Applied Artificial Intelligence for Security MSc Modules
Core modules
This module is designed for students from non-STEM backgrounds who want to understand how programming and machine learning are used in real-world professional settings. It is particularly suited to learners from areas such as law, public policy, security or related fields who want to develop practical applied AI skills.
Students will begin by learning the basics of a modern programming language and how to write simple, readable programs that work with structured data. The focus is on practical problem-solving; students will learn how to think algorithmically, understand what code is doing, and explain their approach clearly.
Building on this foundation, the module introduces core machine learning ideas through applied examples drawn from professional and societal contexts. Students will learn how to define a machine learning problem, implement a practical solution, and evaluate how well it works in context. Throughout the module, students will be encouraged to think critically about the strengths and limitations of machine learning models.
By the end of the module, they will have gained the confidence to apply basic programming and machine learning techniques in professional contexts and have a strong foundation for further study in applied AI.
(30 credits)
This module provides an introduction to AI, designed for students from a wide range of academic and professional backgrounds. It offers a conceptual framework for understanding what AI is, how it has developed over time and how it is applied today, without assuming prior technical or mathematical expertise.
The module begins by exploring key milestones in the history of AI. Students will be introduced to the main techniques that have shaped the field, including classical symbolic AI methods and modern approaches such as machine learning, and will examine the contexts in which different techniques are effective or limited.
Throughout the module, emphasis is placed on critical evaluation. Students will analyse the major achievements of AI alongside its shortcomings, limitations, and unresolved challenges. Particular attention is given to understanding the differences and commonalities between classical and modern approaches, helping students to develop a balanced and nuanced view of AI as a field of practice.
(15 credits)
This module explores what it means to design and deploy AI responsibly in real-world professional contexts. It is designed for students from a wide range of disciplinary backgrounds who want to understand the ethical, legal and security challenges associated with contemporary AI systems, and their own responsibilities when working with these technologies.
The module introduces key concepts in AI security, including issues such as data protection, governance and emerging risks. Alongside this, students are introduced to core ethical and legal principles, including standards and regulatory approaches that are developing in response to the rapid adoption of AI technologies.
A distinctive feature of the module is its focus on professional responsibility and reflective practice. Students are encouraged to consider their own roles, judgement and decision-making when engaging with AI, and to reflect on transferable skills such as initiative, responsibility and ethical awareness. By the end of the module, students will be equipped to engage critically and responsibly with AI in professional contexts.
(15 credits)
Group one modules
Compulsory module
This module takes a detailed look at the ways in which artificial intelligence (AI) impacts strategy, now and into the future. Recent years have seen rapid developments in AI techniques and abilities. Many aspects of AI have potential military applications, and some have already begun to be employed by armed forces and other security actors. AI has the potential to dramatically alter some fundamental tenets of strategy; reshaping human society and the organisations that wage war; and posing acute ethical dilemmas.
(15 credits)
Optional modules (choose one)
Artificial intelligence and machine learning will be among the primary catalysts of social, economic, scientific, political and legal change in the 21st century. Discussions of AI regulation have gathered force in the wake of notable performance leaps in machine learning, particularly in the domains of image recognition, natural language processing, content generation, and deep learning. Given the transformative potential of AI, there are concerns about how far the law can and should adapt to the profound technological changes ahead.
This module provides students with a legal, social-scientific and technical introduction to the current AI discussion that requires no formal computational or mathematical background. This course is primarily intended to explain what AI is, how it works, and to provide an understanding of the current efforts to regulate its use. It will also provide a series of technical examples that will give students a set of skills that can be applied in practice.
(15 credits)
Artificial intelligence (AI) is a widely applied technology from conversational interfaces (Siri, Alexa, chatbots) to self-driving cars, from medical apps to assisting in policing and social care. By mapping a broad range of applications, issues arising, and key debates, this module will equip students with a deep and systematic understanding of AI and an overview of current developments in AI. By studying applied AI in context, students will also acquire the ability to critically and ethically evaluate applications in their own substantial investigations.
The module contextualises artificial intelligence from the following three perspectives: students will evaluate applications of AI in different fields and learn about the technical concepts driving these applications; students will systematically learn about the challenges AI poses for society; and last but not least, the module will also reflect on potential responses to curb AI including policy answers and regulations.
(15 credits)
This module explores the relationship between Artificial Intelligence (AI) and public policy, focusing on how governments, regulators, and public institutions respond to the opportunities and challenges posed by AI. Rapid advances in AI are transforming economies, public services, and systems of governance, while raising complex questions around regulation, accountability, ethics, and societal impact.
The module introduces students to key policy debates surrounding AI, including data governance, algorithmic bias, transparency, privacy, and security. It examines how different political systems and international actors are approaching AI governance, and evaluates the effectiveness of existing regulatory frameworks. Students will also explore how AI is being used within government, including in policy design, public service delivery, and decision-making processes.
Drawing on real-world case studies, the module develops students’ ability to critically analyse policy responses to AI and to design informed, responsible, and context-sensitive policy interventions. No prior technical background is required; the focus is on understanding AI as a policy challenge and governance problem rather than a purely technical system.
(15 credits)
This module is designed for students from a wide range of academic and professional backgrounds. It will introduce students to the wide spectrum of intelligence from historical, cultural and philosophical perspectives. Building a broader understanding of intelligence will allow students to develop critical knowledge that will help them address challenges and biases arising from narrow AI-centric views of intelligence.
In this module, we will engage with different ideas about intelligence found in philosophy, literature, history, political science and other disciplines to examine how the definitions of intelligence vary across time and space. We will interrogate the constructed nature of intelligence and the implications of this for our societies and cultures.
This module will equip students with knowledge and competencies for life, such as being able to consider multiple perspectives, make informed decisions, generate new ideas and impact the development of strategic areas of society. The focus, topics and approach to learning that combines historical and speculative modes of critical thought is, in particular, suited for students who already have background in or consider socially engaged careers in areas such as public, social and cultural policies, education, law, digital advocacy, security, and related fields.
(15 credits)
Group two modules
Compulsory module
This module examines the relationship between international security and emerging disruptive technologies, with a particular focus on the growing role of artificial intelligence in shaping contemporary and future security environments. It is designed for students who may not have a technical background but who require sufficient technical literacy to understand how advanced technologies influence security policy, military capability, strategic competition and global governance.
The module introduces students to the key concepts and debates in international security and strategic studies, before examining how emerging technologies — particularly artificial intelligence, autonomous systems, cyber capabilities, data analytics, space technologies and advanced sensing systems — are transforming the character of conflict, deterrence, intelligence and defence innovation. Students explore how these technologies affect strategic stability, escalation dynamics, military effectiveness, and national security policy, as well as the ethical, legal and governance challenges associated with their development and deployment.
Throughout the module, students engage with interdisciplinary perspectives that combine strategy, policy, technological understanding, ethics and regulation. Emphasis is placed on helping students translate technical developments into meaningful security analysis and insight. Case studies drawn from contemporary international security challenges are used to illustrate how emerging technologies influence geopolitical competition, defence innovation and global security governance.
By the end of the module, students will be able to critically analyse how artificial intelligence and other emerging technologies are shaping international security, and apply structured analytical approaches to evaluate their implications for governments, defence organisations, international institutions and industry.
(15 credits)
Optional modules (choose one)
As artificial intelligence increasingly integrates into our daily lives, it forces us to re-examine fundamental philosophical questions about moral responsibility, human agency, and what it means to lead a meaningful life. This module provides a rigorous introduction to the most pressing contemporary debates in the ethics of AI.
Drawing on cutting-edge scholarship, this course investigates how traditional ethical concepts apply to a world shared with advanced algorithms and autonomous machines. Students will move beyond the headlines to critically engage with both the immediate societal risks of AI and the long-term existential questions it raises.
(15 credits)
This module examines how artificial intelligence should be governed across legal, regulatory, organisational, and technical contexts. It introduces students to the core principles and frameworks used to oversee AI systems, including safety, accountability, transparency, fairness, human oversight, and institutional responsibility. Students will explore how governments, regulators, companies, and civil society actors respond to the risks and opportunities created by AI, and how governance approaches differ across jurisdictions and sectors.
Through contemporary case studies and practical problems, the module develops students’ ability to assess AI governance challenges in real-world settings. It is designed for students who want to understand both the broader policy landscape and the concrete governance tools used to manage AI in practice.
(15 credits)
Artificial intelligence is reshaping education at every level, from curriculum design and classroom practice to assessment, professional development and wider policy. This module introduces the student to the opportunities and challenges surrounding the use of AI in educational settings, with a particular focus on the implications for teaching and assessment practices, and new learning strategies.
Across five sessions, the student will explore key topics including: AI literacy and the place of AI within contemporary curricula; pedagogies that make purposeful and responsible use of AI; and the evolving role of the teacher in AI-rich learning environments. The student will learn to imagine and critically evaluate possible educational futures shaped by AI.
A core feature of the module is its applied orientation. The student will have opportunities to experiment with generative AI tools, critically evaluate their educational value, and design learning activities or practices that promote understanding, creativity and learner agency. Students will select a GenAI tool available in the market to experiment with and critically analyse its use in typical educational activities.
By completing this module, the student will develop practical and theoretical skills that are increasingly essential in contemporary education: critical and ethical evaluation of AI tools, design of AI-informed learning activities, awareness of equity and inclusion considerations, and confidence in navigating emerging educational futures.
(15 credits)
This module introduces students to the creative application of generative AI for synthetic media production. Students will develop practical competence in node-based AI workflows, progressing through text, image, sound, and video generation to produce creative works.
The module combines hands-on technical practice with critical analysis of generative AI as a cultural and creative medium. Students will learn to design, implement, and modify AI generation workflows using industry-standard tools, while examining the aesthetic, ethical, and industrial implications of AI-mediated creative practice.
The module is designed for students pursuing careers in cultural and creative industries, cultural production, media, and design who wish to integrate AI tools into their professional practice with both technical competence and critical depth. Delivered online through asynchronous materials and intensive synchronous workshops, the module emphasises peer collaboration and iterative creative development.
(15 credits)
Dissertation
This module introduces students to the methodological principles, research design decisions and critical questions that underpin postgraduate inquiry in applied artificial intelligence. It is designed to support students from diverse disciplinary and professional backgrounds as they prepare for independent research, recognising that projects within the programme will take a variety of forms.
A central focus of the module is the relationship between research questions, methodological choices and forms of evidence. Students are encouraged to examine how different types of questions generate different research strategies, and how epistemological assumptions influence the design, conduct and interpretation of research. The module introduces both quantitative and qualitative approaches, alongside the use of theory, historical perspectives, documentary analysis and critical source evaluation.
Particular attention is given to the challenges of research in contemporary AI-related contexts, including the selection and interpretation of datasets, the limitations and biases of available evidence, and the ethical implications of working with digital sources, algorithmic outputs and emerging technologies.
The module is designed to support a broad range of dissertation directions across the programme’s pathways. By the end of the module, students will be able to develop a coherent research plan that demonstrates clear methodological justification.
(15 credits)
This module provides students with the opportunity to undertake a substantial independent research project focused on an applied artificial intelligence issue relevant to their pathway, professional context or disciplinary interests. It represents the culmination of the programme and enables students to bring together technical understanding, critical analysis and methodological rigour in the investigation of a defined research problem.
The project may take a range of forms depending on the nature of the research question, including empirical investigation, critical analysis, policy evaluation, legal or ethical inquiry, artefact construction, or the development of an applied professional framework. Students are expected to demonstrate intellectual independence, engaging critically with relevant evidence, literature, datasets or professional sources.
A central feature of the project is the expectation that students will critically examine how knowledge is produced, interpreted and applied within contemporary AI-related contexts. Particular attention is given to the responsible use of evidence, ethical awareness and the limitations of sources.
Through supervised independent study, students will produce an extended piece of work that demonstrates originality, critical judgement and the ability to communicate complex ideas clearly and persuasively.
(45 credits)
Important
You're required to take modules totalling 180 credits.
King’s College London reviews the modules offered on a regular basis to provide up-to-date, innovative and relevant programmes of study. Therefore, modules on offer may change from year to year.