystifying the Draft EU Artificial Intelligence Act—Analysing the good, the bad, and the unclear elements of the proposed approach." Computer Law Review International 22.4 (2021): 97-112.
- Parikh, Ravi B., Ziad Obermeyer, and Amol S. Navathe. "Regulation of predictive analytics in medicine." Science 363.6429 (2019): 810-812.
- Madiega, Tambiama André. "Artificial intelligence act." European Parliament: European Parliamentary Research Service (2021).
Indicative learning resources - Web based and electronic resources
- Case law of the European Court of Justice available at: http://curia.eu
- Additional items will be added to ELE on a weekly basis.
- Indicative learning resources – Online databases: Westlaw, Lexis, Eurlex, HeinOnline.
Indicative learning resources - Other resources
- Selected articles
- Newly published articles
| Credit value | 15 |
|---|---|
| Module ECTS | 7.5 |
| Module pre-requisites | None |
| Module co-requisites | None |
| NQF level (module) | 7 |
| Available as distance learning? | No |
| Origin date | 12/04/2023 |
| Last revision date | 12/04/2023 |
