Minor in Human-AI Systems
As AI systems become embedded in social, cultural, and institutional life, understanding and designing human-AI interactions has become a core competency across sectors. This programme equips students in the humanities and social sciences with the quantitative, computational, and AI skills to navigate these systems, complementing their primary majors with a structured X+AI pathway. Graduates will be prepared for the evolving demands of research, policy, and professional practice across sectors.
The curriculum develops fluency with computational and AI methods spanning text, data, and geospatial analysis, equipping students to solve disciplinary problems, select appropriate tools, and interpret results critically. Emphasis is placed on combining technical rigour with interpretive depth and ethical practice, preparing students to work responsibly at the intersection of human inquiry and AI capability by evaluating outputs for limitations, uncertainty, and appropriate use in context. Students gain hands-on experience working with diverse data sources, learning to extract meaningful insights while maintaining scholarly integrity and ethical standards. Graduates will emerge prepared for diverse career paths in academia, public service, think tanks, cultural institutions, media organizations, and private sector roles requiring analytical thinking, data literacy and AI competences. The programme provides opportunities for students to orchestrate AI-enabled workflows for multi-step disciplinary questions. By combining technical expertise with domain insight and governance awareness, students develop unique interdisciplinary capabilities to address complex, real-world challenges in an increasingly data- and AI-rich environment.
Programme Requirements (Cohort 2026 onwards)
Students must pass a minimum of five courses (20 units) from the list of the Minor, including
(1) one compulsory core course;
(2) one AI Stewardship & Ethics course;
(3) two Data-, AI-, and Discipline-centric Electives; and
(4) one UROP serving as a practical capstone, with topics and scope approved by the Minor convenors.
(1) Core Course (Compulsory, 4 Units)
NM2228 Data Intelligence for Social Applications
(2) AI Stewardship and Ethics — select 1 (4 Units)
GI3101 GeoAI for Good
NM3254 Artificial Intelligence, Algorithms and Governance
PH1201 AI, Algorithms, and Ethics
PH3401 AI Safety and Alignment
SC3210 AI and Society
(3) Data-, AI-, and Discipline-centric Electives — select 2 (8 Units)
BT1101% Introduction to Business Analytics
EC2314 Discovering Economics through Data
EC4308 Machine Learning and Economic Forecasting
EC4501 Economics and Computation
EL2216 Humans vs. Language Models: Linguistic Behaviours
EN2215 Literature and Culture in the Age of AI
GE2234 Geospatial Data Collection and Digital Mapping
GI4101 GeoAI in Urban Applications
GI4102 Computational Simulation for Social Science
HS2931 Smart City / Intelligent Humans
NM3253 Fandoms to Algorithms: K-Pop, Data and Culture
PH3245 Language and Thought
PL4245 Data Science for Psychology: Methods and Applications
PS4344 Artificial Intelligence and Public Policy
SW3224 CTRL+SHIFT+FUTURE: Social Work and Technology
SW4233 Digital Technologies in Children and Youth Services
TS2244 Theatre, Big Data and Artificial Intelligence
(4) Capstone – UROP (4 Units)
Within the UROP format, students will undertake a supervised research project that draws on the methods, ethics, and domain knowledge developed across the programme, translating analytical competence into a substantial piece of applied or scholarly work. Students should demonstrate that they can orchestrate data analytical tools and AI insights to solve complex real-world problems and drive data-informed decision-making in their field. The UROP topic and scope should be approved by the Minor convenor.