Why study this course?
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This micro-credential provides a critical examination of the safety, ethics and risks associated with generative AI systems and their deployment in public administration and the private sector.
Students will evaluate algorithmic reliability, quantify demographic bias, and construct formal threat models, transitioning from theoretical principles to applied frameworks and real-world examples.
Developed in collaboration with the Scottish Government, this course enables work-relevant, rigorous learning with immediate professional application.
Through this course you will:
- Engage in work-relevant learning, such as through case studies, links to relevant policies and practitioner interviews.
- Demonstrate in-demand knowledge, skills and competences, underpinned by rigorous quality assurance.
- Develop the capabilities required to change, learn and adapt continuously.
By the end you'll be able to:
- Critically evaluate the safety, ethics, and risks associated with generative AI systems and their deployment in public administration or the private sector.
- Assess algorithmic reliability and demographic bias, and appraise formal threat models to evaluate and adapt existing organisational governance frameworks.
- Critically reflect on the integration of these concepts into autonomous professional practice and organisational strategy.
Credits and progression
10 credits at SCQF level 11 (St Andrews level: 5000).
Credits attained are eligible for stacking towards a new Postgraduate Certificate in Artificial Intelligence.
Assessment
Students must submit an AI integration portfolio and pass an end-of-module quiz. The module grade will be derived from the quiz, but students must pass both elements of the assessment.
Preparation
Students with no prior knowledge of generative AI may wish to take the Introduction to Generative AI micro-credential beforehand.
Course details
Course leader
Dr Andrew O'Malley is Head of the Division of Education at the University of St Andrews School of Medicine. His work concerns the responsible use of generative AI in professional education and assessment, including research on demographic and skin-tone bias in AI-generated content and on the governance questions that arise when these systems are deployed in public services. He writes and speaks regularly on AI in education at international academic and commercial events. He sits on Elsevier’s AI advisory board, is an OpenAI Community Leader, and is the founder of SimPatient, an AI simulated patient platform used by medical schools in the UK and internationally.
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Establishes a shared vocabulary for what AI systems actually are, and introduces the five pillars used across the module: reliability, alignment, transparency, ethics and governance.
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Distinguishes reliability, robustness and interpretability; examines failure modes (hallucination, distributional fragility, opacity) and pre-deployment evaluation.
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How training data shapes outputs in invisible ways; applying formal frameworks to detect demographic bias and assess impact on under-represented groups.
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How AI can be used as a tool to cause harm to individuals and organisations, and how AI systems are vulnerable to manipulation.
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Distinguishing legislation, regulation and guidelines; comparing the EU AI Act, UK, OECD and Scottish frames; auditing a deployment against the most relevant framework.
What it will lead to
AI is transforming how public services and businesses operate, but the critical, ethical skills to govern it responsibly haven't kept pace. The Scottish Government has identified this gap directly: Skills Development Scotland's Digital Economy Skills Action Plan, the Digital Strategy for Scotland, and the Delivery Plan for Sustainable Digital Public Services (2025-28) all point to the need for people who can think critically and ethically about AI and data, not just use it.
This course puts you ahead of that curve. Whether you're in Scottish Government or another sector, now is the moment to build the skills that national policy says are essential and to put yourself at the front of a fast-moving conversation about how AI should be governed.
Why St Andrews?
When you study with the University of St Andrews, the top university in the UK and Scotland according to The Times and Sunday Times University Guide 2027, you'll join a global community of learners as you explore the complex issues of AI governance.
This expert-led online course, taught by leading academics, provides the same rigorous learning experience as our in-person courses, with the flexibility to study at your own pace.
With dedicated support throughout your studies, you'll gain the insights needed to navigate today's challenges from the comfort of your own home.
Designed for you
Wherever you are, you can take St Andrews with you. Online courses at the University of St Andrews combine all the benefits of studying at one of the world's oldest and best universities with all the advantages of flexible, personalised learning.
The development of this course was funded through the Micro-credentials Pilot for Scottish Government Civil Servants Project (2026).
Entry requirements
No formal entry requirements. Some familiarity with AI tools such as Copilot is beneficial but not required.
English proficiency
This course has no formal entry requirements but is designed for applicants who have a good level of English. You will be asked to self-rate your English language proficiency against the standard undergraduate English language entry requirements. You should have at least a low C1 CEFR score overall, with at least a high B2 level in each of the four skills of reading, writing, listening and speaking.
Fees and funding
£800
Through support from Upskilling Scotland, we have up to 25 fully funded places available for this micro-credential.
You can view eligibility criteria during your application.
Contact us
School of Medicine
University of St Andrews
North Haugh
St Andrews
KY16 9TF
Email: medicine@st-andrews.ac.uk
Phone: +44 (0)1334 46 3599
Website: The School of Medicine
Legal notices
Admission to the University of St Andrews is governed by our Admissions policy
Information about all programmes from previous years of entry can be found in the course archive.
Curriculum development
As a research intensive institution, the University ensures that its teaching references the research interests of its staff, which may change from time to time. As a result, programmes are regularly reviewed with the aim of enhancing students' learning experience. Our approach to course revision is described online.
Tuition fees
The University will clarify compulsory fees and charges it requires any student to pay at the time of offer. The offer will also clarify conditions for any variation of fees. The University’s approach to fee setting is described online.
Page last updated: 12 October 2026