LL214: Applied AI and Law

How we deploy Artificial Intelligence (AI) will define the next fifty years. AI offers the potential to transform and enhance human wellbeing, peace, and prosperity.

It also is an extremely disruptive technology which will change the way we do communicate, business and interact with one another. To successfully integrate AI into society we must ensure it is designed, developed, deployed, and used, in a manner that is safe, in such a way as to be human-centric, trustworthy, and responsible.  

Against the backdrop of this challenge, this course examines through three case-studies how we should develop legal responses to the challenge of AI. Today AI is used by the police, other law enforcement agencies, and even by private citizens to build smart surveillance networks through the use of live facial recognition cameras and so-called “hot spot” policing. This has the potential to impact or privacy and personal data and risks bias and error in design and deployment. The use of AI in law enforcement is our first case study. The second, the deployment of AI in medical practice and treatment, raises questions of autonomy, consent, confidentiality, and liability. The third case study looks at how public authorities deploy AI in ways which impact us all, including digital transformation of public administrative systems, the use of AI in the legal profession and the courts, and the deployment of AI at borders and to manage immigration. 

All three case studies raise vital questions of human rights and dignity. Questions of autonomy, privacy, freedom of expression, freedom of assembly, liability for harm and of course public safety. AI changes the legal landscape and how lawyers, and anyone interested in how our society is regulated, will need to adapt to this new landscape. These case studies will be the lens through which we examine key normative questions: What is the role of law in this new AI empowered environment? Can lawyers develop a co-ordinated legal response? What areas should lawyers be focusing upon? 

This course does not require an in-depth understanding of digital technology or AI systems – we are primarily interested in the implications of the use of information technology, AI and Machine Learning, and the intended and unintended consequences of regulating that use. It may be taken alongside LL204 The Foundations of AI Law and Regulation to allow students to develop an insight into both the development and deployment of AI Law and Governance. Each course may also be taken independently.

Students who receive an offer for this course are also eligible to apply for the Academic Director's Scholarship.

Prerequisites: An introductory law course or ME102: The Ethics of Data and Artificial Intelligence. This course does not require an in-depth understanding of Artificial Intelligence.

Level: 200 level. Read more information on levels in our FAQs

Fees: Please see Fees and payments

Lectures: 36 hours

Classes: 18 hours

Assessment: One examination and one essay

Typical credit: 3-4 credits (US) 7.5 ECTS points (EU)

Please note: Assessment is optional but may be required for credit by your home institution. Your home institution will be able to advise how you can meet their credit requirements. For more information on exams and credit, read Teaching and assessment

This course is suited to those who are interested in developing a deeper understanding of the implications of the deployment of Artificial Intelligence (AI) in practice, the intended and unintended consequences of that use, and the role of lawyers and the legal profession in regulating that use.

This course would be particularly useful to those considering a career in the field of Digital Law (sometimes called TMT Law (Technology, Media and Telecommunications law)) including AI governance, digital rights, public law, and cyber security.

• Critically evaluate contemporary developments in law relating to the deployment of AI and Machine Learning
• Using case studies display an understanding of how these developments relate to one another
• Examine the competing regulatory, political and social debates surrounding rules for the deployment of AI and machine learning in practical situations
• Explore and evaluate these arguments in terms of internal coherence and practical outcomes
• Draw on the analysis and evaluation contained in primary and secondary sources 

The design of this course is guided by LSE faculty, as well as industry experts, who will share their experience and in-depth knowledge with you throughout the course.