Your accelerated and flexible path to leadership in the age of AI.
Lead your organisation into the AI-powered future, with confidence.
Future-proof your career in a rapidly changing world.
Join a global community in the heart of innovation.
Supporting your studies, health, finances, and more.
Empowering your professional growth with coaching, support, and industry connections.
Discover what puts LSI at the forefront of forging leaders for a tech-driven world.
Innovative education that blends traditional excellence with modern, future-focused strategies.
Aspiring to play a key role in shaping the future of education? Join our journey.
This course equips you to navigate the transformative role of AI in public service, blending foundational knowledge, practical applications, and ethical considerations. You’ll gain a deep understanding of AI’s capabilities, limitations, and its potential to revolutionize governance and public service delivery.
You’ll explore how AI has evolved, its core concepts, and its current technological landscape. Learn to design workflows that balance AI efficiency with human oversight, leveraging its strengths while managing risks. Through real-world case studies, you’ll discover how AI enhances equity, efficiency, and accessibility across public sectors.
The course also addresses critical ethical and societal issues, such as bias, fairness, transparency, privacy, and workforce transformation. You’ll understand the regulatory frameworks that guide responsible AI use, enabling you to make informed decisions that balance innovation with accountability.
By combining theory, practice, and ethical guidance, this course prepares you to harness AI effectively and responsibly, empowering you to drive meaningful improvements and navigate AI’s impact on public services with confidence.
The methods of teaching and learning for this module are based on the School's Short-course 5 teaching system, consisting of the following activities.
This is the first weekly session, dedicated to providing a comprehensive introduction to the module. The module leader will present an overview of the subject, elucidating its importance within various digital engineering professions and its interrelation with other modules. Students will need no preparation ahead of attending this session.
The module leader will provide a structured breakdown of the content to be covered in the subsequent 9 sessions. Students will also receive an outline of the essential reference materials, alongside suggestions for supplementary reading. The format and criteria for the summative assessment will be delineated, followed by a dedicated period for questions and answers.
A recording of the session will be available to facilitate async engagement for any other student who missed the class, also offering an opportunity to review the content again.
Our institution's approach to teaching is primarily based on flipped learning. Ahead of each weekly session (Workshop/Lab), students will be required to study the essential concepts that are used in the coming session so they are familiar with the theories and ideas related to that session. The study material will be in the form of written content, illustrations, pre-recorded lectures and tutorials, and other forms of content provided through the AGS.
This content is self-navigated by the students, accommodating different learning styles and schedules, allowing students to watch or listen to them at their own pace and review them as needed.
Once each concept of the theory is studied, students will be prompted to engage in formative assessment with instant AI feedback. They include multiple-choice questions, socratic questions and answers, written questions, role-play and other AI-assisted practice scenarios.
The purpose of this automated formative assessment is to provide students with immediate feedback on their understanding of module material and highlight any areas that need support or further study. They are also used to track student progress, boost motivation and promote accountability.
In this learning activity, students explore recent real-world case studies relevant to their course topic. The case studies will have been selected and curated by the module leader to represent up-to-date examples. They guide students through key details, contextual factors, and outcomes. This approach enhances students' understanding of current industry trends, challenges, and solutions, preparing them for real-world scenarios they may encounter in their future careers.
The learning experienced will be augmented by AI (virtual private tutor) allowing the students to critically engage with the content and discuss the case studies.
This activity challenges students to engage with the reference material and independently explore and analyse academic literature related to the course topic. Students are expected to select relevant sources, practice critical reading skills, and where applicable technical skills, and synthesise information from multiple references. This is an opportunity to enhance research abilities, critical thinking, and self-directed learning skills while broadening and deepening subject knowledge.