Course Listing

Artificial Intelligence, Information Science & Law
Last Updated Date:   8 July 2025


5 Units,  Semester 2

Course Description:
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, including large language models and agentic AI, deploys them in basic scenarios, studies the reasons for their acceptance or rejection, and analyses them for their benefits, limitations and dangers. Students completing this course are expected to be able to deploy many of these AI and IS techniques to legal problems

Course Convenor: A/P Daniel Seng Kiat Boon

Co-teacher(s): NA

Course Codes: LL4283V / LL5283V / LL6283V / LLJ5283V

Contact Hours: 3 hour weekly seminar

Workload: 3 hours

Mode of Assessment: Class Participation - 10%; Programming Assignments - 15%; Project Work - 25%; Written Assignment (6000 words excld footnotes) - 50% [Due: Wednesday, 15 April 2026 (3pm)]

Preclusions: LL4447V/LL5447V/LLJ5447V/LL6447V Law and Data Science
LL4530V/LL5530V/LLJ5530V/LL6530V Law and Natural Language Processing

Prerequisites: (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

Examination Date: Different Mode of Examination

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