Module Specification

AI-Powered Innovation: Valuable Use Cases for Public Sector

Module Specification

AI-Powered Innovation: Valuable Use Cases for Public Sector



Unlock the potential of AI in the public domain with our bespoke short course, tailored specifically for UK's public sector professionals. Dive into real-world applications, where artificial intelligence is not just a buzzword, but a transformative tool driving efficiency, innovation, and smarter service delivery in government. Over an engaging series of learning activities, you will explore compelling AI strategies, understand how to harness data through intelligent algorithms, and also look at analytics to assist tasks, make informed decisions, and ultimately elevate public service. Benefit from insights on ethical considerations and practical adoption challenges, ensuring AI is used responsibly and effectively. Discover tactical use cases that resonate with public service. This cutting-edge learning experience, backed by concepts, case studies, and AI feedback, will equip you with the skills to spearhead AI initiatives within your organization, delivering value that justifies your investment in your future.



Prerequisites and Co-requisites

None

Learning Outcomes

Code Attributes developed Outcomes
LO1 Knowledge and Understanding Analyse case studies for AI's influence in public healthcare improvement
LO2 Knowledge and Understanding Comprehend AI's roles and impacts within UK's public services framework
LO3 Knowledge and Understanding Explain AI ethical implications in data privacy and citizen rights
LO4 Knowledge and Understanding Interpret AI's utility in enhancing policy-making and governance processes
LO5 Knowledge and Understanding Understand AI integration in smart city development and urban management
LO6 Intellectual Skills Appraise the potential and limitations of machine learning in predictive tasks
LO7 Intellectual Skills Assess the effectiveness of NLP in citizen-government interactions
LO8 Intellectual Skills Critically evaluate AI solutions against current public sector challenges
LO9 Intellectual Skills Evaluate AI trends and predict future prospects in public service
LO10 Intellectual Skills Synthesise knowledge of AI tools to propose innovative public services
LO11 Technical/Practical Skills Analyse AI models using machine learning
LO12 Technical/Practical Skills Analyse computational artefacts to solve sector-specific problems
LO13 Technical/Practical Skills Identify AI problem-solving methods within public institutions
LO14 Technical/Practical Skills Understand data management strategies for AI applications
LO15 Technical/Practical Skills Understand NLP tools to interpret and categorise data
LO16 Professional/Transferable Skills Demonstrate skill in steering AI-driven public sector projects
LO17 Professional/Transferable Skills Display initiative in adapting AI solutions for operational improvement
LO18 Professional/Transferable Skills Plan AI strategies within a professional, legal, and ethical framework
LO19 Professional/Transferable Skills Understand the role of AI technological advancements for both specialist and non-specialist audiences
LO20 Professional/Transferable Skills Work effectively in multi-disciplinary teams to produce AI solutions

Content Structure

Week Topic
Week 1 Introductory lecture
Introduces the module, outlining its relevance to the field and connections to other topics. It provides an overview of the content structure, key references, and assessment details.
Week 2 Introductory Chapter: Embracing AI in the UK Public Sector
In this chapter, you will discover AI's transformative role in enhancing society and public sector services, including the labour market and environmental planning. Delve into the course's value, objectives, and also the journey ahead for harnessing AI's potential responsibly and effectively.
Week 3 AI Basics: Understanding the Fundamentals of Artificial Intelligence
Through this chapter, you will grasp introductory AI concepts, including those powering machine learning. Learn how these foundations are building blocks for adding value to public services, such as through education, community feedback systems and public-private partnerships.
Week 4 Data Governance: The Keystone of AI Deployment
In this chapter, you will consider data management, which is pivotal for AI success. Data governance and the ethical use of data will be explored, as well as cybersecurity and FAIR data principles.
Week 5 Machine Learning: Predictive Power for Public Good
This chapter looks at key machine learning models and their potential impact on public services, such as environmental planning and public safety. Understand how predictive insights can optimise policy and decision-making.
Week 6 Natural Language Processing: Enhancing Citizen-Government Interaction
This chapter considers how to apply NLP for improved communication, including citizen engagement and healthcare. See how these tools can facilitate public feedback and aid in accessible digital services.
Week 7 AI in Healthcare: Revolutionizing Public Health Services
This chapter delves into AI healthcare applications, from tracking, disease prediction, pandemic prediction models, to personalized medicine. Understand the life-saving potential of AI in public health.
Week 8 Smart Cities: AI-Driven Urban Planning and Management
This chapter focusses on AI in urban development, including smart infrastructure. Examine how AI informs smarter, liveable city planning, such as city management and civic tech.
Week 9 AI in Policy-Making: Informed Decisions, Better Governance
In this chapter, discover the role of AI in shaping policy. Learn about methods that can aid policymakers in decision-making through data-driven insights, including risk management, prediction, and budget planning.
Week 10 Law and Ethics of AI: Safeguarding Rights and Privacy
This chapter dives into the ethical landscape of AI. Discuss privacy, bias, and accountability to ensure technology serves the public without compromising values, as well as AI enabled forecasting and policy simulations.
Week 11 Strategising and and Overcoming Challenges: Implementing AI in Public Institutions
This chapter identifies common obstacles to AI adoption and strategies to overcome them. Discuss change management, upskilling, and fostering innovation-friendly environments, together with value realisation, ROI analysis, and scalability of AI solutions.
Week 12 Future Horizon: AI Trends and Prospects in Public Service
This chapter look to the future of AI. Consider emerging trends, such as data analytics, cognitive automation, cloud and edge computing, and e-Governance, and prepare for the evolving landscape of public service AI.

Student Workload

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.

Activity
Introductory lecture
Concept learning (knowledge graph)
AI formative assessment
Case Study Review
Independent reading, exploration and practice
Total:

Teaching and Learning Methods

Activity Description
Introductory lecture

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.

Concept learning (knowledge graph)

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.

AI formative assessment

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.

Case Study Review

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.

Independent reading, exploration and practice

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.


Module Approval

Stage Version Date of approval Authority Chair Revalidation
Compliance 1.0 Academic Board Dr Paresh Kathrani
Pre-Teaching 1.0 Director of Education Dr Paresh Kathrani
Note: The information detailed within this record is accurate at the time of publishing and may be subject to change.
Module Spec: AI-Powered Innovation: Valuable Use Cases for Public Sector (AI14)