Courses

Note: Students are required to take all six (6) core courses.

*Course exemptions may be granted to students with relevant prior academic qualifications or professional experience (subject to approval).

HR6001 AI Ethics (3 AUs)

This course provides the programme's foundation in structured ethical reasoning about artificial intelligence. Students are introduced to the major normative frameworks—consequentialist, deontological, virtue-based, and contractualist—and learn to apply them rigorously to the questions AI raises, including fairness and algorithmic bias, privacy and surveillance, transparency and explainability, autonomy and human oversight, and the allocation of responsibility for automated decisions. Designed for students from any disciplinary background and assuming no prior training in philosophy, it equips the whole cohort with a shared ethical vocabulary and analytical method on which the rest of the degree builds.

HR6002 Minds and Machines (3 AUs)

This course examines the conceptual foundations needed to think clearly about minds, machines, and the relationship between them. Drawing on the philosophy of mind and cognitive science, it addresses questions that underlie much public and policy debate about AI but are rarely made explicit: what intelligence, understanding, and consciousness are; whether, and in what sense, artificial systems might possess them; in what sense the human mind can be understood computationally. By taking seriously both what current AI systems do and what they do not do, the course helps students reason carefully about capabilities and limits that claims about AI often take for granted.

HR6003 AI Contexts (3 AUs)

This course traces the historical and social contexts of artificial intelligence, in doing so allowing students to think practically about the forces which shape it and allow it to be governed. Students are introduced to the different forms of AI which have been imagined and developed since the 1950s. They will trace the technological, social and political economic contexts which have made AI possible, and be introduced to the very wide-ranging debate about the future of AI in different societies. A central theme is the idea of AI as a normal form of trans-national technology, whose emergence can be traced alongside other technologies.

HR6004 Technical AI Literacy (3 AUs)

This course gives students a working, non-mathematical understanding of how contemporary AI systems are built and how they behave. It covers the essentials of machine learning and neural networks, the role of data and training, and the design and behaviour of modern systems such as large language models, with attention throughout to their capabilities, limitations, and characteristic failure modes (including bias, brittleness, and hallucination/confabulation). The aim is not to train engineers but to equip graduates from any background to engage credibly with AI systems and technical teams, to interrogate claims made about AI, and to bring informed judgement to its governance and use.

HR6005 Research Seminar Series (3 AUs)

Running fortnightly across both semesters, this course brings local and visiting academics into contact with the cohort to present and discuss current research at the frontier of AI ethics, governance, and the study of AI in society. It exposes students to a wide range of disciplinary approaches and live debates, models how rigorous interdisciplinary research is conducted, and helps students locate their own emerging interests, including in preparation for the capstone project.

HR6006 Business/Policy Incubator (3 AUs)

Running fortnightly across both semesters, this course is structured by talks and seminars delivered by practitioners from AI-related industry, government, and civil society. Students engage directly with the practical challenges of deploying AI responsibly: interpreting and applying governance frameworks, operationalising ethical principles within organisations, and translating between technical, commercial, and policy considerations. The emphasis is on practical judgement and real-world application rather than abstract analysis. 

Note: Students are required to select any two (2) electives.

*Elective offerings may vary each semester depending on availability of instructors and resources.

HR6101 AI Governance and Policy (3 AUs)

This course examines how AI governance emerges across states, corporations, platforms, and international institutions. Topics include platform governance, AI regulation and policy, algorithmic power, digital sovereignty, U.S.–China technological competition, generative AI governance, AI infrastructures, and the role of middle powers such as Singapore in shaping global AI ecosystems. The course combines theoretical frameworks with case studies and policy analysis to help students understand AI as both a technical and sociopolitical system.

HR6102 AI-Mediated Communication and Well-Being (3 AUs)

This course examines how generative AI is reshaping interpersonal communication, social relationships, and mental well-being. Students will critically engage with emerging research on AI companions, AI-mediated communication, and digital mental health, alongside the ethical and societal tensions these technologies raise. Drawing on perspectives from communication, human-computer interaction, and psychology, the course equips students to evaluate AI's communicative and affective dimensions and to think rigorously about its implications for individuals and communities.

HR6103 Applied AI Ethics (3 AUs)

This elective complements the core AI Ethics course by moving from frameworks to concrete cases, examining how ethical questions arise and are negotiated within specific domains of AI deployment. Drawing on detailed case studies (e.g., in healthcare and medicine, scientific research, hiring and the workplace, autonomous weapons in warfare, and content moderation) students learn to identify the ethically salient features of an application, weigh competing values and interests, and reason toward defensible, context-sensitive judgements. The course is oriented toward the kind of practical ethical reasoning that responsible-AI roles demand.

HR6104 Rationality and Extreme Risks (3 AUs)

The future development of AI systems is uncertain: many visionaries in the tech industry have predicted that advanced AI systems will bring enormous benefits; others have forecast mass unemployment, heightened inequality, and various kinds of global catastrophe. In the face of such uncertainty and such risks, what should we do, rationally speaking? This course seeks to answer that question, via the subfield of philosophy known as decision theory, which studies the question of how we rationally ought to make decisions, particularly in the face of risk and uncertainty. It will cover such issues as: how to assign probabilities to different risks, and what it means to do so; whether it is rational to be risk-averse or ambiguity-averse; whether leading theories of decision-making such as expected utility theory must be true; how we should respond to extremely low-probability risks that, if they eventuate, would be catastrophic; and how all of this applies to real-world decisions of how to design, deploy, and regulate AI. 

HD6014 AI in Interpretive Digital Research (3 AUs)

*cross-listed with MA in Digital Humanities

This course teaches students how to leverage generative pre-trained transformers (GPTs) such as ChatGPT, Claude or Gemini in the process of conducting qualitative research, addressing discrepancies between data quantity and detailed qualitative insights.

HD6021 Democracy in the Digital Age: Tools, Truths and Tactics (3 AUs)

*cross-listed with MA in Digital Humanities

This course explores the intersection of digital technologies, politics and democracy, examining how digital tools are transforming political campaigns, governance, and citizen engagement.

HD6023 Culture and the Transformative Effects of AI (3 AUs)

*cross-listed with MA in Digital Humanities

This course explores the transformative potential of artificial intelligence in influencing and reshaping cultural landscapes, examining AI's impact on existing traditions and practices.

HD6024 Visual Integrity and Ethics for Digital Scholarship (3 AUs)

*cross-listed with MA in Digital Humanities

This course explores ethical challenges associated with digital tools in humanities, focusing on ethics, visual integrity and implications of generative AI in scholarly work.

HD6026 AI, Robots and Humans (3 AUs)

*cross-listed with MA in Digital Humanities

This course examines the role of robots in society and evolving human-robot interaction dynamics, adopting a human-centred perspective on societal transformation.

TI6502 AI, ChatGPT and Machine Translation (3 AUs)

*cross-listed with MA in Translation and Interpretation

This interdisciplinary course explores the intersection of artificial intelligence, natural language processing, and translation studies. 

Note: Students are only required to choose any one (1) of the following formats.

Research Paper (6 AUs)

Policy Whitepaper (6 AUs)

Produce a policy-focused report that addresses real-world challenges arising from the development, deployment, or governance of AI. Students will apply ethical, societal, and governance perspectives to develop practical recommendations for organisations, policymakers, or institutions. Students will be offered opportunities for industry co-supervision, providing them with direct exposure to real-world challenges and professional practice.

Start-Up Proposal (6 AUs)

Design an innovative venture concept that addresses emerging opportunities or challenges in the AI ecosystem. Students will develop a proposal grounded in ethical, societal, and practical considerations, demonstrating how responsible AI can create value for organisations and communities. Students will be offered opportunities for industry co-supervision, providing them with direct exposure to real-world challenges and professional practice.

Multimedia Project (6 AUs)

Create a portfolio-quality multimedia work that communicates AI-related ideas, issues, or solutions to a broader audience. This format is ideal for students interested in communications, public engagement, media, or digital storytelling, while drawing on the programme's interdisciplinary perspectives on AI and society. Students will be offered opportunities for industry co-supervision, providing them with direct exposure to real-world challenges and professional practice.