Advancements in computer science have made it possible to deploy information technology to address legal problems. Improved legal searches, fraud detection, electronic discovery, digital rights management, and automated takedowns are only the beginning. We are beginning to see natural language processing, machine learning and data mining technologies deployed in contract formation, electronic surveillance, autonomous machines and even decision making. This course examines the basis behind these technologies, deploys them in basic scenarios, studies the reasons for their acceptance or rejection, and analyses them for their benefits, limitations and dangers.

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(1) NUS Compulsory Core Law Curriculum or common law equivalent;
(2) Law and Technology [LC2017/LL5493/LLJ5493/LL6493]
(3) GCE "A" Level Mathematics (at least or its equivalent), with basic understanding of probability theory and linear algebra.
(4) Intermediate to advanced programming skills in Python are required, and will be assessed early on in the module by way of a graded quiz. The use of intermediate Python and specialised Python libraries will be assumed.

Students will require access to a computer (remote desktop software is workable) with at least the following hardware requirements:
- 64-bit OS (Win 10+, Mac OS 10.15+ or Linux 22.04+ 64-bt)
- 4-core CPU (6+ cores recommended)
- 8GB RAM (16GB recommended

This course focuses on the status of digital creativity within the EU copyright system. It aims to reflect on the expansion of exclusive rights which has necessitated a call for fundamental rights, namely freedom of expression and arts, at both national and EU level, to support digital creativity. The subject considers theoretical rationales of supporting user creativity online, and recent EU regulation (e.g. Article 17 Digital Single Market (DSM) Directive, Digital Services Act (DSA), and the AI Act and referrals to the European Court of Justice.

NUS Compulsory Core Law Curriculum or common law equivalent.

Some knowledge of Intellectual Property is preferred; students should ideally have taken a course in intellectual property or concurrently enrolled in one.

Individuals today face increasing risks to the privacy and security of their personal information and there are growing concerns over how such information may be used or misused. Many countries have enacted new data privacy laws, or amended their existing laws, in recent years to enhance the protection of individuals’ personal information. While there are often many similarities in the specific requirements of such laws, countries’ objectives and approaches often differ with some focusing primarily on the protection of individual rights and freedoms, others emphasising the role of data in the digital economy and cross-border trade and yet others leveraging their laws to enhance national security and promote national development. Companies operating globally are thus required to navigate an increasingly complex legal environment.

This course will explore the main theories of data privacy as well as a cross-section of national data privacy laws from North America, Europe and Asia. As this area of law continues to face new challenges arising from developments in business and technology, this module will conclude by examining the role of data privacy laws in regulating emerging technologies.

This course introduces students to the exciting world of intellectual property arbitration. Traditionally thought of and taught as distinct areas of law, the overlap between IP rights and recourse to arbitration for the protection of those rights has grown significantly in recent years. This pioneering course is not currently offered in any other leading law school in the world. It is designed for students with little to no knowledge of IP law. It is also designed for students with an interest in arbitration, regardless of the level of their pre-existing knowledge of arbitration.

This course offers a hands-on introduction to legal data science and aims to improve students' understanding of:
(1) legal issues that involve technology;
(2) the technologies that underlie many legal–tech products; and
(3) how technology can be used in empirical legal research.
This class also provides practice in the logical reasoning skills important to many areas of legal practice and improves students’ abilities to communicate with clients in high-tech industries.

No computer programming experience is required. Class operates in a "flipped" manner with weekly homework and readings, and intensive classroom activities that are designed to help students overcome learning obstacles.

The recent developments in natural language processing (NLP) methods and the increasing use of artificial intelligence (AI) chatbot tools invite us to question their possible use in various domains, including the legal domain. This course aims to introduce participants to the fundamentals and emerging paradigms of text analysis, machine learning and NLP with a focus on the unique interdisciplinary issues that arise in the application of these methods to the analysis of legal textual data. Participants will utilize NLP methods to examine legal textual data with enough theory to help with intuition-building. Basic knowledge of Python programming is expected.